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Background: Sleep disturbances in the peri-operative period have been associated with adverse outcomes, including postoperative delirium (POD). However, research on sleep quality during the immediate postoperative period is limited., Objectives: This study aimed to investigate the association between sleep quality on the night of the operative day assessed using the Sleep Quality Numeric Rating Scale (SQ-NRS), and the incidence of POD in a large cohort of surgical patients., Design: A prospective cohort study., Setting: A tertiary hospital in China., Patients: This study enrolled patients aged 65 years or older undergoing elective surgery under general anaesthesia. The participants were categorised into the sleep disturbance and no sleep disturbance groups according to their operative night SQ-NRS., Main Outcome Measures: The primary outcome was delirium incidence, whereas the secondary outcomes included acute kidney injury, stroke, pulmonary infection, cardiovascular complications and all-cause mortality within 1 year postoperatively., Results: In total, 3072 patients were included in the analysis of this study. Among them, 791 (25.72%) experienced sleep disturbances on the night of operative day. Patients in the sleep disturbance group had a significantly higher risk of developing POD (adjusted OR 1.43, 95% CI 1.11 to 1.82, P  = 0.005). Subgroup analysis revealed that age 65-75 years; male sex; ASA III and IV; haemoglobin more than 12 g l -1 ; intra-operative hypotension; surgical duration more than 120 min; and education 9 years or less were significantly associated with POD. No interaction was observed between the subgroups. No significant differences were observed in the secondary outcomes, such as acute kidney injury, stroke, pulmonary infection, cardiovascular complications and all-cause mortality within 1 year postoperatively., Conclusions: The poor subjective sleep quality on the night of operative day was independently associated with increased POD risk, especially in certain subpopulations. Optimising peri-operative sleep may reduce POD. Further research should investigate potential mechanisms and causal relationships., Trial Registry: chictr.org.cn: ChiCTR1900028545., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the European Society of Anaesthesiology and Intensive Care.)

Aims: To compare the performance of logistic regression and machine learning methods in predicting postoperative delirium (POD) in elderly patients. Method: This was a retrospective study of perioperative medical data from patients undergoing non‐cardiac and non‐neurology surgery over 65 years old from January 2014 to August 2019. Forty‐six perioperative variables were used to predict POD. A traditional logistic regression and five machine learning models (Random Forest, GBM, AdaBoost, XGBoost, and a stacking ensemble model) were compared by the area under the receiver operating characteristic curve (AUC‐ROC), sensitivity, specificity, and precision. Results: In total, 29,756 patients were enrolled, and the incidence of POD was 3.22% after variable screening. AUCs were 0.783 (0.765–0.8) for the logistic regression method, 0.78 for random forest, 0.76 for GBM, 0.74 for AdaBoost, 0.73 for XGBoost, and 0.77 for the stacking ensemble model. The respective sensitivities for the 6 aforementioned models were 74.2%, 72.2%, 76.8%, 63.6%, 71.6%, and 67.4%. The respective specificities for the 6 aforementioned models were 70.7%, 99.8%, 96.5%, 98.8%, 96.5%, and 96.1%. The respective precision values for the 6 aforementioned models were 7.8%, 52.3%, 55.6%, 57%, 54.5%, and 56.4%. Conclusions: The optimal application of the logistic regression model could provide quick and convenient POD risk identification to help improve the perioperative management of surgical patients because of its better sensitivity, fewer variables, and easier interpretability than the machine learning model. [ABSTRACT FROM AUTHOR]

Prognostic nutritional index (PNI) is an indicator to evaluate the nutritional immune status of patients. This study aimed to assess whether preoperative PNI could predict the occurrence of postoperative POD in aged patients undergoing non-neurosurgery and non-cardiac surgery. The aged patients undergoing non-neurosurgery and non-cardiac surgery between January 2014 and August 2019 were included in the retrospective cohort study. The correlation between POD and PNI was investigated by univariate and multivariable logistic regression analysis, propensity score matching (PSM), inverse probability of treatment weighting (IPTW), and subgroup analysis. In the cohort (n = 29,814), the cutoff value of PNI was 46.01 determined by the receiver operating characteristic (ROC) curve. In univariate and three multivariable regression analysis, the ORs of PNI ≤ 46.01 was 2.573(95% CI:2.261–2.929, P < 0.001),1.802 (95% CI:1.567-2.071, P < 0.001),1.463(95% CI:1.246–1.718, P < 0.001),1.370(95% CI:1.165–1.611, P < 0.001). In the PSM model and IPTW model, the ORs of PNI ≤ 46.01 were 1.424(95% CI:1.172–1.734, P < 0.001) and 1.356(95% CI:1.223–1.505, P < 0.001). The PNI was found to have a predictive value for POD in patients undergoing non-neurosurgery and non-cardiac surgery. Improving preoperative nutritional status may be beneficial in preventing POD for aged patients. [ABSTRACT FROM AUTHOR]