Implementation of a Targeted Screening Program to Detect Airflow Obstruction Suggestive of Chronic Obstructive Pulmonary Disease within a Presurgical Screening Clinic
Bibliographic record
Abstract
BACKGROUND: Targeted spirometry screening for chronic obstructive pulmonary disease (COPD) has been studied in primary care and community settings. Limitations regarding availability and quality of testing remain. A targeted spirometry screening program was implemented within a presurgical screening (PSS) clinic to detect undiagnosed airways disease and identify patients with COPD/asthma in need of treatment optimization. OBJECTIVE: The present quality assurance study evaluated airflow obstruction detection rates and examined characteristics of patients identified through the targeted screening program. METHODS: The targeted spirometry screening program was implemented within the PSS clinic of a tertiary care university hospital. Current or ex-smokers with respiratory symptoms and patients with a history of COPD or asthma underwent prebronchodilator spirometry. History of airways disease and smoking status were obtained during the PSS assessment and confirmed through chart reviews. RESULTS: After exclusions, the study sample included 449 current or ex-smokers. Abnormal spirometry results were found in 184 (41%) patients: 73 (16%) had mild, 93 (21%) had moderate and 18 (4%) had severe or very severe airflow obstruction. One hundred eighteen (26%) new cases of airflow obstruction suggestive of COPD were detected. One-half of these new cases had moderate or severe airflow obstruction. Only 34% of patients with abnormal spirometry results had reported a previous diagnosis of COPD. More than one-half of patients with abnormal spirometry results were current smokers. CONCLUSIONS: Undiagnosed airflow obstruction was detected in a significant number of smokers and ex-smokers through a targeted screening program within a PSS clinic. These patients can be referred for early intervention and secondary preventive strategies.
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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 | 0.004 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".