COPD acute exacerbation concurrent respiratory failure prediction system and monitoring device

Abstract

The invention belongs to the technical field of COPD medical equipment, and particularly discloses a COPD acute exacerbation concurrent respiratory failure prediction system and a COPD acute exacerbation concurrent respiratory failure monitoring device. The prediction system comprises a data collection module used for collecting clinical case data of a sample, a data processing module used for receiving and processing the clinical case data and obtaining variable parameters, and a data processing module used for receiving and processing the clinical case data and obtaining the variable parameters, a risk factor acquisition module used for receiving the variable parameters and screening the variable parameters to obtain independent risk factors, and a prediction module used for bringing the independent risk factors into a machine learning prediction model and predicting the independent risk factors. According to the technical scheme, through cooperation of all the modules, collection and screening of sample information are achieved, and whether T2RF happens to a patient or not is predicted according to the collected information.

Description

technical field [0001] The invention belongs to the technical field of COPD medical equipment, and relates to a prediction system and a monitoring device for acute exacerbation of COPD complicated by respiratory failure. Background technique [0002] Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is defined as the acute deterioration of respiratory symptoms, which is a critical period in the course of chronic obstructive pulmonary disease (COPD) and the main factor determining the health status and prognosis of COPD patients. . [0003] Most literatures report that COPD patients have 0.5-3.5 acute exacerbations per year. One study found that the in-hospital mortality rate of AECOPD patients was 8.3%, and the three-year overall mortality rate was 49%. Respiratory muscle load-volume imbalance in AECOPD patients during hospitalization can easily lead to Type 2 respiratory failure (T2RF), resulting in hypoventilation, carbon dioxide retention and hypercap...

AI Technical Summary

Problems solved by technology

Some scholars at home and abroad have discovered and proved that certain inspection indicators are of certain significance in predicting respiratory failure in patients with COPD, but there are problems such as single indicators and no feasible prediction model

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