Profiling symptom burden and its influencing factors at discharge for patients undergoing lung cancer surgery: a cross-sectional analysis

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Abstract

Background: Following lung cancer surgery, patients often experience severe symptoms which are not properly assessed at discharge. The aim of this study was to identify the clinical presentation at discharge and the influencing factors of postoperative symptoms in patients who have undergone lung cancer surgery. Methods: This cross-sectional study analysed data from patients who participated in a prospective cohort study that enrolled patients who underwent lung cancer surgery at six tertiary hospitals in the People’s Republic of China, from November 2017 to January 2020. Patient symptoms at discharge were measured using the MD Anderson Symptom Inventory Lung Cancer module. The five core symptoms were defined according to ratings of moderate to severe symptoms (≥ 4 on a 0–10 scale). A multivariate linear regression model was used to identify the influencing factors of each symptom at discharge. Results: Among the 366 participants, 51.9% were male and the mean (SD) age was 55.81 (10.43) years. At discharge, the core symptoms were cough (36.4%), pain (28.2%), disturbed sleep (26.3%), shortness of breath (25.8%), and fatigue (24.3%), and more than half of the participants (54.6%) had one to five of the core symptoms, with moderate to severe severity. A low annual income and the use of two chest tubes were significantly associated (P = 0.030 and 0.014, respectively) with higher mean scores of the core symptoms. Conclusion: Though clinically eligible for discharge, more than half of the participants had severe symptoms at discharge after lung cancer surgery. Special attention should be given to patients who have two chest tubes after surgery and those who have a low annual income.

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Liao, J., Wang, Y., Dai, W., Wei, X., Yu, H., Yang, P., … Shi, Q. (2022). Profiling symptom burden and its influencing factors at discharge for patients undergoing lung cancer surgery: a cross-sectional analysis. Journal of Cardiothoracic Surgery, 17(1). https://doi.org/10.1186/s13019-022-01974-9

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