Evidence map›Paper›PMID 31737301›Full record

ArticleJournal of thoracic disease2019

The No-apnea score

Riken Chen, Wang Liu, Junfen Cheng, Zhenzhen Zheng, Manqing Ba, Min Peng, Qizhong He, Huajing Yang, Tao Chen, Cheng Hong

Open access · diamondAbstract read
In one paragraph

Article in Journal of thoracic disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 3 pooled it
0.4field-weighted citation impact, top 35% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 3 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Validation of the STOP questionnaire as a screening tool for OSA among different populations: a systematic review and meta-regression analysis.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2022
    Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 6 institutions in 2 countries.

Riken ChenDepartment of Respiratory Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang 524023, China.
Wang LiuDepartment of Respiratory Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang 524023, China.
Junfen ChengDepartment of Respiratory Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang 524023, China.
Zhenzhen ZhengDepartment of Respiratory Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang 524023, China.
Manqing BaDepartment of Biochemistry and Chemistry, The University of Arizona, Tucson, AR, USA.
Min PengDepartment of Respiratory Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang 524023, China.
Qizhong HeDepartment of Respiratory Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang 524023, China.
Huajing YangDepartment of Respiratory Medicine, State Key Laboratory of Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, Guangzhou 510120, China.
Tao ChenDepartment of Respiratory Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang 524023, China.
Cheng HongDepartment of Respiratory Medicine, State Key Laboratory of Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, Guangzhou 510120, China.
Second Affiliated Hospital of Guangzhou Medical University · CNGuangdong Medical College · CNFirst Affiliated Hospital of Guangzhou Medical University · CNGuangzhou Medical University · CNState Key Laboratory of Respiratory Disease · CNUniversity of Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGiven the growing number of patients suspected of having obstructive sleep apnea-hypopnea syndrome (OSAHS), screening methods have become increasingly important for sleep clinics. We analyzed the clinical value of the No-apnea score which is used to diagnose OSAHS in patients with cerebral infarction, and compared the accuracy of the No-apnea score with the accuracy of the NoSAS score, the STOP-Bang questionnaire (SBQ), the Epworth Sleepiness Scale (ESS), the STOP questionnaire (STOP) and the Berlin questionnaire (BQ).

methodsBetween January 2014 and December 2018, a total of 221 cerebral infarction patients, suspected of having OSAHS, underwent the polysomnography (PSG) for one night at the sleep medical center of Guangdong Medical University Affiliated Second Hospital. The PSG data were collected and analyzed with the NoSAS score, the SBQ, the ESS, the STOP, the BQ, and patients' demographic information. Based on the apnea-hypopnea index (AHI), the patients were classified into four groups: the normal group (<5 events/h), mild OSAHS group (5-15 events/h), moderate OSAHS group (15-30 events/h) and severe OSAHS group (≥30 events/h). The sensitivity, specificity, positive predictive value, negative predictive value and areas under the curve (AUC) of the Receiver Operating Curve (ROC) were calculated for the five questionnaires to compare their relative efficacies for diagnosing OSAHS.

resultsWhen using the standard of AHI ≥5 for diagnosing OSAHS, the NoSAS score had an AUC of 0.831; the SBQ had an AUC of 0.730; the BQ had an AUC of 0.698; and the STOP had an AUC of 0.735, so these techniques are relatively accurate in diagnosing OSAHS. On the other hand, the No-apnea score and the ESS score are relatively less accurate comparing to the rest: the No-apnea had an AUC of 0.626, and the ESS had an AUC of 0.650. Using the NoSAS score to predict AHI ≥5 events/h, AHI ≥15 events/h and AHI ≥30 events/h, the sensitivity and specificity were 0.867 and 0.731, 0.888 and 0.476, 0.889 and 0.369, respectively; Using the SBQ to predict AHI ≥5 events/h, AHI 15 events/h and AHI ≥30 events/h, the sensitivity and specificity were 0.903 and 0.268, 0.914 and 0.200, 0.903 and 0.268, respectively; Using the STOP to predict AHI ≥5 events/h, AHI ≥15 events/h and AHI ≥30 events/h, the values were 0.830 and 0.500, 0.871 and 0.390, 0.875 and 0.302, respectively; and using the BQ to predict AHI ≥5 events/h, AHI ≥15 events/h and AHI ≥30 events/h, the values were 0.758 and 0.482, 0.810 and 0.429, 0.819 and 0.362, respectively.

conclusionsThe study concludes that the NoSAS score and the SBQ had a better predictive value for cerebral infarction patients suspected with OSAHS disease. These questionnaires can also effectively help clinicians quickly address nocturnal hypoxia in patients with cerebral infarction to control subsequent complications in patients with cerebral infarction. More studies are needed to evaluate the efficacy of the NoSAS score in screening for OSAHS in patients with cerebral infarction.

Indexed as

cerebral infarctiondiagnosingNoSAS scoreobstructive sleep apnea-hypopnea syndrome (OSAHS)

Identifiers

PMID31737301
PMCPMC6837961
OpenAlexW2982294814

What OpenQuestion holds

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Registered trials

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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.