ArticleSleep & breathing = Schlaf & Atmung2021
Demographic, clinical, and biomarker predictors of apnea-hypopnea index from polysomnography in Midwestern sleep clinic patients.
Article in Sleep & breathing = Schlaf & Atmung, 2021. 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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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.
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Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo examine if selected demographic (age, gender), clinical (diabetes, coronary artery disease, hyperlipidemia, myocardial infarction, stroke, lung disease, smoking history, alcohol intake), and biomarker [blood pressure (BP), heart rate, body mass index (BMI), neck circumference, Mallampati score] variables are predictors of apnea-hypopnea index (AHI) from polysomnography (PSG).
methodsThis cross-sectional study recruited a sample of adults (N = 170) who were being evaluated for OSA. Participants completed self-reported demographic and clinical questionnaires, and then completed PSG (n = 142). Multi-collinearity was assessed. Confounding factors, correlations, and potential interactions were explored.
resultsThe final regression model was performed on 130 participants; 61 (46.9%) had an AHI ≥ 15. Systolic and diastolic BPs were highly correlated. Interactions were tested between gender and other variables (high cholesterol, BMI, neck circumference, systolic BP) and between systolic BP and other variables (high cholesterol, BMI, neck circumference, and lung disease). No interactions occurred between gender or systolic BP and other variables, meaning that the effects of the variables on AHI levels from PSG did not vary depending on gender or systolic BP. BMI, systolic BP, and absence of lung disease were predictors for AHI levels ≥ 15 from PSG.
conclusionsBMI and systolic BP were significant predictors of OSA in this study. The absence of lung disease as a significant predictor was unique and may be due to the small number of participants who self-reported lung disease. To our knowledge, this is the first study to report this combination of variables to predict AHI levels ≥ 15 from PSG.
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