Objective: To examine the association between length of stay (LOS) after lobectomy and operative adverse events and define the best predictors and risk factors associated with prolonged LOS after lobectomy.
Methods: Data from patients undergoing thoracoscopic lobectomy in the Thoracic Surgery Department of our center between January 2015 and December 2021 were retrospectively analyzed. The association between operative adverse events and LOS after lobectomy was explored using receiver operating characteristic (ROC) curves, and multivariate logistic regression analyses were used to identify preoperative risk factors associated with prolonged LOS after lobectomy.
Results: Prolonged LOS after lobectomy was defined as a LOS after lobectomy that is > 3.5 days based on an optimal diagnostic value for operative adverse events (AUC = 0.882). Of the included patients, 20.9% (91/435) exceeded this threshold, of whom 52.7% (48/91) exhibited operative adverse events. The preoperative risk factors associated with prolonged LOS after lobectomy were age≥60 years old (OR = 9.632, 95%CI 1.126-75.66, p = 0.03), being a current smoker (OR = 2.702, 95%CI 1.547-4.72, P < 0.001), an American Society of Anesthesiology (ASA) classification of 2 or higher (OR = 1.845, 95%CI 1.06-3.211, P = 0.03), ASA = 3 (OR = 9.133, 95%CI 3.281-25.425, P < 0.001), and Stage IIIA disease (OR = 6.565, 95%CI 2.823-15.271, P < 0.001). Prolonged LOS after lobectomy was significantly associated with the incidence of different operative adverse events, including conversion to thoracotomy, an operative duration of ≥300 min, blood transfusion events, chest tube drainage time, postoperative complications, and postoperative interventions (P < 0.001).
Conclusion: The risk of prolonged LOS after lobectomy is higher in patients that are ≥60 years old, current smokers, exhibit an ASA classification of 2 or higher, and have a stage IIIA disease. Early identification of these risk factors can enhance the treatment offered to high-risk patients, thereby reducing the rates of operative adverse events and optimizing resource utilization.
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| http://dx.doi.org/10.1016/j.heliyon.2023.e16061 | DOI Listing |
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