Misdiagnosis of Cerebellar Infarctions
Bibliographic record
Abstract
BACKGROUND: This retrospective study addresses for the first time the differences in clinical features and outcomes between those individuals with a cerebellar infarct who were correctly diagnosed on initial presentation compared to those who experienced delayed diagnosis. METHODS: A retrospective review was conducted of our stroke registry from 09/2003 to 02/2011. Forty seven patients had an isolated cerebellar infarction confirmed by MRI. Misdiagnosis was defined as the diagnosis given by the first physician. RESULTS: Among 47 patients identified, 59.6% had delayed diagnosis. Five patients in the correct diagnosis group received intravenous tissue plasminogen activator, compared to none in the delayed diagnosis group. Complaints of weakness were protective from delayed diagnosis (OR 0.087, 95% CI 0.019-0.393, p=0.001). Conclusion : Patients with an isolated cerebellar infarction need to be considered when patients present with acute non-specific symptoms. Critical components of the neurological examination are omitted which are imperative to diagnose cerebellar infarcts. A thorough neurological examination may increase clinical suspicion of an ischemic stroke.
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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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".