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PURPOSE: To investigate the impact of obstructive sleep apnea (OSA) on postoperative delirium (PD), and evaluate the effectiveness of positive airway pressure (PAP) therapy on PD among OSA patients. METHODS: We systematically searched Embase, Cochrane Library and PubMed databases from their establishment to November 27, 2022. A random-effects approach was employed to determine aggregated results. Subgroup and sensitivity analyses were carried out to investigate heterogeneity. RESULTS: Sixteen eligible studies were included in the analysis. Thirteen studies revealed that OSA significantly elevated the likelihood of developing PD (OR = 1.71; 95%CI = 1.17 to 2.49; p = 0.005). Subgroup analysis according to delirium assessment scales showed that OSA did not exhibit an association with the incidence of PD assessed by the Confusion Assessment Method-Intensive Care Unit (OR = 1.14; 95%CI = 0.77 to 1.67; p = 0.51) but enhanced the likelihood of developing PD evaluated with other measurement scales (OR = 2.15; 95%CI = 1.44 to 3.19; p = 0.0002). Three additional studies explored the impact of PAP treatment on PD among OSA individuals, indicating no significant reduction in PD incidence with PAP use (OR = 0.58; 95%CI = 0.13 to 2.47; p = 0.46). CONCLUSIONS: OSA may not be a risk factor for PD in critically ill patients in the intensive care unit, but may increase the likelihood of developing PD among individuals receiving regular care in the ward postoperatively. The efficacy of PAP therapy in decreasing PD incidence among OSA patients remains debatable.
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BACKGROUND: Severe community-acquired pneumonia is one of the most lethal forms of CAP with high mortality. For rapid and accurate decisions, we developed a mortality prediction model specifically tailored for elderly SCAP patients. METHODS: The retrospective study included 2365 elderly patients. To construct and validate the nomogram, we randomly divided the patients into training and testing cohorts in a 70% versus 30% ratio. The primary outcome was in-hospital mortality. Univariate and multivariate logistic regression analyses were used in the training cohort to identify independent risk factors. The robustness of this model was assessed using the C index, ROC and AUC. DCA was employed to evaluate the predictive accuracy of the model. RESULTS: Six factors were used as independent risk factors for in-hospital mortality to construct the prediction model, including age, the use of vasopressor, chronic renal disease, neutrophil, platelet, and BUN. The C index was 0.743 (95% CI 0.719-0.768) in the training cohort and 0.731 (95% CI 0.694-0.768) in the testing cohort. The ROC curves and AUC for the training cohort and testing cohort (AUC = 0.742 vs. 0.728) indicated a robust discrimination. And the calibration plots showed a consistency between the prediction model probabilities and observed probabilities. Then, the DCA demonstrated great clinical practicality. CONCLUSIONS: The nomogram incorporated six risk factors, including age, the use of vasopressor, chronic renal disease, neutrophil, platelet and BUN, which had great predictive accuracy and robustness, while also demonstrating clinical practicality at ICU admission.