Poor perception of bronchoconstriction and hyperinflation and risk of acute asthma exaerbations: A data linkage analysis
Bibliographic record
Abstract
Background: Perceptual acuity scores from bronchoprovocation testing may be useful clinically to identify individuals at risk of life-threatening asthma. Aim: To determine whether poor perception of bronchoconstriction (BC) and/or dynamic hyperinflation (DH) are independently significant risk factors for an acute asthma exacerbation (AAE) (defined as an ED visit, hospitalization or ICU admission). Methods: This is a prospective cohort data linkage study of adults with asthma, linking high-dose methacholine challenge (MCH) data to administrative data. Dyspnea perception scores (PS) were calculated from MCH tests at standardized changes in FEV1 and inspiratory capacity (IC) of 20, 30 and 40% predicted, representing mild, moderate and severe BC and DH respectively. AAE in the 5 years following MCH were identified from administrative data and compared between groups. The relative risks comparing poor to normal perceivers were determined using zero-inflated Poisson regression. Results: Forty-one AAEs were identified in 155 subjects (age: 34.6±11.2 years (mean±SD); 67.1% female; FEV1=90.6±16.0 %pr; PC20=2.7±3.4 mg/mL; BMI=28.2±6.6 kg/m2). The relative risk of AAEs in poor compared to normal perceivers of mild, moderate and severe BC and DH are summarized in Figure 1. Conclusion: After controlling for age and sex, poor perception of BC and DH increase the relative risk of acute asthma exacerbatiions.
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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 | 0.021 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".