Evidence map›Paper›PMID 36071765›Full record

ArticleJournal of thoracic disease2022

An effective model for screening moderate-to-severe obstructive sleep apnea based on the STOP-BANG questionnaire.

Yuyu Wang, Juanjuan Zou, Huajun Xu, Cuiping Jiang, Hongliang Yi, Jian Guan, Shankai Yin

Abstract read
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Article in Journal of thoracic disease, 2022. 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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1 · What the graph read from it

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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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yuyu Wang *Department of Otolaryngology-Head and Neck Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Juanjuan Zou *Department of Otolaryngology-Head and Neck Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Huajun XuDepartment of Otolaryngology-Head and Neck Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Cuiping JiangDepartment of Endocrinology, Huadong Hospital Affiliated to Fudan University, Shanghai, China.
Hongliang YiDepartment of Otolaryngology-Head and Neck Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Jian GuanDepartment of Otolaryngology-Head and Neck Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Shankai YinDepartment of Otolaryngology-Head and Neck Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aimed to develop a more effective screening model for moderate-to-severe obstructive sleep apnea (OSA) based on the best tool among Epworth Sleepiness Scale (ESS), NoSAS score and STOP-BANG questionnaire (SBQ). Methods: This study screened 2,031 consecutive subjects referred with suspected OSA from 2012 to 2016, including the test cohort from 2012 to 2014 and the validation cohort from 2014 to 2016. Anthropometric measurements, polysomnographic data, ESS, NoSAS scores and SBQ scores were recorded. Receiver operating characteristic curve analyses were performed and the final predictive models were verified in a validation cohort. Results: A total of 1,840 adults were finally included. The performance of ESS, NoSAS score and SBQ in screening OSA was compared. The diagnostic accuracy of SBQ was superior to ESS and NoSAS. A predictive model based on SBQ yielded an area under the curve (AUC) of 0.931 (95% CI: 0.915-0.946), and the sensitivity and specificity were 84.47 (95% CI: 81.4-87.2) and 87.36 (95% CI: 83.9-90.3) respectively. In the validation cohort, the AUC was 0.955 (95% CI: 0.938-0.969), with a sensitivity and specificity of 86.79 (95% CI: 83.2-89.9) and 90.88 (95% CI: 87.2-93.8) respectively. In addition, the model performed moderately in screening mild OSA with the AUC being 0.771 (95% CI: 0.721-0.815). Conclusions: The SBQ was effective in screening moderate-to-severe OSA. And a SBQ -based predictive model afforded excellent diagnostic efficacy, which could be applied in clinical practice.

Indexed as

Obstructive sleep apnea (OSA)screening modelsensitivityspecificitySTOP-BANG questionnaire (SBQ)

Identifiers

PMID36071765
PMCPMC9442538

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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.