Clinical impact of diagnostic imaging discrepancy by radiology trainees in an urban teaching hospital emergency department
Bibliographic record
Abstract
BACKGROUND: To characterize clinically significant diagnostic imaging (DI) discrepancies by radiology trainees and the impact on emergency department (ED) patients. METHODS: Consecutive case series methodology over a 6-month period in an urban, tertiary care teaching hospital. Emergency physicians (EPs) were recruited to flag discrepant DI interpretations by radiology trainees that the EP deemed clinically significant. Cases were characterized using chart review and EP interview. RESULTS: Twenty-eight discrepant reports were identified (representing 0.1% of 18,185 images interpreted). The mean time between provisional discrepant diagnosis (PDDx) and revised diagnosis (RDx) by attending radiology staff was 8.6 h (median 4.8 h, range 1.1-48.4), and 67.9% (n = 19) of the patients had left the ED by time of notification. The most frequently reported PDDx was CT abd/pelvis (32.1%, n = 9) and CT head (28.6%, n = 8). The impact of RDx was deemed major in 57.1% (n = 16) for reasons including altered admitting status (32.1%, n = 9), immediate subspecialty referral (n = 16, 57.1%), impact on management (25%, n = 7), and surgical management (21.4%, n = 6). EPs reported likely perceived impact of PDDx as resulting in increased pain (17. 9%, n = 5), morbidity (10.7%, n = 3), and prolonged hospitalization (25%, n = 7), but not altered long-term outcome or mortality. CONCLUSIONS: Relatively few clinically important discrepant reads were reported. Revised diagnosis (RDx) was associated with major clinical impact in 57.1% of reports, but few patients experienced increased morbidity, and none increased mortality. The importance of expedient communication of discrepant reports by staff radiologists is stressed, as is EP verification of patient contact information prior to discharge.
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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 | 0.001 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".