Risk prediction method for improving diagnosis accuracy of acute exacerbation state of chronic obstructive pulmonary disease

Abstract

The invention relates to a risk prediction method for improving the diagnosis accuracy of an acute exacerbation state of chronic obstructive pulmonary disease. Specifically, the invention establishes a novel and more accurate risk prediction method for acute exacerbation of chronic obstructive pulmonary disease (chronic obstructive pulmonary disease) patients. The method is improved on the basis of an existing genetic risk scoring GRS method, an eGRS prediction method is provided, the traditional GRS method calculates genetic risks based on whole genome genetic mutation, and eGRS predicts disease risks based on genetic mutation on exon sequences, so that the calculation precision is improved, and the accuracy of risk prediction is further improved. According to the method, exon sequencing and a genetic risk scoring method are combined, a new risk prediction method eGRS is designed, and the acute exacerbation occurrence risk of the chronic obstructive pulmonary disease patient can be predicted more accurately.

Description

technical field [0001] The invention relates to the field of medical detection, in particular to a novel risk prediction method for acute exacerbation of chronic obstructive pulmonary disease. Background technique [0002] Chronic obstructive pulmonary disease, or COPD for short, is a common chronic airway inflammatory disease characterized by persistent respiratory symptoms and airway limitation. Acute exacerbation of COPD is a short-term continuous deterioration of respiratory symptoms in patients, which will further deteriorate the patient's health status, accelerate the decline of lung function and increase mortality. At present, it is believed that whether acute exacerbation occurs in patients with COPD is the result of multiple factors, among which genes play an important role. [0003] COPD is a disease with high morbidity and mortality, and the additional treatment required for acute exacerbation brings a huge economic burden to the patient's family and society. In...

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Problems solved by technology

[0006] However, the traditional GRS uses whole genome sequencing, which not only requires a large sample size, but also has a large amount of data, complex processing, slow output speed, and inaccurate positioning, which makes the research work heavy and the time period for gene positioning is long.

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