Evidence map›Paper›PMID 34785967›Full record

ArticleNature and science of sleep2021

Simple and Unbiased OSA Prescreening: Introduction of a New Morphologic OSA Prediction Score.

Naima Laharnar, Sebastian Herberger, Lisa-Kristin Prochnow, Ning-Hung Chen, Peter A Cistulli, Allan I Pack, Richard Schwab, Brendan T Keenan, Diego R Mazzotti, Ingo Fietze and 1 more

Open access · goldAbstract read
In one paragraph

Article in Nature and science of sleep, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

9 citing papers in PubMed, 13 citations in OpenAlex.

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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

11 authors at 7 institutions in 5 countries.

Naima Laharnar *Department of Internal Medicine and Dermatology, Interdisciplinary Center of Sleep Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.ORCID 0000-0001-7484-7747
Sebastian Herberger *Department of Internal Medicine and Dermatology, Interdisciplinary Center of Sleep Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Lisa-Kristin ProchnowDepartment of Internal Medicine and Dermatology, Interdisciplinary Center of Sleep Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Ning-Hung ChenDepartment of Pulmonary and Critical Care Medicine, Sleep Center, Chang Gung Memorial Hospital, Taipei, Taiwan.ORCID 0000-0002-8387-9318
Peter A CistulliCharles Perkins Centre, University of Sydney, Sydney, NSW, Australia.
Allan I PackDepartment of Medicine/Division of Sleep Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Richard SchwabDepartment of Medicine/Division of Sleep Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Brendan T KeenanDepartment of Medicine/Division of Sleep Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Diego R MazzottiDepartment of Medicine/Division of Sleep Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Ingo FietzeDepartment of Internal Medicine and Dermatology, Interdisciplinary Center of Sleep Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Thomas PenzelDepartment of Internal Medicine and Dermatology, Interdisciplinary Center of Sleep Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.ORCID 0000-0002-4304-0112
Charité - Universitätsmedizin Berlin · DEUniversity of Pennsylvania · USChang Gung Memorial Hospital · TWSaratov State University · RUSechenov University · RUThe University of Sydney · AUUniversity of Kansas Medical Center · US

Funding

Understanding the relationship between obesity and tongue fat in humans and ratsP01HL094307 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI PACK, ALLAN I · 2009 to 2020
$23.7M
NHLBI NIH HHS P01 HL094307
6 · The paper itself

Abstract

purposeAn early prescreening in suspected obstructive sleep apnea (OSA) patients is desirable to expedite diagnosis and treatment. However, the accuracy and applicability of current prescreening tools is insufficient. We developed and tested an unbiased scoring system based solely on objective variables, which focuses on the diagnosis of severe OSA and exclusion of OSA. PATIENTS AND

methodsThe OSA prediction score was developed (n = 150) and validated (n = 50) within German sleep center patients that were recruited as part of the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Six objective variables that were easy to assess and highly correlated with the apnea-hypopnea index were chosen for the score, including some known OSA risk factors: body-mass index, neck circumference, waist circumference, tongue position, male gender, and age (for women only). To test the predictive ability of the score and identify score thresholds, the receiver-operating characteristics (ROC) and curve were calculated.

resultsA score ≥8 for predicting severe OSA resulted in an area under the ROC curve (ROC-AUC) of 90% (95% confidence interval: 84%, 95%), test accuracy of 82% (75%, 88%), sensitivity of 82% (65%, 93%), specificity of 82% (74%, 88%), and positive likelihood ratio of 4.55 (3.00, 6.90). A score ≤5 for predicting the absence of OSA resulted in a ROC-AUC of 89% (83%, 94%), test accuracy of 80% (73%, 86%), sensitivity of 72% (55%, 85%), specificity of 83% (75%, 89%), and positive likelihood ratio of 4.20 (2.66, 6.61). Performance characteristics were comparable in the small validation sample.

conclusionWe introduced a novel prescreening tool combining easily obtainable objective measures with predictive power and high general applicability. The proposed tool successfully predicted severe OSA (important due to its high risk of cardiovascular disease) and the exclusion of OSA (rarely a feature of previous screening instruments, but important for better differential diagnosis and treatment).

Indexed as

diagnosticobstructive sleep apneascreeningsensitivityspecificity

Identifiers

PMID34785967
PMCPMC8590840
OpenAlexW3213234653

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

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.