Diagnostic agreement among experts assessing adults presenting with possible cystic fibrosis: need for improvement and implications for patient care
Bibliographic record
Abstract
Background: Increasing awareness of milder presentations of cystic fibrosis (CF) and greater interest in non-CF bronchiectasis are likely to lead to more CF screening by respiratory clinicians. As a result, adults who may not strictly fulfil CF diagnostic criteria yet display evidence of abnormal CF transmembrane conductance regulator (CFTR) function are being identified. The degree of agreement on diagnosis and care needs in these cases between CF clinicians remains unknown, and has implications for patient care, including access to CFTR modulator therapies. Methods: We surveyed adult CF physicians in Canada, the USA, the UK and Ireland, and presented them with anonymised vignettes of adult patients referred for assessment of possible CF. Diagnostic inter-rater agreement over diagnosis, ease of classifying cases and appropriate follow-up was assessed using Krippendorff's reliability coefficient (α). Results: Canada) were associated with higher odds of recommending further testing compared with selecting a formal diagnosis (respectively, OR 2.87; p=0.022, OR 3.74; p=0.013 and OR 3.16; p=0.007). A modified standard of care was recommended in 28.7% of cases labelled as CF. 70% of respondents agreed with the statement that "Accurate distinction between CF and CFTR-related disorder has become significantly more pertinent with the advent of highly effective CFTR modulators". Conclusions: Our results demonstrate low diagnostic concordance among CF specialists assessing cases of possible adult CF and highlight an area in need of improvement.
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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 | 0.053 | 0.166 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".