Interobserver Agreement of Usual Interstitial Pneumonia Diagnosis Correlated With Patient Outcome
Bibliographic record
Abstract
CONTEXT: - The histopathologic criteria for idiopathic pulmonary fibrosis were revised in the American Thoracic Society/European Respiratory Society/Japan Respiratory Society/Latin American Thoracic Association guidelines in 2011. However, the evidence of diagnosis based on the guidelines needs further investigation. OBJECTIVE: - To examine whether the revised histopathologic criteria for idiopathic pulmonary fibrosis improved interobserver agreement among pathologists and the predicted prognosis in patients with interstitial pneumonia. DESIGN: - Twenty, consecutive, surgical lung-biopsy specimens from cases of interstitial pneumonia were examined for histologic patterns by 11 pathologists without knowledge of clinical and radiologic data. Diagnosis was based on American Thoracic Society/European Respiratory Society guidelines of 2002 and 2011. Pathologists were grouped by cluster analysis, and interobserver agreement and association to the patient prognosis were compared with the diagnoses for each cluster. RESULTS: - The generalized κ coefficient of diagnosis for all pathologists was 0.23. If the diagnoses were divided into 2 groups: usual interstitial pneumonia (UIP)/probable UIP (the UIP group) or possible/not UIP (the non-UIP group), according to the 2011 guidelines, the κ improved to 0.37. The pathologists were subdivided into 2 clusters in which 1 showed an association between UIP group diagnosis and patient prognosis (P < .05). CONCLUSIONS: - Agreement about pathologic diagnosis of interstitial pneumonia is low; however, results after division into UIP and non-UIP groups provided favorable agreement. The cluster analysis revealed 1 of the 2 clusters providing high interobserver agreement and prediction of patient prognosis.
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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 | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".