Post-Operative Poor Sleep Quality and Its Associated Factors Among Non-Small Cell Lung Cancer Patients: A Cross-Sectional Study

非小细胞肺癌患者术后睡眠质量差及其相关因素:一项横断面研究

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Abstract

OBJECTIVE: The study aimed to determine the post-operative prevalence and factors associated to poor sleep quality in non-small cell lung cancer (NSCLC) patients in China. METHODS: NSCLC patients (n=307) who underwent thoracoscopic surgery at the Department of Thoracic Surgery of Shanghai Pulmonary Hospital were enrolled in this study. The Pittsburgh Sleep Quality Index (PSQI), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), Prince Henry Hospital Pain Score and the Six-Minute Walk Test (6MWT), and Forced Expiratory Volume in one second (FEV-1) were used to assess the factors that could lead to poor sleep quality. All assessments were carried out between April 1 and May 30, 2023. Descriptive analyses and stepwise factor regression were employed to determine the impact of various factors on sleep quality. The factors predictive of poor sleep quality were used to develop a predictive nomogram. The Hosmer-Lemeshow test was used to assess the predictive value of the nomogram. RESULTS: The median PQSI score was 8 (interquartile range (IQR) 5-12), and 74.6% of patients had poor sleep quality. The median anxiety and depression scores were 6 (IQR 3-9) and 4 (IQR 2-7), respectively. The PSQI latency dimension had the highest score, while the use of sleep medications dimension had the lowest score. The multivariate analysis revealed that patients who were female (OR, 2.38; 95% CI, 1.40-4.05; P <0.01), had post-secondary education (OR, 0.42; 95% CI, 0.19-0.92; P =0.03), tertiary education (OR, 0.38; 95% CI, 0.17-0.84; P =0.02), comorbidities (OR, 2.57; 95% CI, 1.51-4.39; P <0.01), a pain score 1 (OR, 4.22; 95% CI, 2.37-7.50; P <0.01), and cough (OR, 2.97; 95% CI, 1.63-5.40; P <.001) were more like to experience poor sleep quality. The positive predictive value of the nomogram was 79.80% (p=0.390). CONCLUSION: Sociodemographic variables, comorbidities, and pain could be used to predict the post-operative sleep quality in NSCLC patients.

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