ArticleFrontiers in medicine2026
Analysis of influencing factors and construction of nomogram prediction model for pulmonary infection in patients with acute exacerbation of chronic obstructive pulmonary disease complicated with type II respiratory failure.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: To construct a risk prediction nomogram model for pulmonary infection in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) complicated with type II respiratory failure. Methods: A retrospective analysis was conducted on clinical data of 361 patients with AECOPD complicated with type II respiratory failure. Restricted cubic spline analysis was used to analyze the nonlinear relationships between some continuous variables and the outcome. Single factor and multiple factor logistic regression analyses were used to determine independent influencing factors, the predictive model was constructed and the nomogram was drawn. ROC curve, calibration curve, and clinical decision curve were plotted to evaluate the predictive performance of the model. Results: Age showed no significant nonlinear relationship with concurrent pulmonary infection (P for nonlinearity > 0.05), whereas length of hospital stay, APACHE II score, and duration of combined antibiotic use all showed significant nonlinear relationships with concurrent pulmonary infection (P for nonlinearity < 0.05). Age, diabetes, hospital stay > 15 days, APACHE II score > 15 points, antibiotics combination time > 14 days were independent risk factors for pulmonary infection, and albumin was an independent protective factor ( Conclusion: The nomogram risk model constructed in this study may demonstrate a certain predictive performance in predicting pulmonary infection in patients with AECOPD complicated with type II respiratory failure, and may provide a reference for early clinical identification and intervention.
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