Evidence map›Paper›PMID 40143907›Full record

ArticleJHLT open2024

Comparison of race-specific and race-neutral spirometry equations on the classification of restrictive lung physiology, interstitial lung disease, and lung transplant referral eligibility.

Daniel M Guidot, Mackenzie Wood, Emily Poehlein, Scott Palmer, Lisa McElroy

Abstract read
In one paragraph

Article in JHLT open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Daniel M GuidotGeriatrics Research, Education, and Care Center, Durham VA Medical Center, Durham, North Carolina.
Mackenzie WoodDepartment of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina.
Emily PoehleinDepartment of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina.
Scott PalmerDivision of Pulmonary, Allergy, and Critical Care, Duke University Medical Center, Durham, North Carolina.
Lisa McElroyDivision of Abdominal Transplant, Department of Surgery, Duke University Medical Center, Durham, North Carolina.

Funding

Duke Program of Training in Pulmonary ReSearch to Promote, Engage and Retain Academic Researchers (PROSPER)T32HL160494 · NHLBI · DUKE UNIVERSITY · PI Jennifer L. Ingram, DAVID MARTIN MURDOCH · 2022 to 2026
$2.6M
NHLBI NIH HHS T32 HL160494
6 · The paper itself

Abstract

Background: Race-specific reference equations for spirometry, including forced vital capacity (FVC), are under scrutiny in interstitial lung disease (ILD). Their influence on ILD and transplant decision-making warrants study. Methods: We performed a retrospective cohort study of adults with FVC measurements at Duke University Medical Center between October 1, 2014 and February 1, 2023. Using Global Lung Initiative 2012 reference equations, we compared how race-specific and race-neutral equations classified FVC with potential restrictive physiology (z-score < -2). In the subgroup of patients diagnosed with ILD, we compared how race-specific and race-neutral equations classified FVC as warranting transplant referral (percent-predicted <80%). We compared overall rates, odds ratios (ORs), and 95% confidence intervals (CIs) using conditional logistic regression and differences in timing. Results: We identified 45,587 patients, including 550 with ILD. Race-specific equations classified potential restricted physiology 5.2% more White patients (23.8% vs 18.6%, OR 1.28, 95% CI 1.24-1.32), 14.3% fewer Black patients (24.1% vs 38.4%, OR 0.63, 95% CI 0.60-0.66), and 7.7% fewer Asian patients (14.8% vs 22.5%, OR 0.66, 95% CI 0.53-0.82) compared with race-neutral equations. In the ILD subgroup, race-specific equations classified 13.0% more White patients as warranting transplant referral consideration compared to race-neutral equations (57.8% vs 44.8%, OR 1.29, 95% CI 1.07-1.56). Conclusions: Race-specific equations increased the classification of potential restrictive physiology and transplant candidacy for White patients but decreased the classification of potential restrictive physiology for Black and Asian patients. Race-specific equations in ILD and transplant decision-making warrant greater consideration given their potential to contribute to racial disparities.

Indexed as

interstitial lung diseaselung transplantationrace-specific reference equationsracial disparitiesspirometry

Identifiers

PMID40143907
PMCPMC11935469

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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.