Association and prediction of subjective sleep quality and postoperative delirium during major non-cardiac surgery: a prospective observational study.

BACKGROUND

Postoperative delirium (POD) is an acute form of brain dysfunction that can result in serious adverse consequences. There has been a link between cognitive dysfunction and poor sleep. The present study aimed to determine the association and prediction of subjective sleep quality and postoperative delirium during major non-cardiac surgery.

METHODS

One hundred and thirty-four patients, aged 60 years or older, were scheduled for elective laparotomy or orthopaedic procedures. The Pittsburgh Sleep Quality Index (PSQI) and sleep log were used to assess perioperative subjective sleep quality in participants. Nursing Delirium Screening Checklist (NU-DESC) was used for screening, and the Confusion Assessment Method (CAM) was used to diagnose POD during the first seven days following surgery. The association between subjective sleep quality and POD was assessed using a multivariate logistic regression model. Thereafter, the prediction performance of subjective sleep quality was evaluated using a receiver operating characteristic (ROC) curve.

RESULTS

All assessments were completed on 119 patients who had an average PSQI score of 7.0 ± 2.4 before surgery. 23 patients (19.3%) suffered from POD. The multivariate logistic regression analysis showed that the occurrence of POD was closely related to age, BMI, PSQI and operation time. After adjusting for related factors, there was a statistically significant association between PSQI and POD occurrence (OR = 1.422, 95%CI 1.079-1.873, per 1-point increase in PSQI). The ROC curve analysis showed that the optimal PSQI cutoff value was 8.0 for predicting POD, and the area under the ROC (AUROC) value of PSQI was 0.741 (95%CI 0.635 to 0.817). The AUROC of the model developed by the multivariate logistic regression analysis was 0.870 (95%CI 0.797 to 0.925).

CONCLUSIONS

The study found that preoperative subjective sleep quality was strongly associated with POD during major non-cardiac surgery. Additionally, PSQI combined with age, BMI, and operation time improved POD prediction.