Symptom-Based Questionnaire for Identifying COPD in Smokers
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: Symptom-based questionnaires may enhance chronic obstructive pulmonary disease (COPD) screening in primary care. OBJECTIVES: We prospectively tested questions to help identify COPD among smokers without prior history of lung disease. METHODS: Subjects were recruited via random mailing to primary care practices in Aberdeen, UK, and Denver, Colo., USA. Current and former smokers aged 40 or older with no prior respiratory diagnosis and no respiratory medications in the past year were enrolled. Participants answered questions covering demographics and symptoms and then underwent spirometry with reversibility testing. A study diagnosis of COPD was defined as fixed airway obstruction as measured by post-bronchodilator FEV(1)/FVC <0.70. We examined the ability of individual questions in a multivariate framework to correctly discriminate between persons with and without COPD. RESULTS: 818 subjects completed all investigations and proceeded to analysis. The list of 54 questions yielded 52 items for analysis, which was reduced to 17 items for entry into multivariate regression. Eight items had significant relationships with the study diagnosis of COPD, including age, pack-years, body mass index, weather-affected cough, phlegm without a cold, morning phlegm, wheeze frequency, and history of any allergies. Individual items yielded odds ratios ranging from 0.23 to 12. This questionnaire demonstrated a sensitivity of 80.4 and specificity of 72.0. CONCLUSIONS: A simple patient self-administered questionnaire can be used to identify patients with a high likelihood of having COPD, for whom spirometric testing is particularly important. Implementation of this questionnaire could enhance the efficiency and diagnostic accuracy of current screening efforts.
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