Nutrition management and metabolism monitoring system for pancreatitis patients

Abstract

The invention belongs to the technical field of medical monitoring and nutrition support, and particularly discloses a nutrition management and metabolism monitoring system for pancreatitis patients. The system comprises a multi-data monitoring subsystem, a data integration center, an intelligent analysis module, a nutrition scheme adjustment module and a multi-terminal interaction platform, indexes such as inflammation, metabolism and intestinal functions are collected in real time, and tolerance scores and complication risk probabilities are calculated through integration analysis; an enteral nutrition control instruction (opportunity, rate and formula) is generated and a nutrition pump is linked to execute, so that a'monitoring-analysis-adjustment-feedback 'closed loop is formed. According to the invention, empirical management can be replaced, precise management of enteral nutrition of patients with pancreatitis is realized, the risk of complications is reduced, and the safety and efficiency of nutrition support are improved.

Description

Technical Field

[0001] This invention belongs to the field of medical monitoring and nutritional support technology, specifically relating to a nutritional management and metabolic monitoring system for patients with pancreatitis. Background Technology

[0002] In the clinical treatment of acute pancreatitis, enteral nutrition support is considered a core component. However, current clinical practice still heavily relies on the experience and judgment of healthcare professionals, and suffers from various technical limitations.

[0003] First, there is a lack of objective and precise criteria for determining the timing of enteral nutrition initiation. Initiating it too early may stimulate pancreatic juice secretion, exacerbating pancreatic autodigestion and inflammatory responses; while initiating it too late can easily lead to impaired intestinal mucosal barrier function, increasing the risk of intestinal flora translocation and secondary infections. Second, existing monitoring methods cannot provide continuous and systematic metabolic feedback. Conventional testing methods (such as daily serum amylase testing and intermittent blood glucose monitoring) can only obtain physiological indicators at isolated time points, making it difficult to dynamically reflect the patient's overall metabolic status and nutritional tolerance. Although technologies such as continuous glucose monitoring have been applied clinically, their function is limited and they cannot be correlated with pancreatitis-specific indicators (such as lipase and triglycerides), thus limiting their value in individualized nutritional support regulation. Furthermore, there is a significant lag in adjusting nutritional infusion protocols. The commonly used fixed incremental patterns (such as increasing by 20 ml / h every 12 hours) do not fully consider individual differences in patient disease severity, metabolic characteristics, and real-time tolerance, easily leading to feeding intolerance phenomena such as abdominal distension and vomiting in some patients, or conversely, causing insufficient nutritional supply, affecting treatment efficacy and prognosis. Summary of the Invention

[0004] The nutritional management and metabolic monitoring system for pancreatitis patients proposed in this invention can monitor metabolic data in real time, analyze and dynamically adjust nutritional plans, forming a closed-loop mechanism of monitoring-analysis-adjustment, thereby improving management efficiency.

[0005] To achieve the above technical objectives, this invention proposes a nutritional management and metabolic monitoring system for pancreatitis patients, which mainly includes: a multi-data monitoring subsystem, a data integration center, an intelligent analysis module, a nutrition plan adjustment module, and a multi-terminal interactive platform.

[0006] The multi-data monitoring subsystem includes an inflammation monitoring module, a metabolic monitoring module, an intestinal monitoring module, and a nutritional monitoring module. The inflammation monitoring module can detect serum amylase, lipase, CRP, and white blood cell count; the metabolic monitoring module can collect blood glucose in real time and detect triglycerides and lactic acid; the intestinal function monitoring module can detect gastric residual volume (GRV) and intestinal mucosal barrier indicators, and simultaneously collect an abdominal distension score, ranging from 1 to 10, with a score ≥4 indicating intolerance; the nutritional monitoring module can detect muscle mass, albumin, and prealbumin. Each module connects to the detection device via Bluetooth or a wired interface to achieve automatic data upload.

[0007] The data integration center is connected to multiple data monitoring subsystems to receive and process monitoring data, and is also connected to the hospital's electronic medical record (EMR) system to receive and store patients' basic information, vital signs, and monitoring indicators.

[0008] The intelligent analysis module is connected to the data integration center and can assess enteral nutrition tolerance and predict the risk of complications based on data. Specifically, after inputting the monitoring indicators and historical data from the data integration center, a tolerance assessment model is established and analyzed: the indicators of inflammation (weight 30%), metabolism (25%), intestinal function (35%), and infusion status (10%) are quantified into a score of 0-10 and weighted to obtain a "real-time tolerance score"; and a risk prediction model is also established: the current score and infusion parameters are input, and the probability of pancreatitis exacerbation (such as blood amylase rebound) and intolerance (such as vomiting) within 48 hours is output; finally, the score and risk sub-results are pushed to the nutrition plan adjustment module in real time.

[0009] The nutrition program adjustment module is connected to the intelligent analysis module, which can generate enteral nutrition control instructions based on the analysis results, directly link with external infusion equipment to achieve automatic adjustment, and output the program to the medical staff.

[0010] The multi-terminal interactive platform works in conjunction with medical staff and patients to enable human-computer interaction, ensure that control commands are implemented, and collect feedback data in a closed loop to the system.

[0011] This invention also provides an enteral nutrition management method based on the above-mentioned nutritional management and metabolic monitoring system for pancreatitis patients, the steps of which are as follows:

[0012] Step 1: System initialization and configuration: Enter patient information, such as pancreatitis type, weight and comorbidities, and bind the patient's dedicated enteral nutrition pump in the system; preset basic thresholds, such as peak serum amylase and target nutritional achievement values, and synchronize initial examination data from EMR.

[0013] Step 2: Real-time monitoring and data upload: The multi-data monitoring subsystem collects indicators and simultaneously obtains the current rate of the enteral nutrition pump in real time, and pushes the data to the data integration center.

[0014] Step 3: Data Integration and Analysis: The data integration center integrates the various data indicators collected by the multiple data monitoring subsystems and pushes them to the intelligent analysis module for analysis to obtain the tolerance score and risk probability (e.g., 7 points, risk probability 25%), and outputs them to the nutrition plan adjustment module.

[0015] Step 4: Enteral nutrition protocol generation and equipment linkage: The intelligent analysis module generates instructions based on the analysis results, such as "Tolerance score 7 points → Maintain the current rate of 30ml / h and continue monitoring", and then sends the instructions to the enteral nutrition pump and pushes them to the medical staff for confirmation.

[0016] Step 5: Execution Feedback: After confirmation by the medical staff, the enteral nutrition pump adjusts its execution rate and sends a success signal back to the system in real time.

[0017] The beneficial effects of this invention are:

[0018] 1. This invention collects and automatically uploads multi-dimensional indicators of inflammation (such as blood amylase), metabolism (such as blood glucose), and intestinal function (such as GRV) through a multi-data monitoring subsystem. The intelligent analysis module calculates a weighted real-time tolerance score to form an objective standard for determining the timing of initiation, effectively avoiding the risks of stimulating pancreatic juice secretion due to premature initiation and causing intestinal flora translocation due to delayed initiation. At the same time, the risk prediction model outputs the probability of complications within 48 hours, providing early warning of pancreatitis aggravation or feeding intolerance problems.

[0019] 2. The nutrition program adjustment module of this invention generates personalized control instructions (starting time, rate, formula) based on real-time tolerance scores and risk probabilities, and directly links the nutrition pump to automatically perform adjustments, replacing the manual fixed mode; it dynamically optimizes the infusion rate and formula for different types of pancreatitis, complications (such as hyperglycemia) and real-time feedback, significantly reducing intolerance phenomena such as abdominal distension and vomiting, and improving the accuracy of nutrition supply.

[0020] 3. This invention forms a complete closed loop of "multi-dimensional monitoring → data integration → intelligent analysis → scheme adjustment → equipment execution → feedback transmission". The multi-terminal interactive platform links medical staff and patients, reducing human operation errors; patient symptom feedback and equipment execution status are transmitted back to the system in real time, providing data support for subsequent analysis and continuously optimizing model parameters. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments are briefly introduced below.

[0022] Figure 1 This is a schematic diagram of the enteral nutrition management method according to Embodiment 1 of the present invention. Detailed Implementation

[0023] Example 1

[0024] This embodiment provides a specific method for enteral nutrition management using a nutritional management and metabolic monitoring system for pancreatitis patients, and details the execution steps of the enteral nutrition management process.

[0025] Step 1: System Initialization and Associated Configuration

[0026] Healthcare professionals use the doctor's end of a multi-terminal interactive platform to input the patient's pancreatitis type, weight range, and comorbidities. Within the system, a unique "patient-device" correspondence is established by binding the patient's enteral nutrition pump to the device identifier, ensuring accurate matching of subsequent instructions. The system's functional modules preset clinically common basic thresholds, primarily including the reference range for peak serum amylase levels, the target nutrient infusion rate, and the tolerance threshold for abdominal distension scores. The data integration center automatically connects to the hospital's electronic medical record (EMR) system, synchronizing the patient's initial examination data (basic inflammation and metabolic indicators) and basic vital sign information, storing it in a standardized format in the system database.

[0027] Step 2: Implement monitoring and data upload

[0028] Each module of the multi-data monitoring subsystem initiates indicator collection at the routine clinical frequency. All data is automatically uploaded via wireless or wired interfaces. The specific process is as follows:

[0029] Inflammation marker collection: The inflammation monitoring module is equipped with a dry biochemical analysis device to collect blood amylase, lipase, CRP and white blood cell count at the frequency corresponding to the disease grade. After the data collection is completed, it is uploaded to the data integration center in real time.

[0030] Metabolic indicator collection: The metabolic monitoring module is connected to a continuous glucose monitoring device to collect blood glucose data in real time; triglycerides and lactic acid are collected at fixed times every day through a blood lipid testing device, and all metabolic data are uploaded synchronously.

[0031] Intestinal function data collection: The intestinal monitoring module collects gastric residual volume (GRV) at set intervals through a gastric residual volume detection sensor; medical staff enter abdominal distension scores (1-10 points) through the nurse terminal of the multi-terminal interactive platform, and intestinal mucosal barrier-related indicators are collected simultaneously, and the data is automatically uploaded.

[0032] Nutritional status data collection: The nutrition monitoring module collects muscle mass periodically through bedside ultrasound equipment and obtains albumin and prealbumin through biochemical testing at fixed intervals; at the same time, it reads the operating status of the enteral nutrition pump in real time (current rate, remaining formula amount, whether the equipment is normal), and all data are uniformly pushed to the data integration center.

[0033] Step 3: Data Integration and Analysis

[0034] Data preprocessing: After receiving the data uploaded by each module, the data integration center automatically removes outliers caused by equipment errors, and sorts the processed data into standardized analysis datasets by category: "inflammation-metabolism-intestinal function-nutritional status-infusion status". The datasets are then pushed to the intelligent analysis module.

[0035] The intelligent analysis module calls a preset model to perform analysis: Tolerance assessment: Each indicator is quantified and scored according to weighted rules (inflammation 30%, metabolism 25%, intestinal function 35%, infusion status 10%), and a weighted calculation is performed to obtain a real-time tolerance score (0-10 points); Risk prediction: Input the real-time tolerance score and current infusion parameters, and the risk prediction model outputs the probability of pancreatitis aggravation and feeding intolerance within 48 hours; Result output: The analysis results of "tolerance score + risk probability" are pushed to the nutrition plan adjustment module in real time.

[0036] Step 4: Generate enteral nutrition protocol and integrate it with equipment

[0037] Protocol Instruction Generation: The nutrition protocol adjustment module generates enteral nutrition control instructions based on intelligent analysis results and combined with general clinical rules: When the conditions of "inflammatory markers decreasing to the target level + abdominal pain score being qualified + no intestinal obstruction" are met, an "Initiate Enteral Nutrition" instruction is generated; based on tolerance scores and risk probabilities, instructions to "Maintain Current Rate", "Increase Rate", or "Decrease / Pause Rate" are generated; combined with metabolic indicators (such as blood glucose and triglyceride levels), corresponding formula type recommendation instructions (regular, low-fat, low-sugar, etc.) are generated; Instruction Push and Execution: The system synchronously pushes control instructions to the medical staff; after the doctor confirms the instruction, the nurse triggers the instruction to be sent to the bound enteral nutrition pump, automatically executing the infusion parameter adjustment.

[0038] Step 5: Execute feedback and closed loop

[0039] Equipment Status Feedback: After the enteral nutrition pump executes the command, it sends its operating status back to the system in real time. The status data is simultaneously displayed on the doctor's and nurse's terminals, ensuring that medical staff can monitor the execution status in real time. Feedback Data Closed Loop: Medical staff monitor patients' clinical responses (such as abdominal distension, vomiting, etc.), and patients submit symptom scores through their terminals. All feedback data is transmitted back to the data integration center via a multi-terminal interactive platform, serving as input data for the next round of monitoring and analysis, forming a complete closed loop of "monitoring-analysis-planning-execution-feedback".

[0040] The nutritional management and metabolic monitoring system for pancreatitis patients based on the above steps mainly includes:

[0041] Multi-data monitoring subsystem: includes four major monitoring modules: inflammation, metabolism, gut, and nutrition, which automatically collect and upload multi-dimensional indicators;

[0042] Data Integration Center: Processes monitoring data, connects to EMR to store patient information, and provides standardized data for analysis;

[0043] Intelligent analysis module: Outputs objective analysis results through tolerance assessment model (calculates tolerance score) and risk prediction model (assesses the probability of complications);

[0044] Nutrition program adjustment module: Generates enteral nutrition control instructions based on analysis results, and links the nutrition pump to achieve automatic adjustment;

[0045] Multi-terminal interaction platform: Links medical staff and patients to realize instruction confirmation and execution feedback, ensuring a closed-loop process.

[0046] This system, through data linkage between modules, replaces traditional experience-based management, achieving precise closed-loop management of enteral nutrition for pancreatitis patients through "monitoring-analysis-adjustment-feedback," reducing the risk of complications and improving the safety and efficiency of nutritional support. For those skilled in the art, various modifications and variations can be made to the above embodiments without departing from the principles of this invention, and all such modifications and variations should fall within the protection scope of this invention.

Claims

1. A nutritional management and metabolic monitoring system for patients with pancreatitis, characterized in that, include: A multi-data monitoring subsystem, comprising an inflammation monitoring module, a metabolic monitoring module, an intestinal monitoring module, and a nutrition monitoring module, wherein each module is connected to the detection equipment to achieve automatic data uploading; The data integration center is connected to the multi-data monitoring subsystem and is used to receive and process the monitoring data uploaded by the multi-data monitoring subsystem. The data integration center is also connected to the hospital electronic medical record system (EMR) to receive and store patient basic information, vital signs and monitoring indicators. The intelligent analysis module is connected to the data integration center and is used to assess enteral nutrition tolerance and predict the risk of complications based on the monitoring data and historical data processed by the data integration center. The nutrition plan adjustment module is connected to the intelligent analysis module and is used to generate enteral nutrition control instructions based on the tolerance assessment results and complication risk prediction results of the intelligent analysis module, so as to link the external infusion equipment to achieve automatic adjustment, and at the same time output the nutrition plan to the medical staff. A multi-terminal interactive platform is used to link with medical staff and patients to achieve human-computer interaction to ensure that the enteral nutrition control instructions are implemented, while collecting feedback data and closing the loop to the system.

2. The system according to claim 1, characterized in that, The inflammation monitoring module is configured to detect blood amylase, lipase, CRP, and white blood cell count; the metabolic monitoring module is configured to collect blood glucose in real time and detect triglycerides and lactic acid; the intestinal monitoring module is configured to detect gastric residual volume (GRV) and intestinal mucosal barrier indicators, and simultaneously collect abdominal distension scores, which are based on a 1-10 scale, with a score ≥4 indicating feeding intolerance; the nutritional monitoring module is configured to detect muscle mass, albumin, and prealbumin.

3. The system according to claim 1, characterized in that, The intelligent analysis module includes a tolerance assessment model and a risk prediction model. The tolerance assessment model is configured to quantify inflammatory indicators, metabolic indicators, intestinal function indicators, and infusion status indicators into scores of 0-10, and calculate a real-time tolerance score by weighting the scores according to the following weights: 30% for inflammatory indicators, 25% for metabolic indicators, 35% for intestinal function indicators, and 10% for infusion status indicators. The risk prediction model is configured to output the probability of pancreatitis exacerbation and feeding intolerance within 48 hours based on the current real-time tolerance score and infusion parameters.

4. The system according to claim 1, characterized in that, The enteral nutrition control instructions generated by the nutrition protocol adjustment module include instructions for initiating enteral nutrition, instructions for adjusting the infusion rate, and instructions for recommending a formula.

5. The system according to claim 4, characterized in that, The generation logic of the infusion rate adjustment command is as follows: based on the real-time tolerance score and complication risk probability output by the intelligent analysis module, the infusion rate of the external infusion device is dynamically adjusted.

6. The enteral nutrition management method of the nutritional management and metabolic monitoring system for pancreatitis patients according to any one of claims 1-5, characterized in that, Includes the following steps: S1: System initialization and association configuration: Enter patient information, including pancreatitis type, weight and comorbidities, and bind the patient's dedicated enteral nutrition pump to the system; A preset basic threshold is set, which includes the peak value of serum amylase and the target nutritional achievement value, and the initial examination data is synchronized from the hospital's electronic medical record system (EMR); S2: Real-time monitoring and data upload: The multi-data monitoring subsystem collects various indicators, and simultaneously obtains the current rate of the enteral nutrition pump in real time, and pushes the collected indicator data and the current rate to the data integration center; S3: Data Integration and Analysis: After processing the received data, the data integration center pushes it to the intelligent analysis module; The intelligent analysis module calculates a real-time tolerance score based on the received data and predicts the probability of complication risk. S4: Enteral nutrition protocol generation and equipment linkage: Based on the real-time tolerance score and the probability of complication risk, the nutrition protocol adjustment module generates enteral nutrition control instructions, sends the rate instructions in the enteral nutrition control instructions to the enteral nutrition pump, and pushes the enteral nutrition control instructions to the medical staff for confirmation. S5: Execution Feedback: After the medical staff confirms the enteral nutrition control command, the enteral nutrition pump execution rate is adjusted; the medical staff enters the patient feedback information, and the patient feedback information is sent back to the data integration center to form a closed loop.

7. The enteral nutrition management method according to claim 6, characterized in that, The various indicators collected by the multi-data monitoring subsystem in S2 include inflammatory indicators, metabolic indicators, intestinal function indicators, and nutritional status indicators. Specifically, inflammatory indicators are collected by the inflammation monitoring module, metabolic indicators are collected by the metabolic monitoring module, intestinal function indicators are collected by the intestinal monitoring module, and nutritional status indicators are collected by the nutritional monitoring module.

8. The enteral nutrition management method according to claim 6, characterized in that, The enteral nutrition control instructions in S4 are generated based on the real-time tolerance score output by the intelligent analysis module and the risk probability of pancreatitis aggravation and feeding intolerance within 48 hours. After the enteral nutrition control instructions are pushed to the medical staff, the medical staff can confirm or adjust the enteral nutrition control instructions.

Images