Risk factors and predictive model construction for acute respiratory distress syndrome/acute lung injury following lung resection

Background: To identify risk factors for acute respiratory distress syndrome (ARDS) and acute lung injury (ALI) after lung resection and develop an effective risk prediction model. Methods: A retrospective analysis was conducted on clinical data from patients who underwent lung resection between January 2021 and January 2024. Patients were categorized into two groups: ARDS/ALI (observation group) and non-ARDS/ALI (control group). General characteristics, lung function parameters, surgical indicators, and postoperative laboratory findings were compared between groups. Binary Logistic regression was used to determine independent risk factors for ARDS/ALI, and a prediction model was constructed based on these factors. Model performance was evaluated using the receiver operating characteristic (ROC) curve. Results: The observation group included older patients with a higher proportion of smoking index ≥400, elevated forced vital capacity (FVC), prolonged surgical duration and one-lung ventilation (OLV) time, higher one-lung airway pressure, and significantly increased postoperative interleukin-6 (IL-6) and white blood cell (WBC) levels (all p < 0.05). Multivariate logistic regression analysis identified OLV duration, one-lung airway pressure, postoperative IL-6, postoperative WBC, and age as independent risk factors for ARDS/ALI (all p < 0.05). The prediction model, based on these factors, exhibited excellent diagnostic performance with an area under the curve (AUC) of 0.967, sensitivity of 84.80%, and specificity of 97.30%. Conclusions: OLV duration, one-lung airway pressure, postoperative IL-6, postoperative WBC, and age are independent risk factors for ARDS/ALI following lung resection. The prediction model, constructed based on these factors, offers high diagnostic accuracy and provides valuable guidance for early identification and intervention of postoperative ARDS/ALI.

Lung resection; Acute respiratory distress syndrome; Acute lung injury; Risk factors; Prediction model

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