Risk factors of COPD complicated with pulmonary infection and construction of Nomogram model
Objective To investigate the risk factors associated with pulmonary infections in patients with chronic obstructive pulmonary disease(COPD)and to construct a nomogram model.Methods A total of 62 COPD patients with lung infection who visited our hospital from January 2024 to June 2024 were selected as the observation group and 62 COPD patients without lung infection were selected as the control group.Demographic data,personal history,past medical history and disease-related indicators of the two groups were analysed to explore disease-related factors by t-test or χ2 test.Logistic regression analysis was conducted to identify risk factors for pulmonary infection in patients with COPD.Utilizing the R language software package,a prediction model was built,which was then in-ternally validated using the correction curve,and its clinical predictive efficacy was assessed via the decision curve.Results There were no statistically significant differences between the two groups in terms of age,gender,BMI,history of alcohol consumption,and duration of the disease(P>0.05).Compared with the control group,patients in the observation group had higher rates of smoking,diabetes melli-tus,hypoproteinaemia,long-term use of glucocorticoids,antibiotic<15 d,tracheal intubation,elevated levels of TNF-ɑ,IL-6,and lower FEV1/FVC ratios(P<0.05).Smoking,diabetes mellitus,hypoproteinaemia,long-term use of glucocorticoids,duration of antibiotic use,tracheal intubation,TNF-ɑ,IL-6,and FEV1/FVC were identified as independent correlates of concurrent lung infections in patients with COPD(P<0.05).Duration of antibiotic use,TNF-ɑ,IL-6,and FEV1/FVC had predictive value for patients with AUCs of 0.754,0.618,0.881,and 0.817,respectively(P<0.05).The Nomogram model performed well in predicting the risk of COPD-combined lung infection,with an area under the curve of 0.987(95%CI:0.971～1.003).The calibration curves exhibited satisfactory concordance be-tween the observed and predicted data.The DCA results showed that the model could provide standardized net benefits compared to other variables considered in the study.Conclusion The Nomogram model constructed in this study based on smoking,diabetes mellitus,hy-poproteinemia,long-term use of glucocorticoids,endotracheal intubation,TNF-ɑ,IL-6,and FEV1/FVC can effectively guide and pro-vide targeted preventive measures for patients with COPD-complicated lung infections,potentially reducing the incidence of such infec-tions and serving as a clinical reference.
chronic obstructive pulmonary diseasePulmonary infectionRisk factorsNomogram prediction model
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