Misdiagnosis of asthma in schoolchildren
Bibliographic record
Abstract
BACKGROUND: A correct diagnosis of asthma is the cornerstone of asthma management. Few pediatric studies have examined the accuracy of physician-diagnosed asthma. OBJECTIVES: We determined the accuracy of parent reported physician-diagnosed asthma in children sampled from a community cohort. METHODS: Nested case-control study that recruited 203 children, aged 9-12, from a community-based sample. Three groups were recruited: asthma cases had a parental report of physician-diagnosed asthma, symptomatic controls had respiratory symptoms without a diagnosis of asthma, and asymptomatic controls had no respiratory symptoms. All participants were assessed and assigned a clinical diagnosis by one of three study physicians, and then completed spirometry, methacholine challenge, and allergy skin testing. The reference standard of asthma required a study physician's clinical diagnosis of asthma and either reversible bronchoconstriction or a positive methacholine challenge. Diagnostic accuracy, sensitivity and specificity were calculated for parent-reported asthma diagnosis compared to the reference standard. RESULTS: One hundred two asthma cases, 52 controls with respiratory symptoms but no asthma diagnosis, and 49 asymptomatic controls were assessed. Physician agreement for the diagnosis of asthma was moderate (kappa 0.46-0.81). Compared to the reference standard, 45% of asthma cases were overdiagnosed and 10% of symptomatic controls were underdiagnosed. Parental report of physician-diagnosed asthma had 75% sensitivity and 92% specificity for correctly identifying asthma. CONCLUSIONS: There is significant misclassification of childhood asthma when the diagnosis relies solely on a clinical history. This study highlights the importance of objective testing to confirm the diagnosis of asthma. Pediatr Pulmonol. 2017;52:293-302. © 2016 Wiley Periodicals, Inc.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".