Establishment and Validation of a Predictive Model in Female Patients with Obstructive Sleep Apnea.

Wenxuan Yu, Shuwen Yang, Qinhan Wu, Shanqun Li, Huai Huang, Xiaodan Wu

Abstract read

In one paragraph

Article in Women's health reports (New Rochelle, N.Y.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Wenxuan YuDepartment of Respiratory and Critical Care, Zhongshan Hospital affiliated to Fudan University, Shanghai, China.

Shuwen YangDepartment of Respiratory and Critical Care, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen, China.

Qinhan WuDepartment of Respiratory and Critical Care, Zhongshan Hospital affiliated to Fudan University, Shanghai, China.

Shanqun LiDepartment of Respiratory and Critical Care, Zhongshan Hospital affiliated to Fudan University, Shanghai, China.

Huai HuangDepartment of Respiratory and Critical Care, Zhongshan Hospital affiliated to Fudan University, Shanghai, China.

Xiaodan WuDepartment of Respiratory and Critical Care, Zhongshan Hospital affiliated to Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To develop a noninvasive clinical diagnostic model based on clinical markers for obstructive sleep apnea (OSA) and to verify its predictive efficacy. Methods: A retrospective analysis was conducted on female patients who underwent diagnostic sleep monitoring and had complete medical records from January 2021 to April 2023 at Zhongshan Hospital affiliated with Fudan University. The risk factors were analyzed using LASSO regression and multivariate Logistic regression to construct a nomogram predictive model and evaluate its performance. Finally, the predictive efficacy of the constructed model was compared with that of the STOP-Bang score. Result: A total of 317 female patients were enrolled. Logistic regression analysis revealed that age (OR = 1.045, 95% CI: 1.02-1.072, Conclusions: The nomogram predictive model demonstrates good accuracy, consistency, and clinical utility. It aids doctors in the early identification of high-risk female patients with OSA in clinical practice, enabling timely preventive and interventional measures.

Indexed as

femalenomogramobstructive sleep apneapredictive model

Identifiers

PMID41142486

DOI10.1177/26884844251380142

PMCPMC12547395

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.