CN114550931A - Method and system for scoring heart failure of patient in hospital - Google Patents

Abstract

The present invention provides the present invention relates to a scoring method and system for patients with heart failure in a hospital, provides risk factors affecting the occurrence of in-hospital heart failure in STEMI patients after PPCI, and calculates the patient's risk score by a scoring tool. The system recommends follow-up plans based on the scoring results combined with patient medical information, and conducts long-term follow-up to improve the ability of early medical prevention.

Description

A method and system for scoring patients with heart failure in a hospital

technical field

The invention relates to the field of professional medical treatment and the field of computer software, in particular to a method and a system for scoring patients with heart failure in a hospital.

Background technique

Since the 1980s, the treatment concept of heart failure (heart failure) has undergone subversive changes. Neuroendocrine inhibitors have become the mainstream, and the concept of evidence-based medicine has been deeply rooted in the hearts of the people. Many countries and societies have successively formulated heart failure guidelines accordingly. my country has also successively issued and updated relevant guidelines and consensus, especially in 2014, the Chinese Medical Association Cardiovascular Branch and the Chinese Journal of Cardiovascular Disease Editorial Board officially released the "Chinese Heart Failure Diagnosis and Treatment Guidelines 2014", which covers the first time. Four major topics were covered: diagnosis and examination of heart failure, treatment of chronic heart failure, treatment of acute heart failure, and comprehensive treatment and follow-up management of heart failure. The release and promotion of the guidelines have effectively promoted the standardized diagnosis and treatment of heart failure in my country. In recent years, new research results and guidelines have been released continuously, and new ideas and directions have emerged one after another. my country has made great progress in the diagnosis and treatment of heart failure, but there is still a long way to go.

Under the traditional medical model, the long-term follow-up management of heart failure patients requires a lot of human and financial resources, and it is often impossible to rely solely on cardiologists, and the lack of management is unavoidable. The "Internet + medical health model" can realize the balanced allocation of medical resources across time and space. Through telemetry, television, telephone and the Internet, family-based disease management can be carried out in a planned way, and the self-participation of patients and their families can be realized. The effectiveness of the transition from specialist treatment to professional long-term management of chronic diseases has been proven. It also has good health economic benefits and can effectively reduce the medical burden. It is a win-win for patients and medical staff, and it is the general trend. This requires the transformation of the medical system, the transformation of the role of doctors and the renewal of social concepts. How to use big data, artificial intelligence, telemedicine, etc. to carry out comprehensive prevention and control of heart failure with Chinese characteristics, and achieve individualized, precise and long-term health management, is worthy of in-depth research, and domestic scholars have begun to explore this aspect.

With the continuous development of the Internet + medical model, and the increasing application of smart wearable devices in community and home scenarios, telemedicine monitoring has become an important means of follow-up management of patients in major medical institutions. Its convenience and effectiveness Sexuality is also recognized by professional bodies and the general public.

SUMMARY OF THE INVENTION

The purpose of the present invention is to aim at the above-mentioned deficiencies of the prior art, and to provide a scoring method and system for the occurrence of heart failure in a patient in a hospital. The purpose of the risk of heart failure.

To achieve the above object, the present invention has adopted the following technical solutions:

The present invention provides a method for scoring patients with heart failure in a hospital, comprising:

To identify parameters affecting the risk of in-hospital heart failure in patients with STEMI undergoing PPCI;

Determine the weight of each parameter risk score score;

Determine the scoring outcome model;

Generate scoring tool.

Further, the risk parameters include:

SBP<125mmHg;

Total occlusion;

Coronary artery stenosis quantity＞2;

Symptom-onset-to-balloon-time>5h;

Haemoglobin count<135g/L;

Diabetes;

NLR>8.5;

HR>90bmp;

Scr>85μmol/L;

AST>100U/L;

Anterior myocardial infarction;

TIMI flow<3after pPCI;

Age>65y;

Cardiac arrest.

Further, the regression coefficient β value obtained by the multivariate Logistic analysis of the weight of each of the risk parameters is used as a reference value to determine the score associated with each risk factor category, and to determine the risk score weight to generate an algorithm engine.

Further, the score weights of each of the risk parameters are:

SBP<125mmHg (1 point), Total occlusion (1 point), Coronary artery stenosisquantity (1 point), Symptom-onset-to-balloon-time>5h (1 point), Haemoglobin count<135g/L (2 point), Diabetes (2 points), NLR>8.5 (2 points), HR>90bmp (2 points), Scr>85μmol/L (2 points), AST>100U/L (3 points), Anterior myocardial infarction (3 points), TIMI flow<3after pPCI (4 points), Age>65y (4 points), Cardiac arrest (8 points);

Comprehensive score: 0-6 points are low risk, 7-14 points are medium risk, 15 points and above are high risk.

Further, a system for a patient developing heart failure in a hospital is implemented using a scoring method, and includes the following steps:

S1. Perform in-hospital heart failure risk score for patients after PPCI;

S2. On the scoring tool, input the risk parameters of the corresponding scoring model to obtain the total weight score;

S3. Corresponding the total weighted score to the result model to obtain the risk degree of the patient suffering from in-hospital heart failure;

S4. Enter the patient's ID number in the follow-up system, and use the ID number as the unique primary key to access the patient's in-hospital treatment data;

S5. In-hospital treatment data report of patients: basic information, admission information, vital signs, details of test results, details of imaging results, details of DSA intervention, etc.;

S6. Review the patient score results, recommend patient follow-up plans according to different risk levels, and make follow-up report records.

Further, the risk level includes low risk, medium risk and high risk,

General follow-up is recommended for the low risk, as follows:

S61. Basic status: including daily life and exercise ability, drug application dose and adverse reactions;

S62. Physical examination;

S63. Adjust the medication record.

Further, the medium-risk and high-risk recommended special follow-up, the specific content is as follows:

Follow-up to at least once within 6 months, or after the condition changes, in addition to the content of general follow-up, blood biochemistry, BNP/NT-proBNP, electrocardiogram, echocardiography and other tests related to the disease should be added. When doing chest X-ray, dynamic electrocardiogram.

Further, the patient's described follow-up timeline is as follows:

S71. Basic data entry, including: basic information, medical history, clinical symptoms, physical examination, biochemical examination, diagnosis, cardiac function, drug types and doses, and auxiliary examinations; S72, the second week, telephone follow-up, general follow-up content, including : Physical examination, activity endurance, drug adjustment plan, adverse reactions, etc.;

S73, 1 month, outpatient follow-up, general follow-up content, including: physical examination, activity tolerance, drug adjustment plan, adverse reactions, etc.;

S74, 2 months, outpatient follow-up, general follow-up content, including: physical examination, activity tolerance, drug adjustment plan, adverse reactions, etc.;

S75, 3 months, outpatient follow-up, general follow-up content, including: physical examination, activity tolerance, drug adjustment plan, adverse reactions, etc.;

S76, 6 months (or changes in condition), outpatient + special follow-up, general follow-up + special follow-up, including: blood biochemistry, BNP/NT-proBNP, ECG, echocardiography, etc., chest X-ray, dynamic ECG if necessary an examination;

S77, 9 months, outpatient follow-up, general follow-up content, including: physical examination, activity tolerance, drug adjustment plan, adverse reactions;

S78, 12 months, outpatient + special follow-up, general follow-up + special follow-up, including: blood biochemistry, BNP/NT-proBNP, ECG, echocardiography and other examinations, chest X-ray, dynamic ECG examination if necessary.

Further, during the follow-up process, the patient wears a smart wearable device to collect physiological signal data such as ECG, heart rate, blood pressure, blood oxygen, and sleep breathing, and upload the data to the doctor's workstation using the follow-up system as a carrier;

Accessed by medical staff at the doctor's workstation and issued a report to push back to the patient;

Follow-up reports are automatically generated on a regular basis and pushed to the patient and doctor respectively.

The beneficial effects of the invention are: through data processing and analysis, the risk factors and scoring methods for in-hospital heart failure after PPCI (direct percutaneous coronary intervention) in STEMI (acute myocardial infarction) patients are obtained. The scoring method is generated into a scoring engine and embedded in the system to form a scoring tool. The system recommends a follow-up plan based on the score results, and conducts long-term vital sign monitoring to achieve the purpose of early prevention and early detection.

Description of drawings

Fig. 1 is a flow chart of a method for scoring heart failure in a patient in a hospital of the present invention;

Fig. 2 is a flow chart of a scoring system for patients with heart failure in a hospital according to the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

A method for scoring patients with heart failure in a hospital, comprising: determining a risk parameter affecting the occurrence of heart failure in a hospital after a STEMI patient undergoes PPCI, and the specific risk parameter is:

SBP (systolic blood pressure) <125mmHg;

Total occlusion (complete occlusion of infarct-related vessels);

Coronary artery stenosis quantity > 2;

Symptom-onset-to-balloon-time (time from onset to balloon opening)>5h;

Haemoglobin count (hemoglobin level) <135g/L;

Diabetes (previous history of diabetes);

NLR (neutrophil to lymphocyte ratio)>8.5;

HR (heart rate)>90bmp;

Scr (serum creatinine)>85μmol/L;

AST (aspartate aminotransferase)>100U/L;

Anterior myocardial infarction;

TIMI flow<3after pPCI; (postoperative TIMI flow<3 grade)

Age (age)>65y;

Cardiac arrest (preoperative history of cardiac arrest).

The weight of each of the risk parameters is analyzed by multivariate Logistic (linear regression analysis model), and the regression coefficient β value obtained is used as a reference value to determine the score associated with each risk factor category, and to determine the risk score weight to generate an algorithm engine. .

The weights of each of the risk parameters are as follows:

SBP<125mmHg (1 point), Total occlusion (1 point), Coronary artery stenosisquantity (1 point), Symptom-onset-to-balloon-time>5h (1 point), Haemoglobin count<135g/L (2 point), Diabetes (2 points), NLR>8.5 (2 points), HR>90bmp (2 points), Scr>85μmol/L (2 points), AST>100U/L (3 points), Anterior myocardial infarction (3 points), TIMI flow<3after pPCI (4 points), Age>65y (4 points), Cardiac arrest (8 points);

Comprehensive score: 0-6 points are low risk, 7-14 points are medium risk, 15 points and above are high risk.

A system for a patient developing heart failure in a hospital, implemented using a scoring method, and including the following steps:

S1. Perform in-hospital heart failure risk score for patients after PPCI (direct percutaneous coronary intervention);

S2. On the scoring tool, input the risk parameters of the corresponding scoring model to obtain the total weight score;

S3. Corresponding the total weighted score to the result model to obtain the risk degree of the patient suffering from in-hospital heart failure;

S4. Enter the patient's ID number in the follow-up system, and use the ID number as the unique primary key to access the patient's in-hospital treatment data;

S5. In-hospital treatment data report of patients: basic information, admission information, vital signs, details of test results, details of imaging results, details of DSA intervention, etc.;

S6. Review the patient score results, and recommend patient follow-up plans according to different risk levels.

The risk level includes low risk, medium risk and high risk,

General follow-up is recommended for the low risk, as follows:

S61. Basic status: including daily life and exercise ability, drug application dose and adverse reactions;

S62. Physical examination;

S63. Adjust the medication record.

The medium-risk and high-risk recommended special follow-up, the specific content is as follows:

Follow-up at least once within 6 months, or after the disease changes, in addition to the content of general follow-up, disease-related blood biochemistry, BNP/NT-proBNP (brain natriuretic peptide/amino-terminal brain sodium) should be added. Urine peptide), electrocardiogram, echocardiogram, etc., chest X-ray, dynamic electrocardiogram if necessary.

The patient-reported follow-up timeline is as follows:

S71. Basic data entry, including: basic information, medical history, clinical symptoms, physical examination, biochemical examination, diagnosis, cardiac function, drug types and doses, and auxiliary examinations; S72, 2nd week, telephone follow-up, general follow-up content, including : Physical examination, activity endurance, drug adjustment plan, adverse reactions, etc.;

S73, 1 month, outpatient follow-up, general follow-up content, including: physical examination, activity tolerance, drug adjustment plan, adverse reactions, etc.;

S74, 2 months, outpatient follow-up, general follow-up content, including: physical examination, activity tolerance, drug adjustment plan, adverse reactions, etc.;

S75, 3 months, outpatient follow-up, general follow-up content, including: physical examination, activity tolerance, drug adjustment plan, adverse reactions, etc.;

S76, 6 months (or changes in condition), outpatient + special follow-up, general follow-up + special follow-up, including: blood biochemistry, BNP/NT-proBNP, ECG, echocardiography, etc., chest X-ray, dynamic ECG if necessary an examination;

S77, 9 months, outpatient follow-up, general follow-up content, including: physical examination, activity tolerance, drug adjustment plan, adverse reactions;

S78, 12 months, outpatient + special follow-up, general follow-up + special follow-up, including: blood biochemistry, BNP/NT-proBNP, ECG, echocardiography and other examinations, chest X-ray, dynamic ECG examination if necessary.

During the follow-up process, the patient wears a smart wearable device to collect physiological signal data such as ECG, heart rate, blood pressure, blood oxygen, sleep breathing, etc., and uses the follow-up system as a carrier to upload it to the doctor's workstation;

Accessed by medical staff at the doctor's workstation and issued a report to push back to the patient;

Follow-up reports are automatically generated on a regular basis and pushed to the patient and doctor respectively.

Example 1

Import patient medical data into database. According to the fixed parameter values of the scoring model and matching the patient's medical parameters, the patient's systolic blood pressure is 102, the infarct-related blood vessels are completely occluded, the number of coronary stenoses is 2, the time from onset to balloon opening is 10 hours, the hemoglobin is 180g/L, and there are Past history of diabetes, neutrophil-to-lymphocyte ratio of 7, heart rate of 86, serum creatinine of 90 μmol/L, aspartate aminotransferase of 70 U/L, no anterior myocardial infarction, postoperative TIMI (thrombolytic therapy for myocardial infarction) blood Flow = grade 3, age 70 years, no history of preoperative cardiac arrest;

The patient's parameter scores were obtained as:

Systolic blood pressure <125mmHg (0 points), complete occlusion of infarct-related vessels (1 point), number of coronary stenosis >2 (0 points), time from onset to balloon opening >5 hours (1 point), hemoglobin level <135g/L (0 points), previous history of diabetes (2 points), neutrophil-to-lymphocyte ratio>8.5 (0 points), heart rate>90bmp (0 points), serum creatinine>85μmol/L (2 points), aspartate aminotransferase> 100U/L (0 points), anterior myocardial infarction (0 points), postoperative TIMI blood flow <3 (0 points), age > 65 years (4 points), history of preoperative cardiac arrest (0 points);

The patient's total weighted score is 10 points;

The corresponding relationship between the patient's comprehensive total weight score and the risk of acute heart failure is obtained, and the result is: the patient's risk of heart failure is moderate risk;

Select the system to recommend special follow-up;

Select the time axis recommended by the system, and generate a follow-up plan at the same time;

The patient collects ECG data and heart rate data through the smart wearable device, and uploads it to the doctor through the follow-up system. The medical staff reads the data on the doctor's workstation and issues a report and pushes it back to the patient;

According to the follow-up timeline, the follow-up report is automatically generated at the key node system and pushed to the patient side and the doctor side respectively;

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by computer programs.

The above-mentioned embodiments only represent the embodiments of the present invention, and the descriptions thereof are specific and detailed, but should not be construed as limiting the scope of the patent of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can also be made, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention should be subject to the appended claims.

Claims (9)

1. A method for scoring the occurrence of heart failure in a patient in a hospital, comprising: comprises the steps of (a) preparing a mixture of a plurality of raw materials,

determining a risk parameter affecting the occurrence of heart failure in a hospital after a PPCI operation on a STEMI patient;

determining the risk score weight of each parameter;

determining a grading result model;

a scoring tool is generated.

2. A method according to claim 1 for scoring a patient's occurrence of heart failure in a hospital, wherein: the risk parameters include:

SBP<125mmHg；

Total occlusion；

Coronary artery stenosis quantity＞2；

Symptom-onset-to-balloon-time＞5h；

Haemoglobin count<135g/L；

Diabetes；

NLR>8.5；

HR>90bmp；

Scr>85μmol/L；

AST>100U/L；

Anterior myocardial infarction；

TIMI flow<3after pPCI；

Age>65y；

Cardiac arrest。

3. a method of scoring a patient in hospital for heart failure according to claim 2, wherein: and determining the score associated with each risk factor category by using a regression coefficient beta value obtained after the weight of each risk parameter is subjected to multivariate Logistic analysis as a reference value, determining the weight of the risk score, and generating an algorithm engine.

4. A method according to claim 3, wherein the risk parameters are weighted according to the score:

SBP <125mmHg (1 point), Total encapsulation (1 point), Coronary identity standardization (1 point), Symptom-onset-to-balloon-time > 5h (1 point), Haemoglobin count <135g/L (2 points), Diabetes (2 points), NLR >8.5(2 points), HR >90bmp (2 points), Scr > 85. mu. mol/L (2 points), AST >100U/L (3 points), antioxidant mycological interaction (3 points), TIMI flow <3after pPCI (4 points), Age >65y (4 points), Cardiac reset (8 points);

and (3) comprehensive scoring: 0-6 points for low risk, 7-14 points for medium risk, and 15 points and above for high risk.

5. A system for a patient to develop heart failure in a hospital setting, comprising: this is achieved with a scoring method according to any one of claims 1 to 3, and comprising the steps of:

s1, performing hospital heart failure occurrence risk scoring on the PPCI postoperative patient;

s2, inputting risk parameters of corresponding grading models on a grading tool to obtain a total weight score;

s3, corresponding the total weight score to a result model to obtain the heart failure risk degree in the patient' S hospital;

s4, inputting the identity card number of the patient in the follow-up system, and taking the identity card number as the only main key to retrieve and read the treatment data in the patient' S hospital;

s5, patient hospitalization data report: basic information, admission information, vital signs, examination result details, image result details, DSA intervention details and the like;

and S6, reviewing the scoring results of the patients, recommending follow-up plans of the patients according to different risk degrees, and making follow-up report records.

6. A system according to claim 5, wherein the system is adapted to enable a patient to develop heart failure in a hospital setting, and further comprising: the risk levels include low risk, medium risk and high risk,

the low-risk recommendation general follow-up visit specifically comprises the following contents:

s61, basic condition: including daily life and exercise capacity, drug application dose and adverse reactions;

s62, physical examination;

and S63, adjusting medication records.

7. A system according to claim 6, wherein the system is adapted to enable a patient to develop heart failure in a hospital setting, and further comprising: the medium risk and high risk recommend special follow-up visits, and the specific contents are as follows:

at least once in 6 months or after the disease condition changes, in addition to the general follow-up, the patient should be examined with blood biochemistry, BNP/NT-proBNP, electrocardiogram and echocardiogram, etc. related to the disease, and if necessary, chest X-ray and dynamic electrocardiogram examination.

8. A system for hospital-acquired heart failure in a patient according to claim 7 wherein the follow-up time axis for the patient is as follows:

s71, basic data entry, including: basic information, medical history, clinical symptoms, physical examination, biochemical examination, diagnosis, cardiac function, drug types and dosage, and auxiliary examination;

s72, week 2, telephone follow-up, general follow-up content, including: physical examination, exercise endurance, drug adjustment schemes, adverse reactions and the like;

s73, 1 month, clinic follow-up visit, general follow-up contents, including: physical examination, exercise endurance, drug adjustment schemes, adverse reactions and the like;

s74, 2 months, clinic follow-up visit, general follow-up contents, including: physical examination, exercise endurance, drug adjustment schemes, adverse reactions and the like;

s75, 3 months, clinic follow-up, general follow-up contents, including: physical examination, exercise endurance, drug adjustment schemes, adverse reactions and the like;

s76, 6 months (or disease change), clinic + special follow-up, general follow-up + special follow-up, including: blood biochemistry, BNP/NT-proBNP, electrocardiogram, echocardiogram and the like, and chest X-ray and dynamic electrocardiogram examination is carried out when necessary;

s77, 9 months, clinic follow-up, general follow-up contents, including: physical examination, exercise endurance, drug adjustment scheme, adverse reaction;

s78, 12 months, clinic + special follow-up, general follow-up + special follow-up, including: blood biochemistry, BNP/NT-proBNP, electrocardiogram, echocardiogram and the like, and chest X-ray and dynamic electrocardiogram examination are carried out when necessary.

9. A system for hospital-acquired heart failure in a patient according to claim 8, wherein: in the follow-up visit process, a patient wears the intelligent wearable device to acquire physiological signal data such as electrocardio, heart rate, blood pressure, blood oxygen, sleep and breath and uploads the physiological signal data to a doctor workstation by using a follow-up visit system as a carrier;

the doctor visits the doctor workstation by the medical staff and issues a report to the patient;

and automatically generating follow-up reports at regular time, and respectively pushing the follow-up reports to the patient end and the doctor end.

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