Symptom-Based Questionnaire for Differentiating COPD and Asthma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Many patients with obstructive lung disease (OLD) carry an inaccurate diagnostic label. Symptom-based questionnaires could identify persons likely to need spirometry. OBJECTIVES: We prospectively tested questions derived from a comprehensive literature review and an international Delphi panel to help identify chronic OLD (COPD) in persons with prior evidence of OLD. METHODS: Subjects were recruited via random mailing to primary-care practices in Aberdeen, Scotland, and Denver, Colorado. Persons aged 40 and older reporting any prior diagnosis of OLD or any respiratory medications in the past year were enrolled. Participants answered 54 questions covering demographics and symptoms and underwent spirometry with reversibility testing. A study diagnosis of COPD was defined by fixed airway obstruction as measured by post-bronchodilator FEV(1)/FVC <0.70. We examined ability of individual questions in a multivariate framework to discriminate between persons with and without the study diagnosis of COPD. RESULTS: 597 persons completed all investigations and proceeded to analysis. The list of 54 questions yielded 52 items for analyses, which was reduced to 19 items for entry into a multivariate regression model. Nine items had significant relationships with the study diagnosis of COPD, including increased age, pack-years, worsening cough, breathing-related disability or hospitalization, worsening dyspnea, phlegm quantity, cold going to the chest, and receipt of treatment for breathing. Individual items yielded odds ratios ranging from 0.33 to 20.7. This questionnaire demonstrated a sensitivity of 72.0 and a specificity of 82.7. CONCLUSIONS: A short, symptom-based questionnaire identifies persons more likely to have COPD among persons with prior evidence of OLD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it