Interpretation of Skin Biopsies by General Pathologists: Diagnostic Discrepancy Rate Measured by Blinded Review
Bibliographic record
Abstract
CONTEXT: Slide review has been advocated as a means to reduce diagnostic error in surgical pathology and is considered an important component of a total quality assurance program. Blinded review is an unbiased method of error detection, and this approach may be used to determine the diagnostic discrepancy rates in surgical pathology. OBJECTIVE: To determine the diagnostic discrepancy rate for skin biopsies reported by general pathologists. DESIGN: Five hundred eighty-nine biopsies from 500 consecutive cases submitted by primary care physicians and reported by general pathologists were examined by rapid-screen, blinded review by 2 dermatopathologists, and the original diagnosis was compared with the review interpretation. RESULTS: Agreement was observed in 551 (93.5%) of 589 biopsies. Blinded review of these skin biopsies by experienced dermatopathologists had a sensitivity of 100% (all lesions originally reported were detected during review). False-negative errors were the most common discrepancy, but false positives, threshold discrepancies, and differences in type or grade were also observed. Only 1.4% of biopsies had discrepancies that were of potential clinical importance. CONCLUSIONS: Blinded review demonstrates that general pathologists reporting skin biopsies submitted by primary care physicians have a low diagnostic error rate. The method detects both false-negative and false-positive cases and identifies problematic areas that may be targeted in continuing education activities. Blinded review is a useful component of a dermatopathology quality improvement program.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.157 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".