Identifying adults at risk of COPD who need confirmatory spirometry in primary care
Bibliographic record
Abstract
Objective To examine the usefulness of a symptom-based case-finding questionnaire (CFQ) and the Medical Research Council (MRC) dyspnea scale in identifying which individuals with known risk factors for chronic obstructive pulmonary disease (COPD) require targeted spirometry in primary care. Design Cross-sectional study. Setting Three community primary care practices in Ontario. Participants Men and women 40 years of age and older with a smoking history of 20 pack-years or more. Main outcome measures We administered a CFQ for the presence of cough, sputum, wheeze, dyspnea, and recurrent respiratory infections (possible range of scores from 0 to 5) and applied the MRC dyspnea scale to assess the severity of COPD (possible range of scores from 1 to 5). Spirometric measures of forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) were collected, with COPD defined as a postbronchodilator FEV1/FVC of less than 0.7 and FEV1 of less than 80% of the predicted value. Using spirometric data to confirm the diagnosis of COPD, likelihood ratios, pretest and posttest probabilities, and area under a receiver operating characteristic curve were calculated for the total CFQ and MRC scores. Results Scores for the CFQ and MRC dyspnea scale were available for 996 and 829 participants, respectively. The likelihood ratios for a total CFQ score of 3 or higher and an MRC dyspnea score of 4 or 5 were 1.82 (95% confidence interval [CI] 1.48 to 2.22) and 4.22 (95% CI 2.08 to 8.56), respectively. The likelihood ratios for a total CFQ score of 2 or less and an MRC dyspnea score of 1 were 0.75 (95% CI 0.66 to 0.85) and 0.50 (95% CI 0.39 to 0.65), respectively. Area under the receiver operating characteristic curve was 0.62 (95% CI 0.58 to 0.67; P < .001) for the total CFQ scores and 0.64 (95% CI 0.60 to 068; P < .001) for the MRC dyspnea scores. Conclusion In adults with known risk factors, the likelihood of having moderate to severe COPD is increased in those who report 3 or more common respiratory symptoms and marked functional limitation resulting from dyspnea. However, selecting individuals for spirometry based on symptoms alone will identify less than half of those with moderate to severe COPD.
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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 | 0.013 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".