Misdiagnosis of OADs in community patients with inhaled prescription medication for shortness of breath
Bibliographic record
Abstract
Background: Obstructive airway diseases (OADs) mainly asthma and chronic obstructive pulmonary disease (COPD) are the two common diseases associated with shortness of breath (SOB) symptoms. Objective: To compare physician-diagnosis of asthma and COPD among community patients with SOB and with prescribed inhalers to spirometrically-defined diagnosis or expert consensus based on ATS/ERS standard guidelines. Method: 328 of eligible SOB patients were identified through community pharmacies in Edmonton and Saskatoon, in Canada. Full pre and post-bronchodilator PFT were performed and diagnosis subsequently determined based on guideline-derived criteria approved by three expert physicians. Result: 45.4% of patients had a diagnosis of asthma and 29.6% COPD. Subjects were Caucasian (86%), female (57%), and had a postsecondary education (49%) and with a median age of 50 years. Only 40% of patients had prior PFT performed to provide a diagnosis from a family-care physician. Self-reported medications for management included SABA (74.1%), inhaled corticosteroids (28.0%), and combination inhaler products (35%). Measures of agreement ( that is, sensitivity (Sens) and specificity(Spec)) of physician-diagnosis with guideline-derived diagnosis were: asthma (Sens=71%, Spec=51%, Kappa=0.22, p=0.001), and COPD (Sens=28%.; Spec=95%, Kappa=0.28, p=0.001). Conclusion: Significant disagreement exists between physician-diagnosis and guideline-derived diagnosis among management of community patients with SOB symptoms. Most patients are prescribed inhalers without a PFT diagnostic workup. This may be in part due to the inadequate understanding of PFT interpretation and usage by family-care physicians.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".