Risk factors and prediction model for sleep disorders in respiratory critically ill patients after intensive care...

To investigate the risk factors for sleep disorders in respiratory critically ill patients after ICU transfer to general wards and to construct a reliable predictive model for early identification of high-risk patients and guide targeted interventions.

This retrospective observational study included 102 patients with respiratory failure, multiple organ dysfunction, or severe pneumonia treated at a tertiary hospital between June 2022 and June 2025. Sleep disorders were assessed using the Pittsburgh Sleep Quality Index (PSQI; scores >7 as the cutoff) within one month after ICU transfer. Risk factors were screened using Lasso regression and multivariable logistic regression. A nomogram prediction model was constructed and validated through receiver operating characteristic (ROC) curve analysis, Hosmer-Lemeshow goodness-of-fit test, bootstrap validation (1000 resamples), and decision curve analysis (DCA) to assess clinical applicability.

Sleep disorders occurred in 37.3% (38/102) of patients. Four independent risk factors were identified: tracheotomy (OR=4.65, 95% CI: 1.11-19.51, P=0.036), sepsis (OR=4.26, 95% CI: 1.32-13.72, P=0.015), prolonged ICU stay (OR=1.72, 95% CI: 1.09-2.72, P=0.020), and increased APACHE II score (OR=1.20, 95% CI: 1.04-1.39, P=0.013). The nomogram demonstrated favorable discrimination (AUC=0.80, 95% CI: 0.71-0.89) and calibration (Hosmer-Lemeshow P=0.065; bootstrap validation showed 79.4% of resampled datasets with good fit). At the optimal cutoff, sensitivity, specificity, and positive predictive value were 0.62, 0.84, and 0.87, respectively. DCA indicated a positive net benefit when the predicted risk threshold exceeded 10%.

Tracheotomy, sepsis, prolonged ICU stay, and higher APACHE II score at ICU discharge are independent risk factors for post-ICU sleep disorders. The validated nomogram provides a clinically applicable tool for early risk stratification, facilitating targeted preventive interventions to improve post-ICU recovery.