Global, Race-Neutral Reference Equations and Pulmonary Function Test Interpretation
Bibliographic record
Abstract
Importance: Race and ethnicity are routinely used to inform pulmonary function test (PFT) interpretation. However, there is no biological justification for such use, and it may reinforce health disparities. Objective: To compare the PFT interpretations produced with race-neutral and race-specific equations. Design, Setting, and Participants: In this cross-sectional study, race-neutral reference equations recently developed by the Global Lung Function Initiative (GLI) were used to interpret PFTs performed at an academic medical center between January 2010 and December 2020. The interpretations produced with these race-neutral reference equations were compared with those produced using the race and ethnicity-specific reference equations produced by GLI in 2012. The analysis was conducted from April to October 2022. Main Outcomes and Measures: The primary outcomes were differences in the percentage of obstructive, restrictive, mixed, and nonspecific lung function impairments identified using the 2 sets of reference equations. Secondary outcomes were differences in severity of these impairments. Results: PFTs were interpreted from 2722 Black (686 men [25.4%]; mean [SD] age, 51.8 [13.9] years) and 5709 White (2654 men [46.5%]; mean [SD] age, 56.4 [14.3] years) individuals. Among Black individuals, replacing the race-specific reference equations with the race-neutral reference equations was associated with an increase in the prevalence of restriction from 26.8% (95% CI, 25.2%-28.5%) to 37.5% (95% CI, 35.7%-39.3%) and of a nonspecific pattern of impairment from 3.2% (95% CI, 2.5%- 3.8%) to 6.5% (95% CI, 5.6%-7.4%) and no significant change in the prevalence of obstruction (19.9% [95% CI, 18.4%-21.4%] vs 19.5% [95% CI, 18.0%-21.0%]). Among White individuals, replacing the race-specific reference equations with the race-neutral reference equations was associated with a decrease in the prevalence of restriction from 22.6% (95% CI, 21.5%-23.6%) to 18.0% (95% CI, 17.0%-19.0%), a decrease in the prevalence of a nonspecific pattern of impairment from 8.7% (95% CI, 7.9%-9.4%) to 4.0% (95% CI, 3.5%-4.5%), and no significant change in the percentage with obstruction from 23.9% (95% CI, 22.8%-25.1%) to 25.1% (95% CI, 23.9%- 26.2%). The race-neutral reference equations were associated with an increase in severity in 22.8% (95% CI, 21.2%-24.4%) of Black individuals and a decrease in severity in 19.3% (95% CI, 18.2%-20.3%) of White individuals vs the race-specific reference equations. Conclusions and Relevance: In this cross-sectional study, the use of race-neutral reference equations to interpret PFTs resulted in a significant increase in the number of Black individuals with respiratory impairments along with a significant increase in the severity of the identified impairments. More work is needed to quantify the effect these reference equations would have on diagnosis, referral, and treatment patterns.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".