What question did this study set out to answer?

The study seeks to identify risk factors linked to early renal impairment in OSAHS and create a predictive model for patient risk assessment.

May 15, 2026Open Access

Identification of risk factors and development of a predictive model for early renal impairment in patients with obstructive sleep apnea-hypopnea syndrome

XCXiao-Zhong CaiSoochow University SXShenjie XuSoochow University JCJie-Rui CaiSoochow University

Key Points

The study seeks to identify risk factors linked to early renal impairment in OSAHS and create a predictive model for patient risk assessment.
Retrospective cross-sectional study involving 259 patients with OSAHS confirmed by polysomnography.
Patients were classified based on urine albumin-to-creatinine ratio and estimated glomerular filtration rate.
Univariate and multivariate logistic regression analyses were utilized to pinpoint independent predictors.
Elevated body mass index, hypertension, diabetes mellitus, and increased hypoxemia were identified as independent risk factors for early renal impairment.
The predictive nomogram had a good discriminatory capacity with an area under the ROC curve of 0.796.
DCA indicated clinical utility for the nomogram within a predicted probability range of 0.2–0.8.

Abstract

This study aims to identify independent risk factors associated with early renal impairment in patients with obstructive sleep apnea–hypopnea syndrome (OSAHS) and to develop a predictive model for individualized risk stratification. This retrospective cross-sectional study included 259 patients with a confirmed diagnosis of OSAHS based on overnight polysomnography (PSG). Participants were classified into two groups based on urine albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR): a normal renal function group (n = 173) and an early renal impairment group (n = 86). Data on demographic variables, clinical comorbidities, PSG-derived indices, and laboratory parameters were collected. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of early renal impairment. A nomogram was subsequently developed, with its performance assessed using receiver operating characteristic (ROC) curve analysis, the Hosmer–Lemeshow goodness-of-fit test, decision curve analysis (DCA), and bootstrap internal validation. Multivariate analysis identified elevated body mass index, presence of hypertension and diabetes mellitus, increased cumulative time with oxygen saturation below 90%, higher levels of high-sensitivity C-reactive protein, and elevated serum cystatin C as independent risk factors for early renal impairment. Conversely, higher minimum nocturnal oxygen saturation was identified as a protective factor. The constructed nomogram demonstrated good discriminatory capacity (area under the ROC curve = 0.796) and calibration (Hosmer–Lemeshow test, p = 0.231). DCA supported its clinical utility within a predicted probability range of 0.2–0.8. Early renal impairment in patients with OSAHS is significantly associated with obesity, cardiometabolic comorbidities, hypoxemia-related burden, and systemic inflammation. The developed nomogram showed acceptable discrimination and calibration and may serve as a preliminary tool for individualized risk stratification in patients with OSAHS.

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