ArticleNature and science of sleep2023
A Prediction Nomogram for Severe Obstructive Sleep Apnea in Snoring Patients: A Retrospective Study.
Article in Nature and science of sleep, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Development and Validation of Prediction Models for Severe Obstructive Sleep Apnea Based on Periodic Health Examinations.The clinical respiratory journal · 2026Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Snoring patients, as a high-risk group for OSA, are prone to the combination of severe OSA and face serious health threats. The aim of our study was to develop and validate a nomogram to predict the occurrence of severe OSA in snorers, in order to improve the diagnosis rate and treatment rate in this population. Patients and Methods: A training cohort of 464 snoring patients treated at our institution from May 2021 to October 2022 was divided into severe OSA and non-severe OSA groups. Univariate and multivariate logistic regression were used to identify potential predictors of severe OSA, and a nomogram model was constructed. An external hospital cohort of 210 patients was utilized as an external validation cohort to test the model. Area under the receiver operating characteristic curve, calibration curve, and decision curve analyses were used to assess the discriminatory power, calibration, and clinical utility of the nomogram, respectively. Results: Multivariate logistic regression demonstrated that body mass index, Epworth Sleepiness Scale total score, smoking history, morning dry mouth, dream recall, and hypertension were independent predictors of severe OSA. The area under the curve (AUC) of the nomogram constructed from the above six factors is 0.820 (95% CI: 0.782-0.857). The Hosmer-Lemeshow test showed that the model had a good fit ( Conclusion: A nomogram predicting the occurrence of severe OSA in snoring patients was constructed and validated with external data for the first time, and the findings all confirmed the validity of the model. This may help to improve existing clinical decision making, especially at institutions that do not yet have devices for diagnosing OSA.
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