Role of clinical context in residents’ physical examination diagnostic accuracy
Bibliographic record
Abstract
CONTEXT: Clinical context may act as both an aid to decision making and a source of bias contributing to medical error. The effect of clinical history, a form of clinical context, on the diagnostic accuracy of the physical examination is unknown. METHODS: We randomised internal medicine residents to receive either no history or a short stem suggestive of one of six cardiac valvular diagnoses prior to a 10-minute objective structured clinical examination station assessing cardiac examination skills using a high-fidelity simulator. Clinical performance and diagnostic accuracy were compared using a standardised checklist. RESULTS: A total of 159 internal medicine residents were enrolled after providing informed consent. Of these, 80% arrived at the correct diagnosis, with diagnostic accuracy varying significantly by valve lesion (49-100%; p < 0.0001). Clinical context was associated with improved diagnostic accuracy compared with no history (90% versus 74%; likelihood ratio= 6.6, p < 0.0001), but was not associated with trainees' ability to identify and characterise physical findings. Among residents given clinical context, higher diagnostic accuracy was only achieved by those able to correctly predict the diagnosis from the history. CONCLUSIONS: Clinical context is associated with enhanced diagnostic accuracy of common valvular lesions. However, this effect seems linked to heuristic hypothesis generation and may predispose to premature diagnostic closure, anchoring and confirmation bias.
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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 | 0.536 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".