Clinical Relevance of Diagnosing COPD by Fixed Ratio or Lower Limit of Normal: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Different spirometric criteria in diagnosing COPD have been advocated by different groups, debilitating adequate diagnosis and treatment of COPD. We reviewed the clinical relevance of fixed ratio and lower limit of normal (LLN) in diagnosing COPD and explored if modifying factors may affect their clinical relevance. METHODS: Two reviewers independently searched PubMed and Embase for papers that compared both criteria on any clinically relevant outcome, published before June 1st, 2012, without any language restriction. Two reviewers independently extracted the study characteristics, including study design, population characteristics and diagnostic criteria used, and summarized the results of clinical relevance. Study quality was assessed by scoring forms for bias and level of evidence. RESULTS: Of 394 studies retrieved, 11 studies were included, with a median of 1,258 participants. Although both criteria appeared related with various clinically relevant outcomes, we were unable to prefer one criterion over the other, with various performances of the criteria for different outcomes. Should the criteria disagree on diagnosis, an alternative diagnosis should be suspected, in particular in those (elderly) with less severe airflow limitation for whom the LLN appears a better criterion. The fixed ratio appears to perform better in subjects with more severe airflow limitation. CONCLUSION: In diagnosing COPD, severity of airflow limitation appears an important factor for choosing whether the fixed ratio or LLN. Disagreement between the criteria is suggestive for an alternative diagnosis. Future studies on clinical relevance should further reveal the criterion of choice, in order to improve adequate diagnosis and consequent treatments.
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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 | 0.050 | 0.264 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.011 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".