Associations between perioperative sleep patterns and clinical outcomes in patients with intracranial tumors: a correlation study

Abstract

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.

Methods: A correlation study was conducted in patients with intracranial tumors. Perioperative sleep patterns were assessed using a dedicated sleep monitor for 6 consecutive days. Clinical outcomes were gained through medical records and follow-up. Spearman's 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 men, 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 post-operative nausea and vomiting was 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 was 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 post-operative 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) and negatively related to perioperative deep sleep time (β = -0.079; 95% CI = -0.122-0.035; P < 0.001).

Conclusion: 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.

Clinical trial registration: http://www.chictr.org.cn, identifier: ChiCTR2200059425.

Keywords: clinical outcomes; deep sleep; intracranial tumors; perioperative sleep patterns; sleep disorders.