Rehabilitation management system and method based on dental root canal therapy

Abstract

The invention relates to the technical field of rehabilitation management, and discloses a dental root canal therapy-based rehabilitation management system and method.The system comprises a rehabilitation tracking module, a data analysis module and a data display module.The rehabilitation tracking module collects postoperative state data containing pain, swelling and occlusion according to a specified frequency; if pain is quantified through visual simulation scores, swelling and occlusion scores are calculated according to measured values, and traditional rough subjective judgment is avoided; a rehabilitation index is calculated through a rigorous formula in combination with a preset weight, rehabilitation levels are subdivided, and doctors and patients are helped to clearly know the recovery process; the data analysis module can be used for linearly fitting pain and swelling data, accurately judging a trend according to a slope, generating an early warning in time when a threshold value is exceeded, and preventing risks in advance; and calculating an occlusion score mean value, judging the recovery quality according to the range, and focusing the occlusion problem. Efficient information transmission is achieved, a data display module quickly feeds back results, doctors can conveniently master dynamic states, and rehabilitation decisions are optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of rehabilitation management, and in particular to a rehabilitation management system and method based on dental root canal treatment. Background Art

[0002] Dental root canal therapy is a common and effective treatment for endodontic and periapical diseases and is widely used in the field of oral medicine. However, the patient's recovery process after root canal therapy is complex and variable, affected by multiple factors. Traditional postoperative management methods are no longer able to meet the needs of precision medicine.

[0003] As the quality of dental care improves, patients are increasingly interested in postoperative rehabilitation and expect more scientific and detailed rehabilitation guidance. At the same time, dental institutions are facing pressure from increasing patient numbers and limited medical resources. They urgently need efficient rehabilitation management tools to assist doctors, helping them promptly identify potential recovery risks, optimize treatment processes, and rationally allocate medical resources.

[0004] Against the backdrop of the current rapid development of digital medicine, the deep integration of information technology and medical practice has become a trend. However, the information management system for post-root canal treatment rehabilitation in the dental field still has many gaps and deficiencies. In the information integration and feedback process, due to the lack of an efficient management system, the data is scattered and incoherent, making it difficult for doctors to quickly and comprehensively grasp the patient's overall recovery from the immediate postoperative period to all subsequent stages. The need to re-sort the patient's scattered recovery information at each follow-up visit is time-consuming and labor-intensive, affecting the efficiency of diagnosis and treatment. It is also not conducive to the comprehensive treatment of complex cases by multidisciplinary collaboration, and it is unable to provide accurate and powerful data support for subsequent rehabilitation treatment, making it difficult to achieve personalized and dynamic rehabilitation guidance.

[0005] Based on the above problems, the present invention proposes a rehabilitation management system and method based on dental root canal treatment, aiming to fill this technical gap and improve the level of rehabilitation management after root canal treatment. Summary of the Invention

[0006] The purpose of the present invention is to provide a rehabilitation management system and method based on dental root canal treatment, which solves the technical problems raised in the background technology.

[0007] The purpose of the present invention can be achieved through the following technical solutions: A rehabilitation management system based on dental root canal treatment, comprising: A rehabilitation tracking module is used to collect postoperative status data of target patients at a specified collection frequency; The data analysis module is used to perform rehabilitation analysis based on the postoperative status data of the target patient, determine the patient's rehabilitation index based on the rehabilitation analysis, and then classify the patient's rehabilitation status into different rehabilitation levels based on the patient's rehabilitation index; The data display module is used to feed back the results obtained by the data analysis module to the doctor; As a further solution of the present invention: the postoperative status data includes: The visual analog scale was used to obtain the patient's pain assessment score at each collection time point and marked as SP t , t=1, 2, …, e, e represents the number of acquisition time nodes; The swelling was assessed by measuring the maximum diameter of the soft tissue swelling around the patient's teeth, and the patient's swelling assessment score at each sampling time point was obtained and marked as SZ. t ; By having the patient bite the test piece, the bite assessment is performed according to the indentation depth of the test piece, and the patient's bite assessment score at each acquisition time point is obtained and marked as SB t .

[0008] As a further embodiment of the present invention, the swelling assessment score is calculated by the following formula: ; Where z is the maximum diameter of the soft tissue swelling around the patient's teeth actually measured, and zy is the pre-set swelling diameter threshold.

[0009] As a further aspect of the present invention, the occlusal assessment score is calculated using the following formula: ; Where h is the actual indentation depth of the patient's bite force test piece, and hy is the preset indentation depth threshold.

[0010] As a further solution of the present invention: the rehabilitation analysis method is as follows: pass: ; Calculate the patient's recovery index E; Where β1, β2, and β3 are the preset weight coefficients corresponding to pain, swelling, and occlusal function, respectively; When E≤0.8×Ey, the patient’s recovery status is classified as good recovery level; When 0.8×Ey<E≤Ey, the patient’s recovery status is classified as moderate recovery level; When E>Ey, the patient's recovery condition is divided into poor recovery level.

[0011] As a further solution of the present invention: the data analysis module is further used to perform pain trend analysis based on the postoperative status data of the target patient, in the form of pain assessment scores SP at multiple acquisition time nodes. tPerform linear fitting, and the equation of the fitting line is y=a1x+b1, where a1 is the slope and b1 is the intercept. Then, the pain trend is determined by analyzing the a1 value.

[0012] As a further solution of the present invention: the pain trend is determined as follows: Step A1.1: Obtain pain assessment scores SP at multiple acquisition time points t The corresponding time value is marked as T t ; Step A1.2, by: ; Calculate the average value SP0 of pain assessment scores at multiple collection time points; Also through: ; Calculate the pain assessment score SP at multiple collection time points t The average value of the corresponding time value T0; Step A1.3, by: ; Calculate a1 in the fitting straight line equation y=a1x+b1; Step A1.4: If a1 > 0, it indicates that the pain is on an upward trend, that is, the pain intensity gradually increases over time; the larger a1 is, the more obvious the upward trend is; When a1>ay1, risk warning signal 1 is generated; If a1<0, it means that the pain is on a downward trend, which means that the pain gradually decreases over time. The larger |a1| is, the more significant the downward trend is. If a1=0, the pain trend is relatively stable, and the pain intensity has no obvious trend of changing over time.

[0013] As a further solution of the present invention: the data analysis module is further used to perform swelling trend analysis based on the postoperative status data of the target patient, in the form of swelling assessment scores SZ at multiple acquisition time nodes t Perform linear fitting, and the equation of the fitted line is y=a2x+b2, where a2 is the slope and b2 is the intercept. Then, the swelling trend is determined by analyzing the a2 value; As a further solution of the present invention: the swelling trend is determined as follows: Step A2.1: Obtain swelling assessment scores SZ at multiple acquisition time points t The corresponding time value is marked as R t ; Step A2.2, by: ; Calculate the average SP0 of the swelling assessment scores at multiple collection time points; Also through: ; Calculate the swelling assessment score SZ at multiple collection time points t The average value R0 of the corresponding time value; Step A2.3, by: ; Calculate a2 in the fitted straight line equation y=a2x+b2; Step A2.4: When a2 > 0, it indicates that the swelling is on an upward trend, indicating that the swelling of the soft tissue around the affected tooth is increasing over time. The larger a2 is, the more prominent the upward trend is. When a2>ay2, risk warning signal 2 is generated; When a2<0, it means that the swelling is on a downward trend, that is, the swelling gradually subsides over time; the larger |a2| is, the more obvious the downward trend is; If a2=0, it means that the swelling trend is relatively stable and the degree of swelling does not change significantly over time; As a further solution of the present invention, the data analysis module is further configured to perform occlusal restoration analysis based on the postoperative status data of the target patient, in the following manner: pass: ; Calculate the occlusal assessment score SB at multiple acquisition time points t The average value SB0; If SB0≤1, the occlusal function was considered to have recovered well; If 1<SB0≤2, the occlusal function is considered to have recovered moderately; If SB0>2, it is considered that the occlusal function has not recovered well.

[0014] A rehabilitation management method based on dental root canal therapy is implemented by a rehabilitation management system based on dental root canal therapy, and the method comprises the following steps: Step 1: Data Collection: Collect postoperative status data of target patients; Step 2: Data Analysis Conduct rehabilitation analysis based on the target patient's postoperative status data, determine the patient's rehabilitation index based on the rehabilitation analysis, and then classify the patient's rehabilitation status into different rehabilitation levels based on the patient's rehabilitation index; Step 3: Data display: The rehabilitation index obtained from the rehabilitation analysis and the rehabilitation level determined based on the rehabilitation index are fed back to the doctor.

[0015] Beneficial effects of the present invention: Comprehensive and accurate rehabilitation assessment: The rehabilitation tracking module collects multi-dimensional postoperative status data, including pain assessment scores, swelling assessment scores, occlusion assessment scores, etc., at a specified frequency. This can fully reflect the patient's recovery after root canal treatment and provide sufficient basis for subsequent accurate analysis.

[0016] Scientifically quantified rehabilitation grading: Based on the preset weight coefficients and the corresponding assessment scores of pain, swelling and occlusal function, the rehabilitation index E is calculated through a rigorous formula, and the rehabilitation status is subdivided into good recovery, medium recovery and poor recovery levels. This allows doctors and patients to intuitively understand the degree of recovery and take targeted measures.

[0017] Trend prediction and risk warning: In addition to focusing on the current status, the data analysis module can also perform trend analysis on pain and swelling separately. Through linear fitting and slope judgment, it can detect the development trend of pain and swelling in advance, and generate risk warning signals in time when the trend deteriorates and exceeds the threshold, allowing medical staff to intervene in advance and reduce the risk of poor prognosis.

[0018] Special analysis of occlusal function: By calculating the average of the occlusal assessment scores at multiple collection time points and judging the degree of occlusal function recovery based on different value ranges, doctors can focus on patients with poor occlusal function recovery and develop personalized rehabilitation plans.

[0019] Efficient information transmission between doctors and patients: With the help of the data display module, complex data analysis results, such as rehabilitation index, rehabilitation level and various trend analysis conclusions, are quickly and accurately fed back to doctors, helping doctors to timely and comprehensively grasp the patient's rehabilitation dynamics, optimize treatment decisions, and improve the quality and efficiency of rehabilitation management after root canal treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention will be further described below with reference to the accompanying drawings.

[0021] Figure 1 This is a system block diagram of a rehabilitation management system based on dental root canal treatment of the present invention.

[0022] Figure 2 It is a flow chart of a rehabilitation management method based on dental root canal treatment according to the present invention. DETAILED DESCRIPTION

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention. Example 1

[0024] See also Figure 1 and Figure 2 As shown, the present invention is a rehabilitation management system and method based on dental root canal treatment, comprising: A rehabilitation tracking module is used to collect postoperative status data of target patients at a specified collection frequency; Postoperative status data include: The visual analog scale was used to evaluate the postoperative pain level of the patients, and the pain assessment score of the patients at each collection time point was obtained and marked as SP t , t=1, 2, …, e, e represents the number of acquisition time nodes; The evaluation method is as follows: The visual analogue scale (VAS) is used to quantify an individual's subjective experience of a sensation or condition, such as pain severity. The VAS uses a sliding ruler with a 10-cm, unmarked track on the front. A sliding marker is placed between the "0" and "10" ends, with "0" representing no pain and "10" representing the most severe, unbearable pain. During the assessment, the person being assessed moves the marker to the corresponding mark on the scale based on their feelings, indicating the severity of their experience. When the patient marks the position at d cm, the pain assessment score, SP t =d, where the value range of d is 0-10; The swelling was assessed by measuring the maximum diameter of the soft tissue swelling around the patient's teeth, and the patient's swelling assessment score at each sampling time point was obtained and marked as SZ. t ; The swelling assessment score was calculated using the following formula: ; Where z is the maximum diameter of the soft tissue swelling around the patient's teeth actually measured, and zy is the pre-set swelling diameter threshold; By having the patient bite the test piece, the bite assessment is performed according to the indentation depth of the test piece, and the patient's bite assessment score at each acquisition time point is obtained and marked as SB t ; In this embodiment, the bite force test piece is a tool for measuring and evaluating bite force. In a dental clinic, a doctor may use the bite force test piece to evaluate a patient's bite force in order to diagnose and treat periodontal disease or other oral problems. The occlusal assessment score is calculated using the following formula: ; Where h is the actual indentation depth of the patient's bite force test piece, and hy is the preset indentation depth threshold; The data analysis module is used to perform rehabilitation analysis based on the postoperative status data of the target patient. The rehabilitation analysis method is as follows: pass: ; Calculate the patient's recovery index E; Where β1, β2, and β3 are the preset weight coefficients corresponding to pain, swelling, and occlusal function, respectively; The patient's recovery status is divided into different recovery levels according to the patient's recovery index E; When E≤0.8×Ey, the patient’s recovery status is classified as good recovery level; When 0.8×Ey<E≤Ey, the patient’s recovery status is classified as moderate recovery level; When E>Ey, the patient's recovery status is divided into poor recovery level; The data display module is used to feed back the patient's recovery index and the corresponding recovery level of the patient's recovery status to the doctor; The comprehensive rehabilitation assessment result feedback is to display the patient's rehabilitation index E and the patient's rehabilitation level at the top of the display interface in the form of a colored banner to prompt the doctor; Different colors represent different stages of recovery, such as green for good recovery, yellow for moderate recovery, and red for poor recovery. The banner also includes a detailed description of the current recovery stage and corresponding recommended measures. For example, if the patient is in good recovery, the doctor can appropriately reduce the frequency of follow-up visits. If the patient is in poor recovery, the doctor is advised to re-evaluate the treatment plan and add auxiliary treatment methods. This embodiment uses the rehabilitation tracking module to collect postoperative status data including pain assessment scores, swelling assessment scores, occlusion assessment scores, etc. at a specified collection frequency, which can grasp the patient's postoperative condition in multiple dimensions; the data analysis module calculates the rehabilitation index based on the postoperative status data according to the preset weight coefficient, and divides the patient's rehabilitation status into different levels such as good rehabilitation, medium rehabilitation, and poor rehabilitation, so that the doctor has a clear and quantitative understanding of the patient's rehabilitation level; the data display module can feedback the patient's rehabilitation index and corresponding rehabilitation level to the doctor in an intuitive form such as a colored banner, and different colors represent different stages with corresponding recommended measures, which makes it convenient for the doctor to quickly understand the situation and make reasonable decisions such as follow-up visits. Example 2

[0025] As the second embodiment of the present invention, when the present application is specifically implemented, compared with the first embodiment, the technical solution of this embodiment differs from that of the first embodiment only in that in this embodiment, the data analysis module further performs pain trend analysis based on the postoperative status data of the target patient: Pain assessment scores SP at multiple collection time points t Perform linear fitting; The equation of the fitted line is y=a1x+b1, where a1 is the slope and b1 is the intercept; Then the pain trend is determined by analyzing the a1 value; The pain trend is determined as follows: Step A1.1: Obtain pain assessment scores SP at multiple acquisition time points t The corresponding time value is marked as T t ; Step A1.2, by: ; Calculate the average value SP0 of pain assessment scores at multiple collection time points; Also through: ; Calculate the pain assessment score SP at multiple collection time points t The average value of the corresponding time value T0; Step A1.3, by: ; Calculate a1 in the fitting straight line equation y=a1x+b1; Step A1.4: If a1 > 0, it indicates that the pain is on an upward trend, that is, the pain intensity gradually increases over time; the larger a1 is, the more obvious the upward trend is; When a1>ay1, risk warning signal 1 is generated; If a1<0, it means that the pain is on a downward trend, which means that the pain gradually decreases over time. The larger |a1| is, the more significant the downward trend is. If a1=0, the pain trend is relatively stable, and the pain level has no obvious trend of changing over time; The data display module also feeds back the pain trend analysis results from the data analysis module to the doctor; Based on the first embodiment, the data analysis module of this embodiment adds linear fitting and trend analysis of the pain assessment score, which can determine whether the pain is rising, falling or in a relatively stable trend, helping doctors to know the pain changes in advance and respond in time; when the upward trend of pain is obvious, a risk warning signal 1 can be generated, allowing doctors to pay more targeted attention to patients who may experience increased pain, take corresponding intervention measures, and ensure that the patient's recovery process is smoother; the data display module feeds back the pain trend analysis results to the doctor, further enriching the information provided to the doctor and assisting him in making more accurate medical decisions. Example 3

[0026] As the third embodiment of the present invention, when the present application is specifically implemented, compared with the first and second embodiments, the technical solution of this embodiment is to combine the solutions of the first and second embodiments. The technical solution of this embodiment is different from the first and second embodiments only in that in this embodiment, the data analysis module also performs swelling trend analysis based on the postoperative status data of the target patient: Swelling assessment score SZ at multiple collection time points t Perform linear fitting; The equation of the fitted line is y=a2x+b2, where a2 is the slope and b2 is the intercept; Then the swelling trend is determined by analyzing the a2 value; The swelling trend is determined as follows: Step A2.1: Obtain swelling assessment scores SZ at multiple acquisition time points t The corresponding time value is marked as R t ; Step A2.2, by: ; Calculate the average SP0 of the swelling assessment scores at multiple collection time points; Also through: ; Calculate the swelling assessment score SZ at multiple collection time points t The average value R0 of the corresponding time value; Step A2.3, by: ; Calculate a2 in the fitted straight line equation y=a2x+b2; Step A2.4: When a2 > 0, it indicates that the swelling is on an upward trend, indicating that the swelling of the soft tissue around the affected tooth is increasing over time. The larger a2 is, the more prominent the upward trend is. When a2>ay2, risk warning signal 2 is generated; When a2<0, it means that the swelling is on a downward trend, that is, the swelling gradually subsides over time; the larger |a2| is, the more obvious the downward trend is; If a2=0, it means that the swelling trend is relatively stable and the degree of swelling does not change significantly over time; The data display module also feeds back the swelling trend analysis results from the data analysis module to the doctor; Based on the first and second embodiments, this embodiment adds linear fitting and trend analysis of the swelling assessment score, which can clearly indicate whether the swelling is increasing, decreasing, or maintaining a stable trend, helping doctors to grasp the dynamic changes of soft tissue swelling around the affected tooth in real time; when the swelling shows an obvious upward trend, a second risk warning signal is generated, which helps doctors to detect abnormal swelling in a timely manner and adjust the treatment or nursing plan to avoid worsening of the swelling problem and affecting the patient's recovery; the data display module feeds back the swelling trend analysis results, which is combined with other existing feedback information, so that doctors can comprehensively judge the patient's postoperative recovery status from more angles and formulate a more scientific medical plan. Example 4

[0027] As the fourth embodiment of the present invention, when the present application is specifically implemented, compared with the first, second and third embodiments, the only difference between this embodiment and the first, second and third embodiments is that in this embodiment, the data analysis module further performs occlusal recovery analysis based on the postoperative status data of the target patient: pass: ; Calculate the occlusal assessment score SB at multiple acquisition time points t The average value SB0; If SB0≤1, the occlusal function was considered to have recovered well; If 1<SB0≤2, the occlusal function is considered to have recovered moderately; If SB0>2, the occlusal function was considered to have poorly recovered; The data display module also feeds back the occlusal restoration analysis results in the data analysis module to the doctor; The data analysis module of this embodiment adds an analysis of the occlusal recovery status. By calculating the average value of the occlusal assessment score, it determines whether the occlusal function recovery is good, average, or poor, allowing the doctor to clearly understand the degree of recovery of the patient's occlusal function; it provides a basis for the doctor to subsequently decide whether further intervention is needed to restore the occlusal function, which helps to optimize the overall treatment plan and improve the quality of the patient's oral function recovery; the data display module feeds back the occlusal recovery analysis results to the doctor, expanding the information dimension fed back to the doctor, so that the doctor can more comprehensively grasp the various aspects of the patient's recovery after dental root canal treatment. Example 5

[0028] As the fifth embodiment of the present invention, when this application is specifically implemented, compared with the first, second, third and fourth embodiments, the technical solution of this embodiment is to combine and implement the solutions of the above-mentioned first, second, third and fourth embodiments.

[0029] This embodiment combines and implements the solutions of Embodiments 1 to 4, and can conduct a comprehensive and systematic analysis and evaluation of the patient's postoperative condition from multiple aspects and angles, such as pain, swelling, occlusion, and overall rehabilitation level; it provides doctors with the most abundant and complete postoperative information about patients, covering dynamic changes in various dimensions of rehabilitation, functional recovery, and comprehensive rehabilitation level, etc., greatly helping doctors make accurate, scientific, and reasonable decisions on follow-up treatment, nursing, and follow-up visits, and ensuring that patients can recover better.

[0030] A rehabilitation management method based on dental root canal therapy is implemented by a rehabilitation management system based on dental root canal therapy, and the method comprises the following steps: Step 1: Data Collection: Collect postoperative status data of target patients; Step 2: Data Analysis Conduct rehabilitation analysis based on the target patient's postoperative status data, determine the patient's rehabilitation index based on the rehabilitation analysis, and then classify the patient's rehabilitation status into different rehabilitation levels based on the patient's rehabilitation index; Step 3: Data display: The rehabilitation index obtained from the rehabilitation analysis and the rehabilitation level determined based on the rehabilitation index are fed back to the doctor.

[0031] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0032] It should be stated that all user data collected in this application is collected with the user's consent and authorization, and the use of user data is legal and compliant, and the use and processing of user data complies with the relevant laws, regulations and standards of the relevant regions.

[0033] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included within the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A rehabilitation management system based on dental root canal treatment, characterized in that: include: A rehabilitation tracking module is used to collect postoperative status data of target patients at a specified collection frequency; The data analysis module is used to perform rehabilitation analysis based on the postoperative status data of the target patient, determine the patient's rehabilitation index based on the rehabilitation analysis, and then classify the patient's rehabilitation status into different rehabilitation levels based on the patient's rehabilitation index; The data display module is used to feed back the results obtained by the data analysis module to doctors.

2. A dental root canal treatment-based rehabilitation management system according to claim 1, characterized in that: Postoperative status data include: The visual analog scale was used to obtain the patient's pain assessment score at each collection time point and marked as SP t , t=1, 2, …, e, e represents the number of acquisition time nodes; The swelling was assessed by measuring the maximum diameter of the soft tissue swelling around the patient's teeth, and the patient's swelling assessment score at each sampling time point was obtained and marked as SZ. t ; By having the patient bite the test piece, the bite assessment is performed according to the indentation depth of the test piece, and the patient's bite assessment score at each acquisition time point is obtained and marked as SB t .

3. A dental root canal treatment-based rehabilitation management system according to claim 2, characterized in that: The swelling assessment score was calculated using the following formula: ； Where z is the maximum diameter of the soft tissue swelling around the patient's teeth actually measured, and zy is the pre-set swelling diameter threshold.

4. A dental root canal treatment-based rehabilitation management system according to claim 2, characterized in that: The occlusal assessment score is calculated using the following formula: ； Where h is the actual indentation depth of the patient's bite force test piece, and hy is the preset indentation depth threshold.

5. A dental root canal treatment-based rehabilitation management system according to claim 2, characterized in that: The rehabilitation analysis method is as follows: pass: ; Calculate the patient's recovery index E; Where β1, β2, and β3 are the preset weight coefficients corresponding to pain, swelling, and occlusal function, respectively; When E≤0.8×Ey, the patient’s recovery status is classified as good recovery level; When 0.8×Ey<E≤Ey, the patient’s recovery status is classified as moderate recovery level; When E>Ey, the patient's recovery condition is divided into poor recovery level.

6. A dental root canal treatment-based rehabilitation management system according to claim 2, characterized in that: The data analysis module is also used to perform pain trend analysis and swelling trend analysis based on the postoperative status data of the target patient. The method is to perform linear fitting on the pain assessment scores and swelling assessment scores of multiple collection time nodes, and then determine the pain trend and swelling trend through the slope value in the fitted straight line equation.

7. A dental root canal treatment-based rehabilitation management system according to claim 6, characterized in that: The pain trend is determined as follows: Step A1.1: Obtain pain assessment scores SP at multiple acquisition time points t The corresponding time value is marked as T t ; Step A1.2, by: ; Calculate the average value SP0 of pain assessment scores at multiple collection time points; Also through: ; Calculate the pain assessment score SP at multiple collection time points t The average value of the corresponding time value T0; Step A1.3, by: ; Calculate the slope a1 of the fitted straight line equation corresponding to the pain assessment score; Step A1.4: If a1 > 0, it indicates that the pain is on an upward trend, that is, the pain intensity gradually increases over time; the larger a1 is, the more obvious the upward trend is; When a1>ay1, risk warning signal 1 is generated; If a1<0, it means that the pain is on a downward trend, which means that the pain gradually decreases over time. The larger |a1| is, the more significant the downward trend is. If a1=0, the pain trend is relatively stable, and the pain intensity has no obvious trend of changing over time.

8. A dental root canal treatment-based rehabilitation management system according to claim 7, characterized in that: The swelling trend is determined in the same way as the pain trend; When a2>0, it indicates that the swelling is on an upward trend, indicating that the swelling of the soft tissue around the affected tooth is increasing over time; When a2>ay2, risk warning signal 2 is generated; When a2 < 0, it indicates that the swelling is on a downward trend, that is, the swelling gradually subsides over time; If a2=0, it means that the swelling trend is relatively stable and the degree of swelling does not change significantly over time; Wherein, a2 is the slope of the fitted straight line equation corresponding to the pain assessment score.

9. A dental root canal treatment-based rehabilitation management system according to claim 2, characterized in that: The data analysis module is also used to perform occlusal restoration analysis based on the postoperative status data of the target patient in the following manner: pass: ; Calculate the occlusal assessment score SB at multiple acquisition time points t The average value SB0; If SB0≤1, the occlusal function was considered to have recovered well; If 1<SB0≤2, the occlusal function is considered to have recovered moderately; If SB0>2, it is considered that the occlusal function has not recovered well.

10. A rehabilitation management method based on dental root canal treatment, characterized in that: The method is implemented by a dental root canal treatment-based rehabilitation management system according to any one of claims 1 to 9.

Images