Overdiagnosis of asthma in obese and nonobese adults
Bibliographic record
Abstract
BACKGROUND: It is unclear whether asthma is overdiagnosed in developed countries, particularly among obese individuals, who may be more likely than nonobese people to experience dyspnea. METHODS: We conducted a longitudinal study involving nonobese (body mass index 20-25) and obese (body mass index >/= 30) individuals with asthma that had been diagnosed by a physician. Participants were recruited from 8 Canadian cities by means of random-digit dialing. A diagnosis of current asthma was excluded in those who did not have evidence of acute worsening of asthma symptoms, reversible airflow obstruction or bronchial hyperresponsiveness, despite being weaned off asthma medications. We stopped asthma medications in those in whom a diagnosis of asthma was excluded and assessed their clinical outcomes over 6 months. RESULTS: Of 540 individuals with physician-diagnosed asthma who participated in the study, 496 (242 obese and 254 nonobese) could be conclusively assessed for a diagnosis of asthma. Asthma was ultimately excluded in 31.8% (95% confidence interval [CI] 26.3%-37.9%) in the obese group and in 28.7% (95% CI 23.5%-34.6%) in the nonobese group. Overdiagnosis of asthma was no more likely to occur among obese individuals than among nonobese individuals (p = 0.46). Of those in whom asthma was excluded, 65.5% did not need to take asthma medication or seek health care services because of asthma symptoms during a 6-month follow-up period. INTERPRETATION: About one-third of obese and nonobese individuals with physician-diagnosed asthma did not have asthma when objectively assessed. This finding suggests that, in developed countries such as Canada, asthma is overdiagnosed.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".