Objective Structured Clinical Examination (OSCE) Station on Communicating Poor Prognosis to the Family in a Neurological Acute Care Setting
Bibliographic record
Abstract
Abstract Introduction Stroke is a common cause of patient morbidity and mortality. Communicating its prognosis to family members, along with the establishment of goals of care, is a frequent task for neurologists and neurology residents. Given this, we felt it was an appropriate scenario from which to assess neurology resident medical expert and communication skills in an objective structured clinical examination (OSCE) setting. The OSCE station topic was created directly from objectives of training for neurology residents specified by the Royal College of Physicians and Surgeons of Canada. Methods This is a standardized case with an actor portraying a patient's relative. Residents are to give bad news of poor neurologic prognosis and establish goals of care for the patient. The case scenario, instructions to the examinee, and examiner marking sheet are included. Results The OSCE station was implemented with pediatric and adult senior neurology residents (PGY3-PGY5) from three universities. Of the 25 residents who experienced this case, 96% passed the station. Resident scores ranged from 60%-100%, with a mean of 86%. Discussion We consider the significance of the work to be the interpretation of a clinical scenario of poor neurologic prognosis of severe stroke and the communication of poor prognosis to a standardized family member with resultant establishment of code status, a task that is performed several times per week on the acute stroke service. This OSCE station is appropriate for neurology residents who participate in stroke care and will become neurologists who must communicate bad news on a daily basis.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".