An orthopedic shock index detection interaction method, system, device and medium

Abstract

The application provides a kind of orthopedics shock index detection interaction method, system, equipment and medium, it is related to medical information technology field, the method can respond to pulse value and systolic pressure value that user input is automatically calculated shock index by integrating vital sign input box and risk early warning area in main interface, and the main diagnosis information of patient is synchronously acquired, and shock assessment data is formed;When main diagnosis information contains orthopedics keywords, automatically activate the shock early warning logic specially customized for postoperative patients of orthopedics, comprehensive risk determination is carried out in combination with multidimensional clinical parameters, and graded early warning result is generated, and corresponding trigger basis is intuitively presented in risk early warning area, possible etiology explained in natural language form, structured disposal suggestion and operation record item for checking are provided, to realize the precise identification of postoperative patients of orthopedics shock risk, intelligent interpretation and closed-loop management, significantly improve the pertinence, operability and nursing response efficiency of clinical early warning.

Description

Technical Field

[0001] This application relates to the field of medical information technology, and in particular to an interactive method, system, device and medium for detecting shock index in orthopedic trauma. Background Technology

[0002] In orthopedic clinical nursing, especially for high-risk trauma patients such as those with pelvic fractures, the shock index is an important early warning indicator for assessing occult bleeding and circulatory compensation. However, existing technologies have significant shortcomings: on the one hand, traditional paper-based assessment forms rely on manual lookup and calculation, which is prone to errors or omissions due to nurses' lack of experience or busy schedules; on the other hand, even though some hospitals have deployed electronic medical record systems, their vital signs entry modules are mostly of a general design, lacking structured interactive logic specific to orthopedics, unable to automatically link pulse and systolic blood pressure data to generate the shock index in real time, and even less able to dynamically classify shock index values ​​and provide visual alerts. Summary of the Invention

[0003] This application provides an interactive method, system, device, and medium for detecting shock index in orthopedic trauma, in order to solve one or more technical problems existing in the prior art, and at least provide a beneficial option or create conditions to realize the automatic calculation, dynamic grading, and real-time visual early warning of shock index, thereby improving the efficiency of early identification of occult bleeding risk in postoperative orthopedic trauma patients and the timeliness of nursing intervention.

[0004] On the one hand, this application provides an interactive method for detecting shock index in orthopedic surgery, including the following steps: The main interface for displaying the shock index detection interaction includes a vital signs input box and a risk warning area. In the vital signs input box, the system receives the patient's pulse value and systolic blood pressure value input by the user, calculates the shock index, obtains the patient's primary diagnosis information, and generates shock assessment data. If the main diagnostic information includes orthopedic keywords, then activate the shock warning logic adapted to postoperative orthopedic patients; Based on the shock assessment data and the shock early warning logic, a comprehensive risk determination is performed to generate a Level 1, Level 2, or Level 3 early warning result, which is displayed in the risk warning area. The risk warning area displays the triggering basis, natural language etiology explanation, structured handling suggestions, and selectable operation record items corresponding to the warning result.

[0005] Furthermore, based on the shock assessment data and the shock early warning logic, a comprehensive risk determination is performed. Specifically, early warning levels are dynamically generated according to the following multi-parameter criteria, and the interactive status of each level of early warning is presented in the risk early warning area: Level 1 Warning: Triggered when 1.0 ≤ Shock Index < 1.5. In the risk warning area, the current shock index value and the prompt text "Level 1 Warning: Mild Shock" are displayed in green, and a pop-up layer of treatment suggestions corresponding to the Level 1 warning automatically appears; the treatment suggestion pop-up layer is used to display a set of treatment suggestions. Level 2 warning: Triggered when 1.5 ≤ Shock Index < 2.0 or when the time-series joint criterion based on the trend of postoperative drainage volume change and the trend of shock index change is met. In the risk warning area, the current shock index value and the prompt text "Level 2 warning: moderate shock" are highlighted in yellow, and the corresponding treatment suggestion pop-up layer is automatically displayed. Level 3 warning: Triggered when the shock index is ≥2.0, the systolic blood pressure is lower than the first systolic blood pressure threshold, or the pulse exceeds the first pulse threshold. In the risk warning area, the current shock index value and the prompt text "Level 3 warning: severe shock" are displayed in red. At the same time, an audio-visual reminder is triggered, and a pop-up layer of treatment suggestions corresponding to the Level 3 warning and a notification confirmation window from the on-duty physician automatically appear.

[0006] Furthermore, the handling suggestion overlay includes an operation log control; the generation process of the handling suggestion overlays corresponding to Level 1, Level 2, and Level 3 warnings includes the following steps: In response to the determination of the warning level, the corresponding set of treatment suggestions is matched from the preset orthopedic shock treatment rule base, and the set of treatment suggestions is displayed in the form of a list in the treatment suggestion floating layer; in: The recommended treatment for a Level 1 warning includes "oxygen administration via tubing" and "replenishing with sufficient isotonic saline or balanced electrolyte solution"; The recommended treatment for a Level II alert includes "administer oxygen via face mask", "monitor cardiac function", "measure vital signs every 15-30 minutes", "establish two intravenous access lines to rapidly expand blood volume", "draw blood for further examination and prepare for blood transfusion", and "insert urinary catheter". The recommended procedures for Level 3 alerts include: "Administer oxygen via face mask", "monitor cardiac function", "measure vital signs every 15 minutes", "notify the ICU to assist in resuscitation", "clean the ward and create a resuscitation environment", "notify family members to come to the ward", "establish two or more intravenous access lines to rapidly expand blood volume", "draw blood and notify the blood transfusion department for emergency blood matching", and "prepare oxygen bags, move the cardiac monitor, and prepare for transport". In response to a trigger command on the operation record control, a selectable list of completed operations is provided, and the selected records are saved to the patient's electronic nursing log for closed-loop tracking and quality control analysis.

[0007] Furthermore, the main interface includes a traffic flow trend analysis control, a shock index change slope calculation control, and a joint risk assessment control; The timing joint criterion is executed in the main interface to identify the risk of occult bleeding, specifically including the following steps: In response to the trigger command of the drainage flow trend analysis control, a drainage flow time series chart window is displayed, the drainage flow data of the patient at the most recent N consecutive time points after surgery are loaded, and the slope of drainage flow change is generated by linear regression fitting; In response to the trigger command of the shock index change slope calculation control, the shock index trend comparison window is displayed, the difference between the current shock index and the previous measurement value is calculated and divided by the time interval between the two measurements to generate the shock index change slope. In response to the trigger command of the joint risk judgment control, a preset joint criterion rule library is invoked to determine whether the condition of "the slope of the traffic flow change > the first traffic flow slope threshold or the slope of the shock index change > the first index slope threshold" is met. If the judgment result meets the above conditions, a level-two warning will be automatically triggered in the risk warning area.

[0008] Furthermore, the main interface also includes multi-source data comparison controls and conflict resolution operation controls; The conflict resolution of multi-source vital sign data is performed in the main interface, specifically including the following steps: It receives multi-source vital sign data from monitors, wearable devices, and manually entered data. When the difference in pulse values ​​from different sources exceeds the first pulse difference threshold, or the difference in systolic blood pressure exceeds the first blood pressure difference threshold, it pauses the alarm triggering and highlights the multi-source data comparison control on the interface. In response to the trigger command of the multi-source data comparison control, a data conflict card window pops up, listing the timestamp, value and device type of each data source; In response to the trigger command of the conflict resolution operation control, the system provides the options of "using monitor data", "using wearable data" or "manual retesting". After the user selects the option, the shock index is recalculated with the selected data and the warning logic is resumed.

[0009] Furthermore, the risk warning area also includes etiology prompt controls and clinical evidence display controls; Implementing shock precipitation based on structured clinical rules in the risk warning area specifically includes the following steps: In response to triggering a level 2 or 3 alert, the system reads the patient's current drainage volume, pain score, body position record, and surgical type data. In response to the trigger command of the etiology prompt control, a preset orthopedic shock induced rule base is invoked, which contains multiple if-then structured rules; According to the matching rules, corresponding variables are filled from the preset natural language template to generate the natural language etiology explanation; In response to the trigger command of the clinical evidence display control, the specific vital sign values ​​and rule numbers on which the judgment is based are listed in the sub-window.

[0010] Furthermore, the main interface also includes a patient complaint entry control; Performing a comprehensive risk assessment that incorporates the patient's subjective description on the main interface includes the following steps: In response to a trigger command on the patient's complaint entry control, a structured symptom selection window is displayed, providing options for preset symptoms related to shock, including at least "dizziness", "palpitations", "cold sweats", "thirst", "irritability" and "confusion". It receives one or more symptom options selected by medical staff, records the symptom entry time, and generates structured chief complaint symptoms; When at least one of the chief complaints is selected and the patient is currently in a shock warning logic that is suitable for postoperative orthopedic patients, a chief complaint weighting factor is introduced into the comprehensive risk assessment. If the shock index is ≥ 0.9 and any of the preset symptoms are present, a Level 1 warning will be triggered in advance; if the shock index is ≥ 1.3 and any of the preset symptoms are present, a Level 2 warning will be triggered in advance, and the patient's chief complaint and corresponding clinical significance will be highlighted in the risk warning area.

[0011] On the other hand, this application provides an interactive system for detecting shock index in orthopedic trauma, comprising: The main interface module is configured to display the main interface for shock index detection interaction, the main interface including a vital signs input box and a risk warning area; The input processing module is configured to: receive the patient's pulse value and systolic blood pressure value input by the user in the vital signs input box, calculate the shock index, obtain the patient's primary diagnosis information, and generate shock assessment data; if the primary diagnosis information includes orthopedic keywords, then activate shock early warning logic adapted to orthopedic postoperative patients. The risk warning module is configured to: perform a comprehensive risk assessment based on the shock assessment data and the shock warning logic, generate a level 1, level 2, or level 3 warning result, and display it in the risk warning area; and display the triggering basis, natural language etiology explanation, structured treatment suggestions, and selectable operation record items corresponding to the warning result in the risk warning area.

[0012] On the other hand, this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned interactive method for detecting shock index in orthopedic trauma.

[0013] On the other hand, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned interactive method for detecting shock index in orthopedics.

[0014] The beneficial effects of this application are as follows: This application provides an interactive method for detecting shock index in orthopedic trauma patients. This method integrates a vital signs input box and a risk warning area on the main interface. It can automatically calculate the shock index in response to user-inputted pulse and systolic blood pressure values, and simultaneously acquire the patient's primary diagnostic information to form shock assessment data. When the primary diagnostic information contains orthopedic trauma keywords, the system automatically activates a shock warning logic specifically tailored for post-operative orthopedic trauma patients. It combines multi-dimensional clinical parameters for comprehensive risk assessment, generating Level 1, Level 2, or Level 3 warning results. The corresponding triggering criteria, possible causes explained in natural language, structured treatment suggestions, and selectable operation record items are intuitively presented in the risk warning area. This achieves accurate identification, intelligent interpretation, and closed-loop management of shock risk in post-operative orthopedic trauma patients, significantly improving the pertinence, operability, and nursing response efficiency of clinical warnings. This application also provides the corresponding system, equipment, and media for the above method. The beneficial effects of the system, equipment, and media are similar to those of the above method and will not be elaborated further here.

[0015] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0016] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0017] Figure 1 This is a flowchart of the interactive method for detecting shock index in orthopedics provided in this application; Figure 2 This is a schematic diagram of the main interface for the shock index detection interaction provided in this application; Figure 3 This is a structural diagram of the orthopedic shock index detection interactive system provided in this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] The present application will be further described below with reference to the accompanying drawings and specific embodiments. The described embodiments should not be considered as limitations on the present application, and all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of the present application.

[0020] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0022] In orthopedic clinical nursing practice, postoperative patients, especially high-risk groups following pelvic fractures, proximal femoral fractures, or spinal surgery, often face a high risk of circulatory instability due to factors such as extensive trauma, hidden bleeding, severe pain, and limitations in immobilization. The shock index, the ratio of pulse to systolic blood pressure, is an important non-invasive indicator for assessing the presence of hidden bleeding or early compensatory shock. Compared to relying solely on single parameters such as blood pressure or heart rate, the shock index more sensitively reflects hypovolemia, especially in the early stages when systolic blood pressure has not yet significantly decreased but heart rate has already increased compensatorily, demonstrating significant early warning value. Therefore, incorporating the shock index into the routine monitoring system for postoperative orthopedic patients is of great significance for achieving early detection, early intervention, and reducing the incidence of complications and mortality.

[0023] Currently, the clinical application of the shock index relies primarily on manual calculation and subjective judgment. After measuring vital signs, nurses must manually record pulse and systolic blood pressure values, then calculate the shock index mentally or using a calculator, and finally compare it with empirical thresholds to determine the risk level. This process is not only time-consuming and labor-intensive, but also highly susceptible to missed or false alarms due to calculation errors, omissions in recording, or judgment biases. Although some hospitals have deployed electronic medical record systems or mobile nursing terminals, their vital sign entry modules are mostly of general design, lacking structured data collection logic specific to orthopedic specialties. They cannot automatically correlate pulse and systolic blood pressure to generate the shock index in real time, nor can they combine key clinical variables such as postoperative duration, primary diagnosis type, pain score, and patient complaints for comprehensive risk assessment. Furthermore, existing systems typically only provide numerical displays or simple threshold alarms, lacking interpretability support for the warning results. For example, they do not explain why the warning was triggered, what the possible causes are, or what specific measures should be taken, making it difficult for frontline nurses to quickly understand the source of risk and implement effective treatment.

[0024] More critically, current technologies fail to fully consider the unique pathophysiological characteristics of post-orthopedic patients. For example, even if blood pressure is maintained within the normal range, patients with pelvic fractures may experience elevated shock indices due to persistent bleeding from retroperitoneal hematomas; elderly patients, due to decreased vascular elasticity, have limited cardiac rate compensation capabilities, resulting in shock index patterns that differ from the general population; and early postoperative heart rate increases caused by pain stimulation may lead to false positives. However, currently used vital sign monitoring tools do not establish differentiated warning logic for these specialized scenarios, resulting in insufficient warning sensitivity and specificity. Furthermore, even when the system issues an alert, it often relies on pop-up blocking notifications, disrupting normal workflows and lacking a closed-loop linkage mechanism with nursing operation records, making it difficult to translate warning information into traceable clinical behavior.

[0025] In summary, existing technologies have significant shortcomings in areas such as automated calculation of the shock index, specialized risk modeling, fusion of multi-source clinical data, interpretability of early warning results, and closed-loop human-computer interaction, making it difficult to meet the needs of orthopedic postoperative patients for refined, intelligent, and timely shock risk monitoring.

[0026] To address the aforementioned issues, this application constructs an intelligent shock index detection and interactive system for postoperative orthopedic patients. By integrating vital sign input boxes and risk warning areas into the user interface, it enables structured input of pulse and systolic blood pressure data and automatic calculation of the shock index. The system can simultaneously acquire the patient's primary diagnosis information and postoperative duration, forming multidimensional shock assessment data. When the primary diagnosis contains orthopedic keywords, it automatically activates a disease-specific shock warning logic. Based on this logic, it performs a comprehensive risk assessment of the patient, generating Level 1, Level 2, or Level 3 warning results. The warning window presents the triggering basis, etiological explanation, structured treatment suggestions, and selectable operation record items in natural language, thereby deeply integrating specialist knowledge, clinical data, and human-computer interaction to achieve closed-loop management from risk identification to intervention execution, significantly improving the accuracy, interpretability, and clinical operability of the warnings.

[0027] First, the interactive method for detecting shock index in orthopedics provided in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0028] Reference Figure 1 The implementation process of the orthopedic shock index detection interactive method provided in this application embodiment includes, but is not limited to, the following steps.

[0029] Step S110: Display the main interface of the shock index detection interaction.

[0030] Among them, reference Figure 2 The main interface includes a vital signs input box and a risk warning area.

[0031] In step S110, a unified operation portal is provided for medical staff specifically for monitoring the shock risk of postoperative orthopedic patients. The main interface, as the core carrier of human-computer interaction, integrates vital sign input boxes and risk warning areas, allowing users to complete data entry and risk viewing without switching between multiple systems or modules. This integrated design not only simplifies the operation process but also ensures the visibility and accessibility of key functions, effectively avoiding missed or delayed assessments caused by scattered interfaces or hidden functions, thus laying the foundation for subsequent automatic calculations and intelligent warnings.

[0032] Step S120: In the vital signs input box, the patient's pulse value and systolic blood pressure value are received by the user, the shock index is calculated, the patient's primary diagnosis information is obtained, and shock assessment data is generated.

[0033] In step S120, structured acquisition of multi-source clinical data and automated generation of the shock index are achieved. When the user enters the patient's pulse and systolic blood pressure values ​​in the vital signs input box, the system immediately calculates the shock index as the quotient of the pulse value divided by the systolic blood pressure value, while simultaneously proactively linking it to the primary diagnosis information in the electronic medical record. This process breaks through the traditional approach of relying solely on a single vital sign, deeply integrating physiological parameters with clinical context, significantly improving the comprehensiveness and individualization of risk assessment.

[0034] Step S130: If the main diagnostic information includes orthopedic keywords, then activate the shock warning logic adapted to postoperative orthopedic patients.

[0035] In step S130, a specialty adaptation mechanism is introduced to achieve precise activation of the early warning logic. The system dynamically determines whether the current patient belongs to the target high-risk group by identifying whether the primary diagnostic information contains orthopedic keywords, such as pelvic fracture, femoral neck fracture, or spinal injury. Only when confirmed as a post-orthopedic surgery patient is a customized shock early warning rule activated, such as adjusting the shock index threshold, incorporating the weight of high-incidence periods of post-operative bleeding, and considering interfering factors like pain-induced increased heart rate. This on-demand activation strategy avoids misjudgments by general early warning models in specialty scenarios, improving the system's clinical applicability and professionalism.

[0036] Step S140: Based on shock assessment data and shock early warning logic, perform comprehensive risk determination, generate Level 1, Level 2, or Level 3 early warning results, and display them in the risk warning area.

[0037] In step S140, a multi-dimensional risk assessment is performed, and a graded early warning result is output. Based on the aforementioned generated shock assessment data, combined with the activated orthopedic-specific early warning logic, the system comprehensively considers factors such as shock index values, postoperative time windows, primary diagnosis type, pain intensity, and symptom presentation. It employs a weighted or rule-based engine approach for intelligent analysis, ultimately generating early warning results of different levels: Level 1, Level 2, or Level 3. This grading mechanism reflects the urgency of the risk, guides medical staff to take appropriate response measures, and ensures timely delivery of warning information by displaying the risk warning area in real time, preventing delays in intervention.

[0038] Step S150: Display the triggering basis, natural language etiology explanation, structured handling suggestions, and selectable operation record items corresponding to the warning results in the risk warning area.

[0039] In step S150, the interpretability of the warning information and the clinical operation closed loop are achieved. The risk warning area not only displays the warning level, but also shows the specific basis for triggering the warning, such as a shock index of 1.1 and being in the high-risk period of 12 to 24 hours postoperatively. It also explains possible causes in natural language, such as suggesting possible occult retroperitoneal hemorrhage, and provides structured treatment suggestions, including rechecking hemoglobin, accelerating fluid resuscitation, and notifying the doctor. In addition, there are checkboxes for operation recording, allowing nurses to directly mark the completion status after execution, forming a complete closed loop from warning to execution to recording. This design greatly enhances the practicality, credibility, and enforceability of the warning, truly transforming intelligent judgment into clinical action.

[0040] In some embodiments of this application, in step S140, a comprehensive risk determination is performed based on shock assessment data and shock warning logic. Specifically, warning levels are dynamically generated according to the following multi-parameter criteria, and the interactive states of each warning level are presented in the corresponding risk warning area.

[0041] (1) Level 1 warning: Triggered when 1.0≤shock index<1.5. In the risk warning area, the current shock index value and the prompt text "Level 1 warning: mild shock" are displayed in green and a floating layer of treatment suggestions corresponding to the Level 1 warning will pop up automatically. The floating layer of treatment suggestions is used to display the set of treatment suggestions.

[0042] Specifically, when the shock index is between 1.0 and 1.5, the system determines that the patient is in a state of mild shock, corresponding to the first-level warning in clinical guidelines. At this time, the current shock index value and the first-level warning text "Mild Shock" are highlighted in green in the risk warning area. This visual design not only conforms to the medical staff's habit of quickly recognizing color codes, but also effectively reduces the risk of misjudgment. At the same time, the system automatically pops up a pop-up layer with treatment suggestions corresponding to the first-level warning. This pop-up layer centrally displays the standard treatment measures for mild shock, helping medical staff to quickly take standardized interventions and prevent the condition from progressing.

[0043] (2) Level II warning: When 1.5≤shock index<2.0 or when the time-series joint criterion based on the postoperative drainage change trend and the shock index change trend is met, the current shock index value and the prompt text "Level II warning: moderate shock" are displayed in yellow in the risk warning area, and the corresponding treatment suggestion pop-up layer is automatically displayed.

[0044] Specifically, when the shock index reaches the range of 1.5 to 2.0, or even if it does not reach this value but the system analyzes the trends in postoperative drainage volume and shock index and finds that both are deteriorating synchronously, meeting the preset time-series joint criterion, the system triggers a level-two warning. The significance of this mechanism is to capture atypical manifestations such as occult bleeding or early circulatory instability, avoiding missed warnings caused by relying on a single indicator. At this time, the interface uses yellow highlighting to indicate the current shock index value and the level-two warning: moderate shock warning text, providing a prominent visual signal to indicate moderate risk. Simultaneously, a pop-up layer of treatment suggestions corresponding to the level-two warning automatically appears, ensuring that the clinical team can promptly initiate volume resuscitation and monitoring procedures, gaining valuable time for subsequent treatment.

[0045] (3) Level 3 warning: When the shock index is >2.0, the systolic blood pressure is lower than the first systolic blood pressure threshold, or the pulse exceeds the first pulse threshold, the current shock index value and the prompt text "Level 3 warning: severe shock" are displayed in red in the risk warning area. At the same time, the sound and light reminder is triggered, and the corresponding treatment suggestion pop-up and the on-duty physician notification confirmation window are automatically displayed.

[0046] Specifically, when the shock index exceeds 2.0, or the systolic blood pressure falls below the set first systolic blood pressure threshold, or the pulse exceeds the first pulse threshold, the system determines that the patient has entered a state of severe shock and immediately triggers a level-three warning. This multi-condition triggering mechanism enhances the system's robustness; even if the shock index is distorted due to extreme hypotension or bradycardia, the highest level of response can still be initiated based on other critical vital signs. On the interface, the system displays the current shock index value and the level-three warning text (severe shock) in red. Red, as an internationally recognized emergency warning color, instantly attracts the attention of medical staff.

[0047] Simultaneously, the system not only automatically pops up a comprehensive treatment suggestion overlay but also forcibly triggers audio-visual alerts. More importantly, the system immediately pops up a notification confirmation window for the on-duty physician, requiring nursing staff to check "Doctor has been notified by phone" and enter the doctor's employee number or name, ensuring that high-risk events are reported in a timely manner and tracked in a closed loop. This constructs a complete emergency response chain from automatic identification and graded alerts to mandatory intervention, significantly improving the timeliness and safety of rescuing patients in severe shock.

[0048] In some embodiments of this application, the setting of warning thresholds at each level is based on the clinical characteristics and evidence-based medicine of post-orthopedic patients. A shock index ≥1.0 serves as the starting point for Level 1 warning, designed for patients with high bleeding risk, such as those with pelvic fractures or proximal femoral fractures, who often exhibit increased heart rate while maintaining normal blood pressure during the compensatory phase; this threshold is more sensitive than general thresholds. A shock index ≥1.5 corresponds to a clear state of volume insufficiency and serves as the Level 2 warning threshold, effectively identifying progressive bleeding. A shock index >2.0 indicates severe circulatory failure, and combined with absolute physiological limits such as systolic blood pressure below 90 mmHg or pulse exceeding 130 beats / min, these constitute the triggering conditions for Level 3 warnings. The above thresholds are referenced from the Advanced Life Support for Trauma (ATLS) guidelines and calibrated using clinical practice data in this field, applicable to adult post-orthopedic patients. The normal reference range is uniformly defined as 0.5 to 1.0, and the system defaults to this fixed range, but limited adjustments based on hospital configuration strategies according to age or diagnostic type are also supported.

[0049] In some embodiments of this application, the visual and interactive feedback mechanism of the risk warning area is implemented using standard web front-end technologies. The window border color is dynamically bound to the warning level via CSS styles: level one is green, level two is yellow, and level three is red. When a level three warning is activated, the border is animated with CSS animation effects, resulting in a fade-in / fade-out flashing effect that lasts for 3 seconds at a frequency of once per second, without interrupting other user operations. The handling suggestion overlay is presented as a non-modal pop-up window, located in the upper right corner of the main interface, without affecting the continued execution of the main process. The on-duty doctor notification confirmation window is a modal dialog box, which forces focus and disables background operations until the user completes the checkmark "On-duty doctor has been notified by phone" and enters the doctor's employee number or selects a name from the drop-down list before it can be closed, ensuring that high-risk events are confirmed and responded to.

[0050] The on-call physician notification confirmation window includes structured input fields: a dropdown list of physician names (data source: the hospital information system's daily shift schedule cache), automatically recorded notification time (accurate to the second), and automatically populated operator identity (based on the currently logged-in account). After user confirmation, the system generates a structured event log, including patient ID, warning level, trigger time, shock index, drainage trend status, notifying physician name, and confirmation time, and simultaneously writes it to the nursing event database, supporting subsequent quality control audits and adverse event retrospectives. Even without integration with the real-time scheduling system, basic functionality can be achieved through a static on-call schedule pre-maintained by the administrator.

[0051] In some embodiments of this application, the audio-visual alerts are auxiliary enhancement methods, and their triggering depends on the capabilities of the operating terminal. On devices with audio output, the system plays a preset short beep (frequency 1000 Hz, duration 800 milliseconds); on mobile devices or in a silent environment, it automatically downgrades to a bright flashing screen area and a status bar icon alert. Regardless of whether the audio-visual alerts are triggered, the core intervention mechanism is always a mandatory pop-up notification confirmation window for the on-call physician, ensuring that clinical response is not rendered ineffective due to environmental limitations.

[0052] In some embodiments of this application, the handling suggestion overlay includes an operation log control; the generation process of the handling suggestion overlays corresponding to Level 1, Level 2, and Level 3 warnings includes the following steps.

[0053] (1) In response to the determination of the warning level, the corresponding set of treatment suggestions is matched from the preset orthopedic shock treatment rule base, and the set of treatment suggestions is displayed in the form of a list in the treatment suggestion floating layer; Specifically, once the warning level is determined, the system first precisely matches a set of treatment suggestions corresponding to the current risk level from a pre-set orthopedic shock management rule base. This set is then presented in a clear list format in a floating layer of treatment suggestions, ensuring that medical staff can quickly access standardized, scenario-based treatment guidelines. This mechanism not only reduces omissions in treatment due to memory bias or experience differences but also enhances the standardization and timeliness of postoperative shock management in orthopedics, enabling frontline staff to efficiently execute critical measures even under high-pressure environments.

[0054] This orthopedic shock management rule base is stored in a database table format. Each record includes a warning level field (e.g., Level 1, Level 2, Level 3), a list of management suggestion IDs, an applicable surgical type label, and the effective status. The system performs precise queries using the current warning level as the primary key and returns the corresponding set of suggestions. For example, a Level 1 warning corresponds to suggestion IDs A01 and A02, which respectively map to "administer oxygen via oxygen tube" and "infuse sufficient isotonic saline or balanced electrolyte solution." If a rule supports multiple conditions (e.g., combined with surgical type), it should be stated that these are extended fields and do not affect the basic matching logic.

[0055] (2) In response to the trigger command of the operation record control, provide selectable completed operation items and save the selected records to the patient's electronic nursing log for closed-loop tracking and quality control analysis.

[0056] Specifically, after medical staff complete a procedure, they can trigger this control to check the corresponding completed operation item, and the system will automatically save the check record to the patient's electronic nursing log. This function realizes the digitalization of the entire process from suggestion issuance and execution confirmation to data archiving. It not only facilitates real-time tracking of the implementation of medical orders and prevents omissions or duplicate operations, but also provides structured and traceable original evidence for subsequent quality control, adverse event analysis, nursing performance evaluation, and scientific research data extraction, thereby promoting the transformation of shock management from experience-driven to data-driven and evidence-based management.

[0057] In some embodiments of this application, the set of treatment recommendations corresponding to a Level 1 warning includes "administer oxygen via oxygen tube" and "replenish with sufficient isotonic saline or balanced electrolyte solution." These two recommendations closely address the core issues of early volume depletion and potential bleeding risk in orthopedic patients, especially after pelvic fracture surgery. Oxygen therapy improves tissue oxygen supply, while electrolyte solutions rapidly replenish effective circulating blood volume. This combination of recommendations embodies the clinical principles of early intervention, stabilizing vital signs, and preventing disease deterioration, laying the foundation for subsequent observation and treatment.

[0058] In some embodiments of this application, the set of treatment recommendations corresponding to a Level II warning includes "administer oxygen via face mask," "monitor cardiac function," "measure vital signs every 15-30 minutes," "establish two intravenous access lines to rapidly expand blood volume," "draw blood for further examination and prepare for transfusion," and "insert a urinary catheter." These measures together constitute a complete emergency response system for moderate shock: oxygen via face mask improves oxygenation efficiency, cardiac monitoring and high-frequency vital sign monitoring enable dynamic assessment, dual intravenous access ensures rapid infusion of fluids and medications, laboratory tests provide a basis for transfusion decisions, and indwelling urinary catheters are used for precise monitoring of renal perfusion and volume responsiveness. The entire set of recommendations emphasizes both multidimensional monitoring and aggressive volume resuscitation, meeting the requirements for the early golden window of treatment in traumatic shock.

[0059] In some embodiments of this application, the set of treatment recommendations corresponding to the Level 3 warning includes "administer oxygen via face mask," "monitor cardiac electrocardiogram (ECG)," "measure vital signs every 15 minutes," "notify the ICU to assist in resuscitation," "clean the ward and establish a resuscitation environment," "notify family members to come to the ward," "establish two or more intravenous access lines to rapidly expand blood volume," "draw blood and notify the blood transfusion department for emergency blood matching," and "prepare oxygen bags, move the ECG monitor, and prepare for transport." This series of measures goes beyond the scope of ordinary nursing care and enters the multidisciplinary collaborative resuscitation stage. Its significance lies in not only maintaining basic life support but also simultaneously initiating the allocation of advanced life support resources, communication with family members, preparation of resuscitation space, and potential transport arrangements, ensuring that the patient receives the highest level of medical intervention in the shortest possible time and minimizing the risk of death.

[0060] In some embodiments of this application, the main interface includes drainage flow trend analysis controls, shock index change slope calculation controls, and joint risk assessment controls. Through the collaborative analysis of multidimensional dynamic parameters, the early identification capability of occult bleeding in postoperative orthopedic patients is improved. The execution of temporal joint criteria in the main interface to identify the risk of occult bleeding specifically includes the following steps.

[0061] Step S210: In response to the trigger command of the drainage flow trend analysis control, display the drainage flow time series chart window, load the drainage flow data of the patient's most recent N consecutive time points after surgery, and generate the slope of drainage flow change by linear regression fitting.

[0062] In step S210, postoperative drainage data is transformed from static records into quantifiable trend indicators. When medical staff click the drainage volume trend analysis control, the system automatically pops up a drainage volume time series chart window, loading drainage volume data for the patient's most recent N consecutive time points after surgery, where N is a preset value (e.g., 6 time points, corresponding to records every 2 hours, covering the most recent 12 hours). Subsequently, the system uses the least squares method to perform linear regression fitting on these discrete data points, generating a trend line and calculating its slope as a quantitative representation of the rate of change in drainage volume. The larger the positive value of this slope, the faster the drainage volume increases per unit time, suggesting possible active or progressive bleeding, thus providing an objective basis for subsequent joint judgment.

[0063] Optionally, the least squares method is used as the fitting method, and the input is a two-dimensional data point sequence of time-drainage flow. , , …, The output is a univariate linear equation. slope in The slope of the drainage volume change is expressed in milliliters per hour squared (mL / h²).

[0064] During the drainage volume trend analysis, the system has a data cleaning mechanism to eliminate outliers caused by non-bleeding factors. For example, when a sudden increase in drainage volume occurs due to surgical area irrigation, drainage tube compression, or recording errors, the system uses an outlier detection method based on the 3σ principle: it calculates the mean and standard deviation of the most recent N drainage volume data. If a data point deviates from the mean by more than three times the standard deviation, it is identified as an outlier and removed. Then, linear regression fitting is performed on the remaining valid data to ensure that the slope of the drainage volume change truly reflects the postoperative bleeding trend and avoids false positive warnings.

[0065] Step S220: In response to the trigger command of the shock index change slope calculation control, the shock index trend comparison window is displayed, the difference between the current shock index and the previous measurement value is calculated and divided by the time interval between the two measurements to generate the shock index change slope.

[0066] In step S220, the system accurately captures the dynamic evolution of the shock index. Responding to a trigger command on the shock index slope calculation control, the system displays a shock index trend comparison window. This window not only shows the current and historical shock index values ​​but also performs real-time calculations: subtracting the previous valid measurement value from the currently measured shock index, and then dividing the difference by the time interval between the two measurements (in hours), thus obtaining the shock index slope. This slope reflects the rate of deterioration of the circulatory compensation state. Even if a single shock index reading does not reach the traditional warning threshold, a rapid upward trend (e.g., above 0.1 / hour) may indicate continued blood volume loss. By structurally outputting this dynamic parameter, the system overcomes the limitations of relying solely on instantaneous values ​​to assess risk and enhances its sensitivity to early compensatory imbalances.

[0067] Step S230: In response to the trigger command of the joint risk judgment control, the preset joint judgment rule library is called to determine whether the condition of "the slope of the traffic flow change > the first traffic flow slope threshold or the slope of the shock index change > the first index slope threshold" is met.

[0068] In step S230, a multi-parameter fusion risk logic judgment is performed. When the user activates the joint risk judgment control, the system calls the preset joint judgment rule library, which contains composite condition rules specifically designed for occult bleeding scenarios. Specifically, the system synchronously reads the drainage volume change slope generated in step S210 and the shock index change slope generated in step S220, and determines whether they meet the logical condition that "the drainage volume change slope is greater than the first drainage volume slope threshold or the shock index change slope is greater than the first index slope threshold".

[0069] Specifically, the first drainage volume slope threshold can be set to 50 ml / hour squared (i.e., a net increase of 50 ml / hour in drainage volume), and the first exponential slope threshold can be set to 0.05 / hour. These thresholds are set based on clinical observation data and are used to identify abnormal trend combinations with statistical and clinical significance. This step achieves a leap from single-indicator monitoring to collaborative inference from multi-source time-series data, significantly improving the specificity and foresight of the early warning.

[0070] In addition, the pre-set joint criterion rule base is stored in the system database in the form of structured rule tables. Each rule record includes the threshold for the slope of drainage change, the threshold for the slope of shock index change, logical operators (such as "AND" or "OR"), the applicable diagnostic category (such as pelvic fracture), the warning level, and the associated treatment suggestion identifier. When performing joint risk assessment, the system matches the corresponding rule entry according to the patient's primary diagnosis, reads the threshold parameters, and substitutes the two slope values ​​calculated in real time into the rule for Boolean logic judgment to determine whether the occult bleeding warning conditions are met, ensuring that the criteria are configurable, traceable, and clinically applicable.

[0071] In step S240, in response to the judgment result being that the above conditions are met, the hidden bleeding warning information is highlighted on the risk warning area interface, and a level 2 warning is automatically triggered.

[0072] In step S240, the combined judgment results are transformed into clear clinical action guidelines. Once the system determines that the above combined conditions are met, it considers the patient to have a highly suspected risk of occult bleeding. At this time, the risk warning area interface highlights the prompt message "Suspected occult bleeding, please combine hemoglobin and vital signs for comprehensive assessment," and automatically triggers the secondary warning process. This trigger not only updates the warning level indicator but also links the aforementioned warning mechanism, including turning the window border orange, displaying the secondary warning text at the top, and popping up a floating layer containing structured treatment suggestions such as accelerating fluid resuscitation, urgently checking blood routine, and preparing for blood transfusion.

[0073] By directly mapping trend analysis results to standardized response pathways, this step effectively bridges the gap between data analysis and clinical decision-making, ensuring that high-risk signals can be rapidly translated into timely and standardized nursing and medical interventions, thereby reducing the incidence of adverse events caused by occult bleeding.

[0074] In some embodiments of this application, the main interface also includes multi-source data comparison controls and conflict resolution operation controls. Performing conflict resolution of multi-source vital sign data in the main interface specifically includes the following steps.

[0075] Step S310: Receive multi-source vital sign data from the monitor, wearable device, and manually entered data. When the difference in pulse values ​​from different sources exceeds the first pulse difference threshold, or the difference in systolic blood pressure exceeds the first blood pressure difference threshold, pause the alarm trigger and highlight the multi-source data comparison control on the interface.

[0076] In step S310, the system proactively identifies and intercepts potential misjudgments due to data conflicts. The system receives multi-source vital sign data in real time from monitors, wearable devices, and manually entered data by nurses. When the difference between pulse values ​​from different sources exceeds a first pulse difference threshold (e.g., 20 beats per minute) or the systolic blood pressure difference exceeds a first blood pressure difference threshold (e.g., 20 mmHg), a significant measurement discrepancy is identified. At this point, the system automatically pauses the triggering of the shock index warning logic to avoid generating erroneous alarms based on unreliable data. The system also highlights the multi-source data comparison control on the main interface to visually guide medical staff to focus on data consistency issues, ensuring that subsequent assessments are based on reliable data.

[0077] In step S320, in response to the trigger command of the multi-source data comparison control, a data conflict card window pops up, listing the timestamp, value and device type of each data source.

[0078] In step S320, when the user clicks the highlighted multi-source data comparison control, the system pops up a data conflict card window. This window clearly displays the specific information of each data source in a list format, including the timestamp of each record (accurate to the second), the measured pulse or systolic blood pressure value, and the corresponding device type (such as bedside monitor, wrist-worn wearable heart rate belt, nurse's manual record, etc.). By presenting the time and device information side by side, medical staff can intuitively determine whether the difference stems from asynchronous measurement time (such as the monitor reading being the current real-time value, while the wearable device is the average value from 5 minutes ago), differences in device accuracy (such as wearable devices being susceptible to motion artifacts when the patient is active), or human input errors, thus providing sufficient basis for subsequent decision-making. In step S330, in response to the trigger command of the conflict resolution operation control, the user is provided with the options of "using monitor data", "using wearable data" or "manual retesting". After the user selects, the shock index is recalculated with the selected data and the warning logic is resumed.

[0079] In step S330, a closed-loop process is implemented from conflict identification to manual intervention and then to system recovery. In the data conflict card window, the system provides conflict resolution operation controls, including three explicit options: using monitor data, using wearable data, or manual retesting. Monitors are generally considered the gold standard due to their direct connection and clinical calibration; wearable devices are suitable for continuous monitoring but may be affected by movement; manual retesting is used to obtain the latest reliable data when in doubt. After the user selects one based on the clinical context, the system immediately uses the pulse and systolic blood pressure values ​​from the selected data source as valid input, recalculates the shock index, and removes the previous warning pause, restoring the complete risk assessment and warning logic execution. This mechanism respects the efficiency advantages of automated systems while preserving the professional judgment of medical personnel in complex scenarios, effectively balancing the reliability of intelligent warnings with the flexibility of clinical practice, and preventing unnecessary alarm fatigue or missed alarm risks caused by data noise.

[0080] In some embodiments of this application, the risk warning area further includes etiology prompting controls and clinical evidence display controls. Performing shock precipitation prompts based on structured clinical rules in the risk warning area specifically includes the following steps.

[0081] Step S410: In response to triggering a level 2 or 3 alert, read the patient's current drainage volume, pain score, position record, and surgical type data.

[0082] In step S410, comprehensive and structured clinical context data is provided to support subsequent etiological analysis. When the system triggers a level 2 or 3 alert, it automatically retrieves the patient's current key clinical parameters in real time from the electronic medical record, nursing record, and surgical information system. These parameters include postoperative drainage volume, pain score, recent positional changes (such as whether the patient is sitting up or turning over), and specific surgical type (such as internal fixation of pelvic fracture or femoral neck replacement). These data together constitute the basic input for inferring the causes of shock, ensuring that subsequent analysis closely follows the patient's individual condition rather than relying on generalized judgments.

[0083] Optionally, the drainage volume comes from the "Hourly Drainage Volume" structured field in the nursing record module; the pain score uses a 0–10 numeric rating scale and is stored in integer form; the position record comes from the "Position Change" event in the nursing operation log (such as "Supine", "Semi-sitting", "Getting out of bed"); the surgery type is obtained by connecting to the electronic medical record system and mapped to the orthopedic specialty category (such as "Pelvic Ring Injury Surgery").

[0084] Step S420: In response to the trigger command of the cause prompt control, the preset orthopedic shock cause rule base is invoked. The rule base contains multiple if-then structured rules.

[0085] In step S420, a specialized knowledge base is activated to achieve intelligent attribution. When medical staff click the cause prompt control, the system calls the preset orthopedic shock cause rule base. This rule base is jointly constructed by clinical experts and information engineers and contains multiple structured rules organized in the form of if-then statements, such as "If the drainage volume increases by more than 200ml in the past 2 hours and the shock index rises, it may be progressive retroperitoneal hemorrhage" or "If the pain score is greater than or equal to 7.0, the systolic blood pressure is normal but the heart rate is increased, the increased heart rate may be caused by pain stress." Each rule is bound to a specific clinical scenario and postoperative pathological characteristics in orthopedics, ensuring that the reasoning process is professional and targeted, and avoiding the generation of vague or irrelevant interpretations.

[0086] Step S430: According to the matching rules, fill the corresponding variables from the preset natural language template to generate a natural language etiology explanation.

[0087] In step S430, the machine-readable rule matching results are converted into natural language expressions that are easy for medical staff to understand. Based on the matched rules, the system selects corresponding sentence structures from a pre-set natural language template library and dynamically fills in actual variable values. For example, it automatically generates and displays the statement "The patient's postoperative drainage volume increased by 230ml in the last 2 hours, and the shock index rose from 0.9 to 1.2, suggesting possible occult progressive bleeding" in the warning window. This mechanism not only improves the efficiency of information transmission but also enhances the credibility and clinical acceptance of the warning results, enabling nurses to quickly grasp the nature of the risk and take corresponding measures, rather than simply facing an abstract warning level.

[0088] In step S440, in response to the trigger command of the clinical evidence display control, the specific vital sign values ​​and rule numbers on which the judgment is based are listed in the sub-window.

[0089] In step S440, decision-making transparency and audit traceability are achieved. When the user clicks the clinical evidence display control, the system pops up a sub-window that lists in detail the specific vital sign values ​​(such as current pulse 110 beats per minute, systolic blood pressure 100 mmHg, shock index 1.1), drainage volume change trend, pain score and other raw data on which the warning judgment is based, and marks the triggered rule number (such as Rule_OB_07) and a brief description of the rule; this design allows medical staff to review the system's judgment logic and verify its rationality, while also providing structured data support for quality control, adverse event review and system rule optimization.

[0090] In some embodiments of this application, the main interface also includes a patient complaint entry control. Performing a comprehensive risk assessment based on the patient's subjective description within the main interface specifically includes the following steps.

[0091] In step S510, in response to the trigger command of the patient complaint entry control, a structured symptom selection window is displayed, providing preset symptom options related to shock, including at least "dizziness", "palpitation", "cold sweats", "thirst", "irritability" and "confusion".

[0092] In step S510, medical staff are guided to efficiently and systematically collect symptom information highly related to shock. When the user triggers the patient's chief complaint entry control, the system pops up a structured symptom selection window. This window is not an open text input window, but provides a set of clinically validated preset symptom options, including at least dizziness, palpitations, cold sweats, thirst, irritability, and confusion. These symptoms are common autonomic or central nervous system reactions in hypoperfusion states and have high early warning value in post-orthopedic patients. The structured design avoids the ambiguity of free description and improves data entry efficiency and standardization.

[0093] Step S520: Receive one or more symptom options selected by medical staff, record the symptom entry time, and generate structured chief complaint symptoms.

[0094] In step S520, the subjective complaint is transformed into calculable and traceable structured clinical data. The system receives one or more symptom options selected by medical staff and automatically records the precise timestamp of symptom entry, generating a structured complaint symptom record with semantic tags. This record not only includes the symptom content itself but also associates it with the patient's identity, the operator, and the contextual warning status, ensuring that subsequent analysis is traceable and auditable. By transforming unstructured verbal complaints into machine-readable discrete variables, a data foundation is laid for multimodal risk fusion judgment, enabling the system to identify the collaborative evidence chain between "patient's self-reported palpitations" and "monitoring shows increased heart rate."

[0095] Step S530: When at least one symptom is selected and the patient is currently in a shock warning logic activation state suitable for postoperative orthopedic patients, a chief complaint weighting factor is introduced into the comprehensive risk assessment.

[0096] In step S530, dynamic coupling between the chief complaint information and the early warning logic is achieved. When the system detects that at least one symptom is selected, and the shock early warning logic adapted to post-orthopedic patients is currently activated (i.e., the primary diagnosis contains orthopedic keywords), a chief complaint weighting factor is introduced into the comprehensive risk assessment engine. This factor, as an enhancement to the risk score, regulates the overall early warning threshold, for example, by lowering the triggering conditions or increasing the early warning level, thereby reflecting a higher risk weight under the dual evidence of "subjective discomfort + objective indicators." This mechanism effectively captures the early compensatory stage in some patients where the shock index has not yet significantly increased but significant discomfort has already occurred, improving the sensitivity of the early warning.

[0097] Step S540: When at least one symptom is selected and the patient is currently in a shock warning logic activation state suitable for postoperative orthopedic patients, a chief complaint weighting factor is introduced into the comprehensive risk assessment.

[0098] In step S540, a refined triggering rule based on the chief complaint-indicator combination is established to achieve earlier and more accurate clinical intervention prompts.

[0099] Specifically, if the shock index is ≥ 0.9 and any preset symptom is present (such as cold sweats or confusion), a Level 1 warning is triggered in advance, because such symptoms often indicate sympathetic excitation or insufficient brain perfusion and are highly specific.

[0100] On the other hand, if the shock index is ≥ 1.3 and any preset symptom is present (such as dizziness or palpitations), a secondary warning is triggered in advance, and the patient's selected complaint and its corresponding clinical significance are highlighted simultaneously (such as "cold sweats: indicating activation of the sympathetic system, commonly seen in the early stage of hypovolemia"). This composite criterion combining subjective experience and objective parameters significantly enhances the system's ability to identify hidden circulatory disorders, enabling the warning to move from "numerical-driven" to "symptom-physiological fusion-driven", truly aligning with the actual clinical decision-making logic.

[0101] In some embodiments of this application, reference is made to Figure 2 This application provides a schematic diagram of the main interface for shock index detection, used for real-time monitoring and intelligent early warning of shock risk in postoperative patients. The upper left of the main interface 100 is the patient information area, displaying name, bed number, hospital number, diagnosis, and admission date. It also includes a vital signs input box 101 for inputting pulse value and systolic blood pressure, from which the system automatically calculates the shock index (e.g., a current value of 1.1). Slightly to the right of center is the risk warning area 102, highlighted in green with the message "Current shock index 1.1, Level 1 warning: Mild shock," explaining that the trigger is a value exceeding the normal range of 0.5–1.0. Below this area are a cause-of-effect prompt control 103 and a clinical evidence display control 104, used to generate natural language explanations of the cause and display specific judgment data and rule numbers, respectively.

[0102] The right side of the interface features a vertically arranged set of functional controls: the drainage flow trend analysis control 105 is used to plot drainage flow over time and calculate the slope of change; the shock index change slope calculation control 106 is used to assess the rate of shock progression; the combined risk assessment control 107 can be used to identify the risk of occult bleeding; the multi-source data comparison control 108 highlights conflicts when data from different devices differ significantly; the conflict resolution operation control 109 provides data source selection or retesting options to update the calculation; and the patient complaint entry control 111 supports selecting structured symptoms such as dizziness, palpitations, and cold sweats, triggering early warnings based on the patient's complaint. The entire interface integrates clearly numbered functional modules, achieving full-process digital management from vital sign collection and multi-parameter fusion analysis to graded early warning, treatment recommendations, and operational closure, significantly improving the standardization and efficiency of early identification and intervention of postoperative shock in orthopedics.

[0103] In some embodiments of this application, the main interface also includes a pain correction suggestion window and a corrected heart rate reference control. Performing heart rate correction auxiliary decision-making under pain interference in the main interface aims to address the false-positive shock index problem caused by a reflexive increase in heart rate due to severe pain in post-operative orthopedic patients, and to improve the accuracy of risk assessment. Specifically, this includes the following steps.

[0104] In step S610, in response to detecting that the patient's pain score is ≥ the first pain score threshold and the systolic blood pressure is ≥ the second systolic blood pressure threshold, a pain correction suggestion window pops up, displaying the message "High pain may cause a false increase in heart rate. It is recommended to calculate the shock index after correction".

[0105] In step S610, the system actively identifies pain-interference scenarios and provides intelligent prompts. When the system detects that the patient's current pain score reaches or exceeds the first pain score threshold (e.g., a score of 7, representing severe pain) and the systolic blood pressure is still at a normal or slightly elevated level (i.e., not lower than the second systolic blood pressure threshold, such as 90 mmHg), it indicates that the patient's circulation is still stable, but the heart rate may be significantly increased due to pain stimulation. At this time, the system automatically pops up a pain correction suggestion window and displays a prompt text indicating that high pain may cause a false increase in heart rate, suggesting the calculation of the shock index after correction. This guides medical staff to carefully judge whether the increase in heart rate truly reflects insufficient blood volume, thereby avoiding the risk of misjudging the risk of shock due to pain stress.

[0106] Specifically, the first pain score threshold is 7 points (based on the commonly used 0–10 numerical rating scale), indicating severe pain; the second systolic blood pressure threshold is 90 mmHg, representing that the circulation is still in a compensated state. The clinical logic behind this combination of conditions is that when high pain is accompanied by normal blood pressure, the increased heart rate is more likely to be due to sympathetic excitation rather than low blood volume, thus triggering the correction recommendation.

[0107] In step S620, in response to the trigger command of the calibrated heart rate reference control, a historical heart rate reference window pops up, displaying the patient's lowest stable heart rate value in the past 24 hours, excluding periods of postural change.

[0108] In step S620, an individualized physiological baseline reference is provided for clinical decision-making. When the user clicks the heart rate reference calibration control, the system pops up a historical heart rate reference window. This window displays the patient's lowest stable heart rate value in the past 24 hours, excluding periods of disturbance such as changes in body position, nursing procedures, or drug interventions. This value is extracted by analyzing time-series data from vital sign monitoring records and automatically filtering unstable periods from nursing event logs. It represents the patient's baseline heart rate level in a relatively quiet state without acute stimulation. This reference value can effectively reflect the patient's true circulatory compensation status, and is especially suitable for elderly patients or patients with a slow baseline heart rate, providing an objective basis for distinguishing between painful tachycardia and hemorrhagic tachycardia.

[0109] Specifically, data on periods of positional change are obtained from structured operation logs in the nursing record system (such as events like "turning over," "sitting up," and "getting out of bed"), or detected by accelerometer signals from wearable devices. The system marks these time periods as unstable periods and automatically skips them when extracting historical heart rates. If no relevant data is available, the heart rate during quiet nighttime hours (such as 2 a.m. to 5 a.m.) is used as the alternative baseline by default.

[0110] Step S630: In the historical heart rate reference window, a checkbox for "Calculate shock index using correction value" is provided. In response to the user checking the checkbox, the shock index is recalculated and the warning result is updated by replacing the currently entered pulse value with the lowest stable heart rate.

[0111] In step S630, a closed-loop operation from information prompting to calculation and correction is implemented. In the historical heart rate reference window, the system provides a checkbox for calculating the shock index using the correction value. When the user selects this option based on clinical judgment, the system immediately replaces the currently manually entered or device-collected pulse value with the displayed lowest stable heart rate value, recalculates it using the shock index formula, and automatically executes the warning logic based on the updated shock index, refreshing the warning level, triggering basis, and treatment suggestions in the risk warning area. This mechanism empowers medical staff to reasonably correct input parameters in specific situations, preserving the efficiency of automated assessment while incorporating the flexibility of professional judgment, significantly improving the applicability and reliability of the shock index in complex postoperative scenarios.

[0112] Specifically, the minimum stable heart rate is not simply the lowest value within 24 hours, but must meet the condition of "stability". The system first filters out heart rate data points from all non-interference periods, then calculates the standard deviation within a sliding window (e.g., 30 minutes), retaining only continuous intervals with standard deviations less than a preset tolerance (e.g., ±5 beats / min), and selecting the window with the lowest average heart rate, using its mean or median as the final correction value. This process can be achieved through conventional time series analysis.

[0113] The correction calculation generates a new snapshot of shock assessment data, triggering a complete risk assessment process (including whether the orthopedic early warning logic is activated, whether the grading conditions are met, etc.), and marks "Corrected heart rate has been used" in the interface to distinguish it; the original and corrected results can be saved in parallel, supporting audit traceability.

[0114] In some embodiments of this application, the main interface also includes individual baseline setting controls and deviation alarm switch controls. Performing individualized shock index baseline modeling and abnormal deviation detection in the main interface specifically includes the following steps.

[0115] Step S710: In response to the completion of at least M valid vital sign records after the patient's admission, a prompt for setting individual baselines pops up, and the individualized shock index baseline μ and standard deviation σ are calculated using the sliding window moving average method.

[0116] In step S710, the triggering conditions and basic calculation process for individualized modeling are initiated. When the system detects that the patient has completed at least M effective vital sign recordings since admission (e.g., M is 5 times, typically covering a stable observation period of 6 to 24 hours after admission), it is considered that sufficient data has been accumulated to establish a reliable individual baseline. At this time, an individual baseline setting prompt automatically pops up and the individual baseline setting control is activated. The system then calls historical shock index data and uses a sliding window moving average method to smooth the original sequence to reduce transient interference (such as pain attacks or changes in body position). The sliding window length is the most recent K data points (e.g., K=3) or a fixed time span (e.g., 6 hours); the moving average is a simple arithmetic mean or a weighted average. Based on this, the patient's specific shock index baseline mean μ and its standard deviation σ are calculated as a dynamic reference system to measure whether the subsequent state is abnormal, thereby transforming the assessment benchmark from a population standard to an individual steady state.

[0117] In step S720, in response to the trigger command of the individual baseline setting control, the individual baseline parameter window is displayed, showing the values ​​of μ and σ and the data period used for calculation.

[0118] In step S720, when medical staff click the individual baseline setting control, the system pops up an individual baseline parameter window, clearly displaying the specific values ​​of the calculated baseline mean μ and standard deviation σ, and indicating the time period of the data used (e.g., from the 8th to the 24th hour after admission), the number of valid measurements included, and data quality indicators (e.g., whether outliers were removed). This design allows nurses to intuitively judge the reliability of the baseline. If the data period is during the peak of postoperative acute pain or the anesthesia recovery period, they can choose to postpone activation or manually reset the baseline, thereby ensuring that the individual model truly reflects the patient's physiological characteristics in a relatively stable state and avoiding the impact of early warning accuracy on the baseline shift caused by early interference data.

[0119] In step S730, in response to each subsequent completion of the shock index calculation, it is determined in real time whether the condition "shock index > μ + 2σ" is met. In step S730, real-time dynamic monitoring of the individual's physiological state is achieved. After each subsequent recording of the patient's pulse and systolic blood pressure and calculation of the new shock index, the system immediately executes deviation detection logic to determine whether the current shock index is greater than μ plus twice σ (i.e., μ + 2σ). This criterion is based on the rule of thumb in statistics. Under the assumption of normal distribution, approximately 95% of the data should fall within the μ ± 2σ range. Exceeding this range is considered a significant abnormality. Even if the absolute value of the current shock index does not reach the general warning threshold (e.g., it is still below 1.0), as long as it significantly deviates from the patient's own historical steady state, it is marked as a potential risk signal, thereby capturing those early circulatory instability states that "appear normal" under the group standard but have undergone significant compensatory changes for the individual.

[0120] Step S740: In response to the condition being met and the deviation alarm switch control being in the on state, the corresponding warning level is increased.

[0121] In step S740, individual deviation information is organically integrated into the overall risk decision-making system to achieve intelligent enhancement of the early warning level. When the system determines that the current shock index meets the condition of "shock index > μ + 2σ", and the user has actively enabled the deviation alarm switch control (which can be turned off by default and is enabled by medical staff according to the patient's condition), the original early warning level is adjusted up by one level. For example, a situation that originally only triggered a level one observation prompt may be upgraded to a level two warning due to significant individual deviation, and the prompt text, treatment suggestions, and visual labels in the risk warning area will be updated simultaneously. This mechanism not only respects clinical autonomy (by controlling the function activation through the switch control), but also constructs a multi-dimensional early warning model with both sensitivity and specificity by integrating individual trends and absolute thresholds, significantly improving the early identification ability and intervention accuracy of shock risk in postoperative patients with high heterogeneity in orthopedic trauma.

[0122] Secondly, refer to Figure 3This application provides an interactive system for detecting shock index in orthopedic trauma, which includes the following modules.

[0123] The main interface module is configured to display the main interface for shock index detection interaction, which includes a vital signs input box and a risk warning area.

[0124] The input processing module is configured to: receive the patient's pulse value and systolic blood pressure value input by the user in the vital signs input box, calculate the shock index, obtain the patient's primary diagnosis information, and generate shock assessment data; if the primary diagnosis information includes orthopedic keywords, then activate the shock warning logic adapted to post-orthopedic patients.

[0125] The risk warning module is configured to: perform a comprehensive risk assessment based on the shock assessment data and the shock warning logic, generate a level 1, level 2 or level 3 warning result, and display it in the risk warning area; and display the triggering basis, natural language etiology explanation, structured treatment suggestions and selectable operation record items corresponding to the warning result in the risk warning area.

[0126] Furthermore, this application provides an electronic device, characterized in that the electronic device includes a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the aforementioned interactive method for detecting shock index in orthopedic trauma.

[0127] Furthermore, embodiments of this application provide a computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the aforementioned interactive method for detecting shock index in orthopedic trauma.

[0128] In summary, the interactive method, system, device, and medium for detecting shock index in orthopedics provided in this application have the following technical effects.

[0129] This solution significantly improves the ability to identify and respond to occult bleeding and early shock by constructing a specialized, structured, and intelligent risk assessment mechanism. The system abandons traditional manual calculations and generic threshold models, automatically integrating multi-dimensional clinical parameters such as pulse, systolic blood pressure, primary diagnosis, pain score, drainage volume trends, and structured patient complaints to generate individualized shock assessment data. It activates appropriate early warning logic only after recognizing orthopedic keywords, ensuring accurate coverage of high-risk groups. Based on this, a three-tiered early warning model is adopted, combining visual identifiers, natural language etiological explanations, structured treatment suggestions, and mandatory operation controls to transform risk values ​​into understandable, executable, and traceable clinical actions, effectively bridging the gap between intelligent judgment and nursing practice.

[0130] Furthermore, the system integrates several enhanced functions to improve the sensitivity and reliability of early warnings: capturing dynamic signals of progressive bleeding through a temporal joint criterion of drainage volume and shock index; differentiating stress-induced tachycardia from true circulatory decompensation through pain correction mechanisms; identifying early abnormalities that significantly deviate from homeostasis through individual baseline modeling; ensuring the credibility of input data through multi-source vital sign conflict resolution; and triggering symptom-driven early warnings before the shock index reaches a threshold through structured patient complaint collection. All intervention operations can be automatically written to the electronic nursing log by checking records, achieving full-process digital management from risk identification and decision support to execution closed loop. Overall, this solution effectively solves the core defects of existing technologies, such as delayed early warnings, high false alarm rates, lack of interpretability, and operational disconnect, providing practical technical support and beneficial options for the safe management of postoperative orthopedic patients.

[0131] It should be noted that in all specific embodiments of this application, all data processing activities related to user identity or personal characteristics, such as user information, user behavior data, historical data, and location information, will be conducted in accordance with the principles of legality, legitimacy, and necessity. All data collection, use, storage, and processing will be subject to compliance with applicable national and regional laws, regulations, and industry standards, and informed consent from users will be obtained in a clear and explicit manner before processing. For the processing of sensitive personal information, separate consent from users will be obtained through prominent means such as pop-up prompts and independent confirmation pages. If any processing conflicts with laws and regulations, the laws and regulations will prevail, and necessary data processing will only be carried out within the scope permitted by laws and regulations, ensuring that all data-based applications, analyses, and technical implementations are conducted within the scope permitted by laws and regulations.

[0132] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this application are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0133] Furthermore, although this application is described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding this application. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of ordinary skill of an engineer. Therefore, those skilled in the art can implement the application set forth in the claims using ordinary skill. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of this application, which is determined by the full scope of the appended claims and their equivalents.

[0134] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several programs to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0135] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequential list of executable programs for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, a program execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can retrieve and execute a program from or in conjunction with such a program execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can mean any means that can contain, store, communicate, propagate, or transmit a program for use by or in conjunction with a program execution system, apparatus, or device.

[0136] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Additionally, computer-readable media can even be paper or other suitable media on which programs can be printed, for example, by optically scanning the paper or other media, then editing, interpreting, or, if necessary, processing it in a suitable manner to obtain the program electronically, and then storing it in computer memory.

[0137] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable program execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0138] In the foregoing description of this specification, the reference to terms such as "one embodiment / implementation," "another embodiment / implementation," or "certain embodiments / implementations," etc., indicates that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in an embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0139] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0140] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. An orthopedic shock index detection interaction method, characterized in that, Includes the following steps: The main interface for displaying the shock index detection interaction includes a vital signs input box and a risk warning area. In the vital signs input box, the system receives the patient's pulse value and systolic blood pressure value input by the user, calculates the shock index, obtains the patient's primary diagnosis information, and generates shock assessment data. If the main diagnostic information includes orthopedic keywords, then activate the shock warning logic adapted to postoperative orthopedic patients; Based on the shock assessment data and the shock early warning logic, a comprehensive risk determination is performed to generate a Level 1, Level 2, or Level 3 early warning result, which is displayed in the risk warning area. The risk warning area displays the triggering basis, natural language etiology explanation, structured handling suggestions, and selectable operation record items corresponding to the warning result.

2. The interactive method for detecting shock index in orthopedics according to claim 1, characterized in that, Based on the shock assessment data and the shock early warning logic, a comprehensive risk determination is performed. Specifically, the early warning level is dynamically generated according to the following multi-parameter criteria, and the interactive status of each level of early warning is displayed in the risk early warning area: Level 1 Warning: Triggered when 1.0 ≤ Shock Index < 1.

5. In the risk warning area, the current shock index value and the prompt text "Level 1 Warning: Mild Shock" are displayed in green, and a pop-up layer of treatment suggestions corresponding to the Level 1 warning automatically appears; the treatment suggestion pop-up layer is used to display a set of treatment suggestions. Level 2 warning: Triggered when 1.5≤shock index<2.0 or when the time-series joint criterion based on the trend of postoperative drainage volume change and the trend of shock index change is met. In the risk warning area, the current shock index value and the prompt text "Level 2 warning: moderate shock" are highlighted in yellow, and the corresponding treatment suggestion pop-up layer will automatically pop up. Level 3 warning: Triggered when the shock index is ≥2.0, the systolic blood pressure is lower than the first systolic blood pressure threshold, or the pulse exceeds the first pulse threshold. In the risk warning area, the current shock index value and the prompt text "Level 3 warning: severe shock" are highlighted in red. At the same time, an audio-visual reminder is triggered, and a pop-up layer of treatment suggestions corresponding to the Level 3 warning and a notification confirmation window from the on-duty physician automatically appear.

3. The interactive method for detecting shock index in orthopedics according to claim 2, characterized in that, The action suggestion overlay includes an operation log control; the generation process of the action suggestion overlays corresponding to Level 1, Level 2, and Level 3 warnings includes the following steps: In response to the determination of the warning level, the corresponding set of treatment suggestions is matched from the preset orthopedic shock treatment rule base, and the set of treatment suggestions is displayed in the form of a list in the treatment suggestion floating layer; in: The recommended treatment for a Level 1 warning includes "oxygen administration via tubing" and "replenishing with sufficient isotonic saline or balanced electrolyte solution"; The recommended treatment for a Level II alert includes "administer oxygen via face mask", "monitor cardiac function", "measure vital signs every 15-30 minutes", "establish two intravenous access lines to rapidly expand blood volume", "draw blood for further examination and prepare for blood transfusion", and "insert urinary catheter". The recommended procedures for Level 3 alerts include: "Administer oxygen via face mask," "monitor cardiac function," "measure vital signs every 15 minutes," "notify the ICU for assistance," "clean the ward and create a suitable environment for resuscitation," "notify family members to come to the ward," "establish two or more intravenous access lines to rapidly expand blood volume," "draw blood and notify the blood transfusion department for emergency blood matching," and "prepare oxygen bags, portable cardiac monitors, and make preparations for transport." In response to a trigger command on the operation record control, a selectable list of completed operations is provided, and the selected records are saved to the patient's electronic nursing log for closed-loop tracking and quality control analysis.

4. The interactive method for detecting shock index in orthopedics according to claim 2, characterized in that, The main interface includes a traffic flow trend analysis control, a shock index change slope calculation control, and a joint risk assessment control. The timing joint criterion is executed in the main interface to identify the risk of occult bleeding, specifically including the following steps: In response to the trigger command of the drainage flow trend analysis control, a drainage flow time series chart window is displayed, the drainage flow data of the patient at the most recent N consecutive time points after surgery are loaded, and the slope of drainage flow change is generated by linear regression fitting; In response to the trigger command of the shock index change slope calculation control, the shock index trend comparison window is displayed, the difference between the current shock index and the previous measurement value is calculated and divided by the time interval between the two measurements to generate the shock index change slope. In response to the trigger command of the joint risk judgment control, a preset joint criterion rule library is invoked to determine whether the condition of "the slope of the traffic flow change > the first traffic flow slope threshold or the slope of the shock index change > the first index slope threshold" is met; If the judgment result meets the above conditions, a level-two warning will be automatically triggered in the risk warning area.

5. The interactive method for detecting shock index in orthopedics according to claim 1, characterized in that, The main interface also includes multi-source data comparison controls and conflict resolution operation controls; The conflict resolution of multi-source vital sign data is performed in the main interface, specifically including the following steps: It receives multi-source vital sign data from monitors, wearable devices, and manually entered data. When the difference in pulse values ​​from different sources exceeds the first pulse difference threshold, or the difference in systolic blood pressure exceeds the first blood pressure difference threshold, it pauses the alarm triggering and highlights the multi-source data comparison control on the interface. In response to the trigger command of the multi-source data comparison control, a data conflict card window pops up, listing the timestamp, value and device type of each data source; In response to the trigger command of the conflict resolution operation control, the system provides the options of "using monitor data", "using wearable data" or "manual retesting". After the user selects the option, the shock index is recalculated with the selected data and the warning logic is resumed.

6. The interactive method for detecting shock index in orthopedics according to claim 1, characterized in that, The risk warning area also includes etiology prompt controls and clinical evidence display controls; Implementing shock precipitation based on structured clinical rules in the risk warning area specifically includes the following steps: In response to triggering a level 2 or 3 alert, the system reads the patient's current drainage volume, pain score, body position record, and surgical type data. In response to the trigger command of the etiology prompt control, a preset orthopedic shock induced rule base is invoked, which contains multiple if-then structured rules; According to the matching rules, corresponding variables are filled from the preset natural language template to generate the natural language etiology explanation; In response to the trigger command of the clinical evidence display control, the specific vital sign values ​​and rule numbers on which the judgment is based are listed in the sub-window.

7. The interactive method for detecting shock index in orthopedics according to claim 1, characterized in that, The main interface also includes a patient complaint entry control; Performing a comprehensive risk assessment that incorporates the patient's subjective description on the main interface includes the following steps: In response to a trigger command on the patient's complaint entry control, a structured symptom selection window is displayed, providing options for preset symptoms related to shock, including at least "dizziness", "palpitations", "cold sweats", "thirst", "irritability" and "confusion". It receives one or more symptom options selected by medical staff, records the symptom entry time, and generates structured chief complaint symptoms; When at least one of the chief complaints is selected and the patient is currently in a shock warning logic that is suitable for postoperative orthopedic patients, a chief complaint weighting factor is introduced into the comprehensive risk assessment. If the shock index is ≥ 0.9 and any of the preset symptoms are present, a Level 1 warning will be triggered in advance; if the shock index is ≥ 1.3 and any of the preset symptoms are present, a Level 2 warning will be triggered in advance, and the patient's chief complaint and corresponding clinical significance will be highlighted in the risk warning area.

8. An interactive system for detecting shock index in orthopedic trauma, characterized in that, include: The main interface module is configured to display the main interface for shock index detection interaction, the main interface including a vital signs input box and a risk warning area; The input processing module is configured to: receive the patient's pulse value and systolic blood pressure value input by the user in the vital signs input box, calculate the shock index, obtain the patient's primary diagnosis information, and generate shock assessment data; if the primary diagnosis information includes orthopedic keywords, then activate shock early warning logic adapted to orthopedic postoperative patients. The risk warning module is configured to: perform a comprehensive risk assessment based on the shock assessment data and the shock warning logic, generate a level 1, level 2 or level 3 warning result, and display it in the risk warning area; The risk warning area displays the triggering basis, natural language etiology explanation, structured handling suggestions, and selectable operation record items corresponding to the warning result.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the interactive method for detecting shock index in orthopedics as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the interactive method for detecting shock index in orthopedics as described in any one of claims 1 to 7.

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