Evidence map›Paper›PMID 36223645›Full record

ArticleJournal of sleep research2023

Machine learning approach for obstructive sleep apnea screening using brain diffusion tensor imaging.

Bo Pang, Suraj Doshi, Bhaswati Roy, Milena Lai, Luke Ehlert, Ravi S Aysola, Daniel W Kang, Ariana Anderson, Shantanu H Joshi, Daniel Tward and 3 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of sleep research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.6field-weighted citation impact, top 9% 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, 24 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

13 authors at 1 institution in 1 country.

Bo PangDepartment of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, California, USA.
Suraj DoshiDepartment of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, California, USA.
Bhaswati RoyDepartment of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, California, USA.
Milena LaiDepartment of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, California, USA.
Luke EhlertDepartment of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, California, USA.
Ravi S AysolaDepartment of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Daniel W KangDepartment of Medicine, University of California Los Angeles, Los Angeles, California, USA.
Ariana AndersonDepartment of Statistics, University of California Los Angeles, Los Angeles, California, USA.
Shantanu H JoshiDepartment of Neurology, University of California Los Angeles, Los Angeles, California, USA.
Daniel TwardDepartment of Neurology, University of California Los Angeles, Los Angeles, California, USA.
Fabien ScalzoDepartment of Neurology, University of California Los Angeles, Los Angeles, California, USA.
Susana VacasDepartment of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, California, USA.
Rajesh KumarDepartment of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, California, USA.ORCID 0000-0001-5355-9586
University of California, Los Angeles · US

Funding

Blood-Brain Barrier Deficit and Brain Injury in Obstructive Sleep ApneaR01NR015038 · NINR · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KUMAR, RAJESH · 2015 to 2018
$2.0M
Mechanisms Mediating Postoperative Neurocognitive DisordersK23GM132795 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI VACAS, SUSANA · 2019 to 2023
$1.0M
Brain Changes in Pediatric Obstructive Sleep ApneaR21HD102544 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KUMAR, RAJESH · 2021 to 2022
$429k
NICHD NIH HHS R21 HD102544NICHD NIH HHS R21HD102544NIGMS NIH HHS K23 GM132795NIGMS NIH HHS K23GM132795NINR NIH HHS R01 NR-015038NINR NIH HHS R01 NR015038
6 · The paper itself

Abstract

Patients with obstructive sleep apnea (OSA) show autonomic, mood, cognitive, and breathing dysfunctions that are linked to increased morbidity and mortality, which can be improved with early screening and intervention. The gold standard and other available methods for OSA diagnosis are complex, require whole-night data, and have significant wait periods that potentially delay intervention. Our aim was to examine whether using faster and less complicated machine learning models, including support vector machine (SVM) and random forest (RF), with brain diffusion tensor imaging (DTI) data can classify OSA from healthy controls. We collected two DTI series from 59 patients with OSA [age: 50.2 ± 9.9 years; body mass index (BMI): 31.5 ± 5.6 kg/m

Indexed as

Diffusion Tensor ImagingSleep Apnea, ObstructiveAdultBody Mass IndexBrainFemaleHumansMachine LearningMiddle Agedbrainmean diffusivityrandom forestsleep disordered breathingsupport vector machine

Identifiers

PMID36223645
PMCPMC9851969
OpenAlexW4304807456

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.