Evidence map›Paper›PMID 40638677›Full record

ArticlePloS one2025

Weighted Hypoxemia Index: An adaptable method for quantifying hypoxemia severity.

Diane C Lim, Cheng-Bang Chen, Ankita Paul, Yujie Wang, Jinyoung Kim, Soonhyun Yook, Emily Y Kim, Edison Q Kim, Anup Das, Medhi Wangpaichitr and 5 more

Abstract read
In one paragraph

Article in PloS one, 2025. 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Diane C LimDepartment of Medicine, University of Miami, Miami, Florida, United States of America.ORCID https://orcid.org/0000-0001-5748-629X
Cheng-Bang ChenDepartment of Industrial and Systems Engineering, University of Miami, Coral Gables, Florida, United States of America.
Ankita PaulBioinformatics & Computational Biology, MD Anderson, Houston, Texas, United States of America.
Yujie WangDepartment of Industrial and Systems Engineering, University of Miami, Coral Gables, Florida, United States of America.
Jinyoung KimSchool of Nursing, University of Nevada, Las Vegas, Nevada, United States of America.
Soonhyun YookDepartment of Neurology, Stevens Neuroimaging and Informatics Institute, University of Southern California, Keck School of Medicine, Los Angeles, California, United States of America.ORCID https://orcid.org/0000-0002-1329-9051
Emily Y KimDepartment of Research, Miami VAHS, Miami, Florida, United States of America.
Edison Q KimDepartment of Research, Miami VAHS, Miami, Florida, United States of America.
Anup DasDepartment of ECE, Drexel University, Philadelphia, Pennsylvania, United States of America.
Medhi WangpaichitrDepartment of Research, Miami VAHS, Miami, Florida, United States of America.
Virend K SomersDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, United States of America.
Chi Hang LeeDepartment of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Phyllis C ZeeDepartment of Neurology, Northwestern University, Chicago, Illinois, United States of America.
Toshihiro ImamuraDepartment of Pediatrics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Hosung KimDepartment of Neurology, Stevens Neuroimaging and Informatics Institute, University of Southern California, Keck School of Medicine, Los Angeles, California, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo quantitate hypoxemia severity.

methodsWe developed the Weighted Hypoxemia Index to be adapted to different clinical settings by applying 5 steps to the oxygen saturation curve: (1) Identify desaturation/resaturation event [Formula: see text] by setting the upper threshold; (2) Exclude events as artifact by setting a lower threshold; (3) Calculate weighted area for each [Formula: see text] as [Formula: see text]; (4) Calculate a normalization factor [Formula: see text] for each subject; (5) Calculate the Weighted Hypoxemia Index as the summation of all weighted areas multiplied by [Formula: see text]. We assessed the Weighted Hypoxemia Index predictive value for all-cause mortality and cardiovascular mortality using the Sleep Heart Health Study (enrollment 1995-1998, 11.1 years mean follow-up).

resultsWe set varying upper thresholds at 92%, 90%, 88%, and 86%, a lower threshold of 50%, calculated area under the curve and area above the curve, with and without a linear weighted factor (duration of each event [Formula: see text]), and used the same normalization factor of total sleep time <90% divided by total sleep time. After excluding subjects with missing data, we analyzed 4,509 participants (Alive: N = 3,769; All-cause mortality: N = 1,071; cardiovascular mortality: N = 330). Since the Weighted Hypoxemia Index-Area Under the Curve set at upper threshold of 90% (WHI-AUC90) had the best results in predicting all-cause mortality, we then compared it to the Apnea-Hypopnea Index and Total Sleep Time <90%. WHI-AUC90 showed statistical significance across quintiles for all-cause mortality, but not cardiovascular mortality, in adjusted Cox regression models.

conclusionThe Weighted Hypoxemia Index offers a versatile and clinically relevant method for quantifying hypoxemia severity, with potential applications to evaluate mechanisms and outcomes across various patient populations.

Indexed as

HypoxiaAdultAgedCardiovascular DiseasesFemaleHumansMaleMiddle AgedOxygen SaturationSeverity of Illness Index

Identifiers

PMID40638677
PMCPMC12244826

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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 Socratic graph.