ArticleNature and science of sleep2022
Development and Validation of a Nomogram for Predicting Obstructive Sleep Apnea in Patients with Pulmonary Arterial Hypertension.
Article in Nature and science of sleep, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05595200 (Prevalence, Phenotypes, Predictors and Prognostic Implication of Obstructive Sleep Apnea in Pulmonary Hypertension), which is not on this map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Prevalence, Phenotypes, Predictors and Prognostic Implication of Obstructive Sleep Apnea in Pulmonary Hypertension
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Clinical prediction models for the early diagnosis of obstructive sleep apnea in stroke patients: a systematic review.Systematic reviews · 2024Pooled it
- TRPC Channels as Mediators of Hypoxia-Induced Pulmonary Hypertension in Obstructive Sleep Apnea.International journal of molecular sciences · 2026Review
- Interpretable Machine Learning Model for Pulmonary Hypertension Risk Prediction: Retrospective Cohort Study.JMIR medical informatics · 2025Article
- Further insights into influence factors of hypertension in older patients with obstructive sleep apnea syndrome: a model based on multiple centers.Aging clinical and experimental research · 2025Article
- A Machine Learning Prediction Model of Adult Obstructive Sleep Apnea Based on Systematically Evaluated Common Clinical Biochemical Indicators.Nature and science of sleep · 2024Article
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Patients with pulmonary arterial hypertension (PAH) are at high risk for obstructive sleep apnea (OSA), which may adversely affect pulmonary hemodynamics and long-term prognosis. However, there is no clinical prediction model to evaluate the probability of OSA among patients with PAH. Our study aimed to develop and validate a nomogram for predicting OSA in the setting of PAH. Patients and Methods: From May 2020 to November 2021, we retrospectively analyzed the medical records of 258 patients diagnosed with PAH via right-heart catheterization. All participants underwent overnight cardiorespiratory polygraphy for OSA assessment. General clinical materials and biochemical measurements were collected and compared between PAH patients with or without OSA. Lasso regression was performed to screen potential predictors. Multivariable logistic regression analysis was conducted to establish the nomogram. Concordance index, calibration curve, and decision curve analysis were used to determine the discrimination, calibration, and clinical usefulness of the nomogram. Results: OSA was present in 26.7% of the PAH patients, and the prevalence did not differ significantly between male (29.7%) and female (24.3%) patients. Six variables were selected to construct the nomogram, including age, body mass index, hypertension, uric acid, glycated hemoglobin, and interleukin-6 levels. Based on receiver operating characteristic analysis, the nomogram demonstrated favorable discrimination accuracy with an area under the curve (AUC) of 0.760 for predicting OSA, exhibiting a better predictive value in contrast to ESS (AUC = 0.528) ( Conclusion: By establishing a comprehensive and practical nomogram, we were able to predict the presence of OSA in patients with PAH, which may facilitate the early identification of patients that benefit from further diagnostic confirmation and intervention.
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