CN113160911A - Assessment system for preoperative liver function tolerance analysis - Google Patents
Assessment system for preoperative liver function tolerance analysis Download PDFInfo
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- CN113160911A CN113160911A CN202110217282.0A CN202110217282A CN113160911A CN 113160911 A CN113160911 A CN 113160911A CN 202110217282 A CN202110217282 A CN 202110217282A CN 113160911 A CN113160911 A CN 113160911A
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- 238000004458 analytical method Methods 0.000 title claims abstract description 28
- 230000003908 liver function Effects 0.000 title claims abstract description 24
- 238000012545 processing Methods 0.000 claims abstract description 26
- 238000011156 evaluation Methods 0.000 claims abstract description 17
- 238000007689 inspection Methods 0.000 claims abstract description 8
- 238000007405 data analysis Methods 0.000 claims abstract description 4
- 239000000284 extract Substances 0.000 claims abstract description 4
- 206010003445 Ascites Diseases 0.000 claims description 14
- 208000007386 hepatic encephalopathy Diseases 0.000 claims description 9
- 230000004083 survival effect Effects 0.000 claims description 9
- 102000009027 Albumins Human genes 0.000 claims description 8
- 108010088751 Albumins Proteins 0.000 claims description 8
- 102100027378 Prothrombin Human genes 0.000 claims description 8
- 108010094028 Prothrombin Proteins 0.000 claims description 8
- 238000008050 Total Bilirubin Reagent Methods 0.000 claims description 8
- 229940039716 prothrombin Drugs 0.000 claims description 8
- 238000012216 screening Methods 0.000 claims description 6
- 238000012360 testing method Methods 0.000 claims description 4
- 238000013480 data collection Methods 0.000 claims 1
- 238000001514 detection method Methods 0.000 abstract description 2
- 230000002980 postoperative effect Effects 0.000 abstract description 2
- 206010010071 Coma Diseases 0.000 description 4
- 206010044565 Tremor Diseases 0.000 description 4
- 230000003187 abdominal effect Effects 0.000 description 4
- 238000000034 method Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 210000004185 liver Anatomy 0.000 description 3
- 206010000117 Abnormal behaviour Diseases 0.000 description 2
- 230000005856 abnormality Effects 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 210000005036 nerve Anatomy 0.000 description 2
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- 210000003109 clavicle Anatomy 0.000 description 1
- 238000003759 clinical diagnosis Methods 0.000 description 1
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- 230000002459 sustained effect Effects 0.000 description 1
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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Abstract
An assessment system for preoperative hepatic function tolerance analysis, comprising a data collector, a data processing platform and a tolerance assessment system; the data collector is connected with a plurality of different databases, collects a plurality of examination data of the patient and transmits the collected examination data to the data processing platform; the data processing platform extracts the latest numerical value of each inspection data, performs data analysis on the latest inspection data, transmits the obtained analysis result to the tolerance evaluation system for classification and grading judgment to obtain a tolerance analysis result, and guides operation planning and implementation; compared with the prior art, the data of a plurality of databases are collected and screened through the data collector, the latest detection data of each index of the patient is selected, and the comparison, classification and analysis are carried out in the data processing platform and the tolerance evaluation system, so that the liver function tolerance of the patient is obtained, the manual workload is reduced, the liver function tolerance evaluation correctness of the patient is improved, the postoperative planning is facilitated, and the operation safety is improved.
Description
Technical Field
The invention belongs to the technical field of medical diagnosis and treatment, and particularly relates to an evaluation system for preoperative liver function tolerance analysis.
Background
The risk of operation needs to be evaluated and the operation scheme needs to be analyzed before the liver surgery. Liver function is often analyzed clinically, with the graded square of liver function as a criterion to assess whether a patient is able to tolerate surgery, and assessment of surgical tolerance affects the ratio of residual liver and the determination of the patient's surgical plan.
In the currently known clinical practical scene, indexes used for grading liver functions come from different systems in a hospital, statistical calculation is carried out in an artificial mode, the liver functions are graded according to calculated values, different operation schemes are needed for different liver function grades by using different residual liver ratios, errors are easy to make by adopting the artificial mode for statistical calculation, the efficiency is low, and the related analysis function is lacked.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides an evaluation system for preoperative liver function tolerance analysis, which can automatically acquire data and intelligently analyze the data.
In order to achieve the above purposes, the technical scheme adopted by the invention is as follows: an assessment system for preoperative hepatic function tolerance analysis comprises a data collector, a data processing platform and a tolerance assessment system, wherein the data collector is electrically connected with the data processing platform; the data collector is connected with a plurality of different databases and is used for collecting a plurality of examination data of the patient, each examination data is marked with examination time, and the collected examination data are transmitted to the data processing platform; the data processing platform extracts the latest numerical values of the inspection data, performs data analysis on the inspection data with the latest numerical values to obtain analysis results, and transmits the obtained analysis results to the tolerance evaluation system; and the tolerance evaluation system carries out classification and grading judgment on the obtained analysis result to determine the liver function tolerance of the patient.
As a preferred embodiment of the present invention, the examination data carries patient information, and the patient information is a name and an identification number of the patient.
As a preferred scheme of the invention, the identification number is an identification number or a medical insurance card number or a treatment card number or a registration serial number of the patient.
As a preferred scheme of the invention, the database comprises an HIS database, an LIS database, a PACS database and an EMR database, and the main data required by the system comprises: hepatic encephalopathy (stage) data, ascites data, total bilirubin (umol/L) data, albumin (g/L) data, and prothrombin time extension (sec) data.
As a preferred aspect of the present invention, the data collector includes an acquisition unit, a data screening unit, and a data backup unit.
In a preferred embodiment of the present invention, the acquisition unit acquires hepatic encephalopathy (stage) data, ascites data, total bilirubin (umol/L) data, albumin (g/L) data and prothrombin time extension (sec) data of the current patient in a data integration manner.
As a preferable aspect of the present invention, the data screening unit classifies different types of data of the same patient and sorts a plurality of data of the same type in order of examination time.
As a preferred embodiment of the present invention, a tolerance score table is established in the data processing platform, different examination data of the same patient are input into the tolerance score table to obtain different scores, and the different scores corresponding to all the examination data are accumulated.
As a preferable embodiment of the present invention, the tolerance evaluation system is formed with a grading criterion, and CHILD A grade, CHILD B grade and CHILD C grade are formed according to different scores obtained by the data processing platform.
As a preferred embodiment of the present invention, the CHILD class a is: the operation risk is low, and the survival rate of 1-2 years is 100-85%; CHILD grade B is: the operation risk is moderate, and the survival rate of 1-2 years is 80-60 percent; CHILD grade C: the operation risk is high, and the survival rate of 1-2 years is 45-35%.
Compared with the prior art, the invention has the beneficial effects that: data in a plurality of databases are collected and screened through a data collector, the latest detection data of each index of a patient is selected, comparison and division are carried out in a data processing platform and a tolerance evaluation system, the analysis result of the patient is obtained, the liver function tolerance of the patient is determined, the workload of manual collection, calculation, statistics and analysis is reduced, the correctness of the liver function tolerance evaluation of the patient is improved, postoperative planning is facilitated, and the safety of an operation is improved.
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FIG. 1 is a schematic flow diagram of the invention;
Detailed Description
The following describes embodiments of the present invention in detail with reference to the accompanying drawings.
As shown in fig. 1, an assessment system for preoperative hepatic function tolerance analysis includes a data collector, a data processing platform and a tolerance assessment system, wherein the data collector is electrically connected with the data processing platform, and the data processing platform is electrically connected with the tolerance assessment system; the data collector is connected with a plurality of different databases and is used for collecting a plurality of examination data of the patient, each examination data is marked with examination time, and the collected examination data are transmitted to the data processing platform; the data processing platform extracts the latest numerical values of all the inspection data, performs data analysis on the inspection data with the latest numerical values to obtain analysis results, and transmits the obtained analysis results to the tolerance evaluation system; and the tolerance evaluation system carries out classification and grading judgment on the obtained analysis result to determine the liver function tolerance of the patient.
The evaluation system mainly comprises the following stages: 1. determining a grading standard; 2. collecting data required by grading; 3. calculating a score for the patient; 4. automatic grading; 5. tolerance and surgical risk were analyzed.
The data collector is connected with the data processing platform through a wire or a wireless connection, the data processing platform is connected with the tolerance evaluation system through a wire or a wireless connection in the same way, the data collector is connected with a plurality of different databases through a wire or a wireless connection, and the number of the databases is set and selected according to actual needs.
The patient information is the name and identification number of the patient, the identification number is used for distinguishing the patients with the same name, the identification number is the identity card number or medical insurance card number or doctor seeing card number or registration serial number of the patient, and the identity card number or medical insurance card number or doctor seeing card number or registration serial number of each patient is an independent account number.
The data in the database is sent to the data collector through the sending unit after a certain time or a specific time, and the data sending time of the data can be set according to actual needs, for example: the data sending time of the database can be set to be in the morning, the data in the database can be updated every day in real time, and the overload of a transmission channel is reduced by sending the data in the morning; or setting two hours to send sequential data, so as to update the data in real time, and covering the data collector after the data is sent by the database.
The databases include a HIS database, a LIS database, a PACS database, and an EMR database. The main data required by the system are hepatic encephalopathy (period) data, ascites data, total bilirubin (umol/L) data, albumin (g/L) database and prothrombin time extension (seconds) data. Each database operates independently, all the databases are communicated with the data collector, and the data sending time of all the databases is consistent.
The data collector comprises an acquisition unit, a data screening unit and a data backup unit, wherein the acquisition unit is used for receiving different types of data from different databases, the database covers the data in the data collector after sending the data, and the data backup unit is used for recording the covered data, so that the data in the data collector can be traced after accidents or errors occur.
The method is characterized in that hepatic encephalopathy (period) data, ascites data, total bilirubin (umol/L) data, albumin (g/L) data and prothrombin time extension (second) data of a current patient are acquired in a data integration mode, and a data base layer can construct an integrated system through a correlation method or a method based on an intermediate model or a data warehouse.
The data screening unit classifies different types of data of the same patient and sorts a plurality of data of the same type according to the examination time sequence. The top data is the data of the last test performed by the patient.
The data processing platform establishes a tolerance algorithm according to a tolerance score table, which is as follows:
the hepatic encephalopathy (stage) is divided into four stages, one stage (prodromal stage), mild character change and behavior disorder in the clinical diagnosis process, and can have flutter tremor, and electroencephalogram is normal; in the second stage (early coma), confusion, sleep disorder and behavior disorder are mainly caused, fluttering tremor and obvious nerve signs exist, and electroencephalogram has characteristic abnormality; in the third stage (comatose stage), mainly comatose and mental disorder, various nerve signs are sustained or aggravated, and flutter tremor and electroencephalogram abnormality can be caused; in stage IV (coma period), the mind is completely lost, and the patient cannot wake up without tremor.
Patients were classified according to their clinical manifestations of hepatic encephalopathy and scored for stage.
Total bilirubin (umol/L), albumin (g/L) and prothrombin time extension (seconds) were scored for patient condition based on the amount and time in the patient.
The clinical abdominal moisture is divided into three types, namely mild abdominal moisture, moderate abdominal moisture and severe abdominal moisture, and two types are distributed: 1. taking the navel as a standard, the patient with the navel lower than the connecting line of the two lateral iliac bones is in a non-ascites state, the patient with the same level is in a mild ascites state, the patient with the navel higher than the navel even the navel is expanded to be in a medium and severe ascites state, 2, the patient with the movable voiced sound lower than the axillary midline is in a non-ascites state, the patient with the clavicle midline and the axillary midline is in a mild ascites state, the patient with the movable voiced sound higher than the axillary midline is in a medium and severe ascites state, and scoring is carried out according to different ascites of the patient.
Inputting different examination data of the same patient into a tolerance score table to obtain different scores, accumulating the different scores corresponding to all the examination data, and comparing the hepatic encephalopathy (stage), ascites, total bilirubin (umol/L), albumin (g/L) and prothrombin time extension (second) data obtained by the patient at the last time according to the table to obtain the score generated by the last data of the patient.
Meanwhile, the operator can also select the data examined by the patient at different times to calculate the tolerance score, so as to calculate whether the tolerance of the patient is better or not along with the change of time.
Grading standards are formed in the tolerance evaluation system, and a CHILD A grade, a CHILD B grade and a CHILD C grade are formed according to different scores obtained by the data processing platform, wherein the CHILD A grade is as follows: the operation risk is low, and the survival rate of 1-2 years is 100-85%; CHILD grade B is: the operation risk is moderate, and the survival rate of 1-2 years is 80-60 percent; CHILD grade C: the operation risk is high, and the survival rate of 1-2 years is 45-35%.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention; thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. An assessment system for preoperative hepatic function tolerance analysis is characterized by comprising a data collector, a data processing platform and a tolerance assessment system, wherein the data collector is electrically connected with the data processing platform; the data collector is connected with a plurality of databases of different systems and is used for collecting a plurality of times of examination data of the patient, each examination data is marked with examination time, and the collected plurality of times of examination data are transmitted to the data processing platform; the data processing platform extracts the latest numerical values of the inspection data, performs data analysis on the inspection data with the latest numerical values to obtain analysis results, and transmits the obtained analysis results to the tolerance evaluation system; and the tolerance evaluation system performs classification and grading judgment on the obtained analysis result.
2. The system of claim 1, wherein the patient information is a name and an identification number of the patient, and the patient information is carried on the respective test data.
3. An assessment system for pre-operative liver function tolerance analysis according to claim 2, wherein the identification number is a patient's identification number or medical care number or visit number or registration flow number.
4. An assessment system for pre-operative liver function tolerance analysis according to claim 1, wherein said databases include HIS database, LIS database, PACS database and EMR database, the main data required by the system including: hepatic encephalopathy (stage) data, ascites data, total bilirubin (umol/L) data, albumin (g/L) data, and prothrombin time extension (sec) data.
5. An assessment system for pre-operative liver function tolerance analysis according to claim 1 wherein the data collector comprises an acquisition unit, a data screening unit and a data backup unit.
6. The system of claim 1, wherein the data collection unit collects hepatic encephalopathy (stage) data, ascites data, total bilirubin (umol/L) data, albumin (g/L) data, and prothrombin time extension (sec) data of the patient in a data-integrated manner.
7. An assessment system for preoperative hepatic function tolerance analysis according to claim 5, wherein said data screening unit classifies different types of data of the same patient and sorts multiple data of the same type in order of examination time.
8. The system of claim 1, wherein the data processing platform is configured to establish a tolerance score table, input different test data of the same patient into the tolerance score table to obtain different scores, and accumulate the different scores corresponding to all the test data.
9. The system of claim 7, wherein the tolerance assessment system is configured with grading criteria, such that the grading criteria are configured to generate a CHILD class A, a CHILD class B, and a CHILD class C according to the scores obtained from the data processing platform.
10. An assessment system for pre-operative liver function tolerance analysis according to claim 8, wherein the CHILD class a is: the operation risk is low, and the survival rate of 1-2 years is 100-85%; CHILD grade B is: the operation risk is moderate, and the survival rate of 1-2 years is 80-60 percent; CHILD grade C: the operation risk is high, and the survival rate of 1-2 years is 45-35%.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102789536A (en) * | 2011-05-20 | 2012-11-21 | 中国人民解放军第二军医大学 | Method for establishing noninvasive evaluation model for liver surgical treatment risks |
| CN105335608A (en) * | 2015-10-16 | 2016-02-17 | 宜昌市中心人民医院 | Method for establishing liver function scoring formula by using matter-element analysis method |
| US20180250317A1 (en) * | 2017-03-01 | 2018-09-06 | Medigen Biotechnology Corp. | Muparfostat for use in treating patients with hepatitis virus-related hepatocellular carcinoma after surgical resection |
| CN110577998A (en) * | 2019-01-31 | 2019-12-17 | 上海交通大学医学院附属仁济医院 | Construction of molecular model for predicting postoperative early recurrence risk of liver cancer and application evaluation thereof |
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- 2021-02-26 CN CN202110217282.0A patent/CN113160911A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102789536A (en) * | 2011-05-20 | 2012-11-21 | 中国人民解放军第二军医大学 | Method for establishing noninvasive evaluation model for liver surgical treatment risks |
| CN105335608A (en) * | 2015-10-16 | 2016-02-17 | 宜昌市中心人民医院 | Method for establishing liver function scoring formula by using matter-element analysis method |
| US20180250317A1 (en) * | 2017-03-01 | 2018-09-06 | Medigen Biotechnology Corp. | Muparfostat for use in treating patients with hepatitis virus-related hepatocellular carcinoma after surgical resection |
| CN110577998A (en) * | 2019-01-31 | 2019-12-17 | 上海交通大学医学院附属仁济医院 | Construction of molecular model for predicting postoperative early recurrence risk of liver cancer and application evaluation thereof |
Non-Patent Citations (1)
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| 孙春伟: "肝硬化CA72-4、AFP水平对预后的评估价值", 《肝脏》 * |
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Application publication date: 20210723 |