CN-121366711-B - Method, system, device, equipment and program product for predicting tension pneumothorax progress

CN121366711BCN 121366711 BCN121366711 BCN 121366711BCN-121366711-B

Abstract

The invention provides a method, a system, a device, equipment and a program product for predicting the progress of a tension pneumothorax, wherein the method is performed based on a computer and comprises the steps of obtaining the count data of an affected partition of a sample POCUS to be detected, performing classification prediction based on the count data of the affected partition of POCUS to obtain a classification result of the tension pneumothorax of the sample to be detected on the basis of the occurrence of the cyclic collapse risk, obtaining the classification result of the tension pneumothorax of the sample to be detected on the basis of the count data of the affected partition of POCUS to be detected which is more than or equal to 4, and obtaining the classification result of the tension pneumothorax of the sample to be detected on the basis of the count data of the affected partition of POCUS to be detected which is less than 4.

Inventors

LIU LIRONG
SUN HAO
GAO NONG
LV FAQIN

Assignees

中国人民解放军总医院第三医学中心

Dates

Publication Date: 20260505
Application Date: 20250929

Claims (10)

1. A method of clinical decision making for a tension pneumothorax, the method being computer-based and comprising: Acquiring counting data of affected areas of a sample POCUS to be detected and side information of the tension pneumothorax, wherein the sides of the tension pneumothorax respectively comprise left sides and/or right sides, the counting data of the affected areas POCUS are divided into six areas according to a six-area method, namely dividing each side of the chest into six areas, namely an upper front area, a lower front area, an upper side area, a lower side area, an upper rear area and a lower rear area, wherein the number of the areas is equal to the number of the areas with bar codes or the lost lung sliding in an M mode of POCUS; Performing classification prediction based on the POCUS affected zone count data to obtain a classification result of the occurrence of the cyclic collapse risk of the tension pneumothorax of the sample to be detected; If the count data of the affected area of the sample POCUS to be detected is more than or equal to 4, a classification result of high risk of cyclic collapse of the tension pneumothorax of the sample to be detected is obtained, wherein the cyclic collapse is that the heart displacement is less than or equal to 50; If the count data of the affected area of the sample POCUS to be detected is less than 4, a classification result of low risk of cyclic collapse of the tension pneumothorax of the sample to be detected is obtained; giving clinical decision advice based on the POCUS affected zone count data and side information of the tension pneumothorax; If the sample to be measured is a right tension pneumothorax and the count data of the affected areas of POCUS is more than or equal to 4, clinical decision suggestion for taking tertiary measures is given, if the sample to be measured is a left tension pneumothorax and the count data of the affected areas of POCUS is more than or equal to 4, clinical decision suggestion for taking secondary measures is given, and if the sample to be measured is a left tension pneumothorax and a right tension pneumothorax and the count data of the affected areas of POCUS is more than or equal to 4, clinical decision suggestion for taking primary measures is given; the response force of the first-level measure is highest, the second-level measure is secondary, and the third-level measure is more secondary.
2. A clinical decision making system for a tension pneumothorax, the system comprising: The acquisition module is used for acquiring counting data of affected areas of a sample POCUS to be detected and side information of the tension pneumothorax, wherein the side of the tension pneumothorax comprises a left side and/or a right side, the counting data of the affected areas POCUS are divided according to a six-area method, and the number of areas with bar code signs or lost lung sliding appears in an M mode of POCUS after the counting data of the affected areas are divided, wherein the six-area method is used for dividing each chest part into six areas, namely an upper front area, a lower front area, an upper side area, a lower side area, an upper rear area and a lower rear area; the clinical decision suggestion module is used for carrying out classification prediction based on the POCUS affected area count data to obtain a classification result of the occurrence of the cyclic collapse risk of the tension pneumothorax of the sample to be detected; If the count data of the affected area of the sample POCUS to be detected is more than or equal to 4, a classification result of high risk of cyclic collapse of the tension pneumothorax of the sample to be detected is obtained, wherein the cyclic collapse is that the heart displacement is less than or equal to 50; If the count data of the affected area of the sample POCUS to be detected is less than 4, a classification result of low risk of cyclic collapse of the tension pneumothorax of the sample to be detected is obtained; giving clinical decision advice based on the POCUS affected zone count data and side information of the tension pneumothorax; If the sample to be measured is a right tension pneumothorax and the count data of the affected areas of POCUS is more than or equal to 4, clinical decision suggestion for taking tertiary measures is given, if the sample to be measured is a left tension pneumothorax and the count data of the affected areas of POCUS is more than or equal to 4, clinical decision suggestion for taking secondary measures is given, and if the sample to be measured is a left tension pneumothorax and a right tension pneumothorax and the count data of the affected areas of POCUS is more than or equal to 4, clinical decision suggestion for taking primary measures is given; the response force of the first-level measure is highest, the second-level measure is secondary, and the third-level measure is more secondary.
3. A computer device comprising a first computing device including a memory for storing program instructions and a processor for invoking the program instructions, which when executed, implement the steps of the clinical decision method for tension pneumothorax of claim 1.
4. A computer device according to claim 3, wherein the processor is one or more.
5. The computer device of claim 4, wherein the processor comprises one or more of a controller, an integrated circuit, a microchip, and a computer.
6. The computer device of any of claims 3-5, wherein the device further comprises one or more of POCUS instruments, user interface devices.
7. The computer device of claim 6, wherein the device further comprises a tension pneumothorax side identification device.
8. The computer device of claim 6, wherein the user interface device comprises a local computing device, a remote computing device.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the clinical decision method for tension pneumothorax according to claim 1.
10. A computer program product, characterized in that the computer program, when being executed by a processor, implements the steps of the clinical decision method for tension pneumothorax according to claim 1.

Description

Method, system, device, equipment and program product for predicting tension pneumothorax progress Technical Field The invention belongs to the field of intelligent medical treatment, and particularly relates to a method, a system, a device, equipment and a program product for predicting tension pneumothorax progress. Background Tension pneumothorax (Tension pneumothorax, TP) is a life threatening emergency, especially in trauma care where rapid identification and immediate treatment is critical to patient survival. However, pneumothorax diagnosis is still mainly at a qualitative level, and clinicians usually make binary judgments of "pneumothorax" or "pneumothorax free" based on symptoms. There is currently a lack of a validated, quantifiable indicator for early warning of impending circulatory collapse to guide clinical decisions. In addition, in normal times, under the support of sufficient medical resources, a single individual can be effectively treated in time no matter which side of the tension pneumothorax is, but in the first-line rescue or disaster rescue site of war sites, due to the batch production of wounded persons, when facing more rescue tasks possibly existing tension pneumothorax injuries, the sequential problem of rescue should be emphasized. This further embodies the urgency of seeking a validated, quantifiable indicator. Disclosure of Invention In view of this, the present invention has been made in order to make up for the deficiencies of the prior art. The first aspect of the present invention provides a method of predicting the progression of a tension pneumothorax, the method being computer-based and comprising: Acquiring the count data of affected areas of a sample POCUS to be detected; Performing classification prediction based on the POCUS affected zone count data to obtain a classification result of the occurrence of the cyclic collapse risk of the tension pneumothorax of the sample to be detected; if the counted data of the affected areas of the sample POCUS to be detected is more than or equal to 4, a classification result with high risk of cyclic collapse of the tension pneumothorax of the sample to be detected is obtained, and if the counted data of the affected areas of the sample POCUS to be detected is less than 4, a classification result with low risk of cyclic collapse of the tension pneumothorax of the sample to be detected is obtained. In the present invention, the POCUS affected partition count data is the number of partitions in which "bar code sign" or disappearance of lung sliding occurs in the M mode of POCUS after the partitioning according to the six-partition method. The six-zone division refers to dividing each chest portion into six areas of front zone (upper and lower), side zone (upper and lower) and rear zone (upper and lower). In the invention, POCUS (point-of-care ultrasonic diagnostic equipment) refers to portable or palm-type color Doppler ultrasonic diagnostic equipment, and has the characteristics of small volume, simple and convenient operation, suitability for bedside, field and other environments. In some embodiments, the POCUS may include, but is not limited to, the form of a hand-held probe, tablet, or cell phone connection, notebook portable ultrasound. In some embodiments, the POCUS is not limited to a particular manufacturer or model, such as may be a portable color Doppler ultrasound device manufactured by Philips, GE, mindray, butterfly Network, or the like. In the present invention, the cyclic collapse is defined as cardiac output (Cardiac output, CO). Ltoreq.50% of baseline. In a second aspect, the present invention provides a system for predicting the progression of a tension pneumothorax, the system comprising: the acquisition module is used for acquiring the count data of the affected partition of the sample POCUS to be detected; The prediction module is used for carrying out classification prediction based on the POCUS affected area count data to obtain a classification result of the occurrence of the cyclic collapse risk of the tension pneumothorax of the sample to be detected; If the count data of the affected areas of the sample POCUS to be detected is more than or equal to 4, a classification result with high risk of cyclic collapse of the tension pneumothorax of the sample to be detected is obtained, if the count data of the affected areas of the sample POCUS to be detected is less than 4, a classification result with low risk of cyclic collapse of the tension pneumothorax of the sample to be detected is obtained; And the output module is used for outputting the classification result. A third aspect of the invention provides a method of clinical decision making for a tension pneumothorax, the method being computer-based and comprising: Acquiring counting data of affected areas of a sample POCUS and side information of the tension pneumothorax, wherein the side of the tension pneumothorax comprises a left side and/or a right sid