Associations between perioperative sleep patterns and clinical outcomes in patients with intracranial tumors: a correlation study - Liu, Yang; Wu, Fan; Zhang, Xiaoyu; Jiang, Mengyang; Zhang, Yiqiang; Wang, Chenhui; Sun, Yongxing; Wang, Baoguo (Frontiers in Neurology, 2023)
Objective: Although the quality of perioperative sleep is gaining increasing attention in clinical recovery, its impact role remains unknown and may deserve further exploration. This study aimed to investigate the associations between perioperative sleep patterns and clinical outcomes among patients with intracranial tumors.: A correlation study was conducted in patients with intracranial tumors. Perioperative sleep patterns were assessed by a dedicated sleep monitor for six consecutive days. Clinical outcomes were gained through medical records and follow-up. Spearman correlation coefficient and multiple linear regression analysis were applied to evaluate the associations between perioperative sleep patterns and clinical outcomes. Results: Of 110 patients, 48 (43.6%) were male, with a median age of 57 years. A total of 618 days of data on perioperative sleep patterns were collected and analyzed. Multiple linear regression models revealed that the preoperative blood glucose was positively related to the preoperative frequency of awakenings (β=0.125; 95% CI=0.029-0.221; P=0.011). The level of postoperative nausea and vomiting were negatively related to perioperative deep sleep time (β=-0.015; 95% CI=-0.027–0.003; P=0.015). The level of anxiety and depression were negatively related to perioperative deep sleep time, respectively (β=-0.048; 95% CI=-0.089–0.008; P=0.020, β=-0.041; 95% CI=-0.076–0.006; P=0.021). The comprehensive complication index was positively related to the perioperative frequency of awakenings (β=3.075; 95% CI=1.080-5.070; P=0.003). The postoperative length of stay was negatively related to perioperative deep sleep time (β=-0.067; 95% CI=-0.113–0.021; P=0.005). The Pittsburgh Sleep Quality Index was positively related to perioperative sleep onset latency (β=0.097; 95% CI=0.044-0.150; P<0.001), negatively related to perioperative deep sleep time (β=-0.079; 95% CI=-0.122–0.035; P<0.001). Conclusions: Perioperative sleep patterns are associated with different clinical outcomes. Poor perioperative sleep quality, especially reduced deep sleep time, has a negative impact on clinical outcomes. Clinicians should, therefore, pay more attention to sleep quality and improve it during the perioperative period.