The Impact of Obstructive Sleep Apnea on Early Depression in Patients with Acute Ischemic Stroke and Construction of a Nomogram Prediction Model

Purpose: To investigate the impact of obstructive sleep apnea (OSA) on depression inacute ischemic stroke (AIS) patients within 14 days post-stroke, and to develop and validate a nomogram for predicting early post-stroke depression (PSD) risk. Methods: This retrospective cohort study enrolled AIS patients admitted to Hefei Second People's Hospital. Depression was assessed using the Patient Health Questionnaire-9 (PHQ-9; cutoff ≥5). Demographic, clinical vascular risk factors, insomnia, uric acid（UA）, and apnea-hypopnea index（AHI）were collected. Multivariable logistic regression identified independent predictors of early PSD. A nomogram incorporating significant predictors was developed and internally validated using bootstrap resampling (1,000 repetitions). Model performance was evaluated by C-statistic and calibration curves. Clinical utility was assessed via decision curve analysis. Results: Among 138 AIS patients (median AHI: 18.15 events/h [IQR:11.70–28.82]), moderate-to-severe OSA (AHI≥15) prevalence was 60.1% (83/138), and early PSD incidence was 50.7% (70/138). Regression analysis revealed: 1. Continuous AHI model: Insomnia (OR=6.507, 95% CI:2.931–14.447; P<0.001), uric acid（UA）(OR=1.006, 95% CI:1.001–1.011; P=0.027), and AHI (OR=1.039, 95% CI:1.007–1.072; P=0.016) independently predicted PSD. 2. Categorical AHI model: Moderate-to-severe OSA (OR=2.248, 95% CI:1.006–5.023; P=0.048), insomnia (OR=5.825, 95% CI:2.672–12.702; P<0.001), and uric acid (OR=1.006, 95% CI:1.001–1.011; P=0.013) were significant predictors. The nomogram demonstrated good discrimination (C-statistic=0.784, 95% CI:0.704–0.863) and calibration. Decision curve analysis confirmed clinical utility across threshold probabilities. Conclusion: Insomnia, UA, and AHI are independent risk factors for early depression in AIS patients, while moderate to severe OSA further increases this risk. The nomogram constructed based on the above factors shows good predictive efficacy for early depression in AIS patients.