Patients Referred for TIA May Still Have Persisting Neurological Deficits
Bibliographic record
Abstract
BACKGROUND: The presence of residual neurological deficits after neurological symptoms is important information for making a diagnosis of Transient Ischemic Attack (TIA) versus stroke. The purpose of this study was to establish the reliability of the referring physician (non neurologist) to report focal neurological deficits in the context of an urgent referral for TIA. METHODS: Prospectively recorded urgent physician-to-physician phone referrals for TIA through the Southern Alberta TIA hotline from March 2009 to July 2010 were reviewed. "Has the neurological deficit completely resolved?" was asked to the referring physician (family or emergency room physician) and recorded prospectively as a yes/no response. Patients were included if a neurological examination was performed by a neurologist on the same day as referral. The neurologist's assessment of whether the deficit had resolved was compared to that of the referring physician. RESULTS: 78 patients were included in this study. 62 patients had resolved as per the referring physician's assessment. Of these 62 patients, 16 (25.8% 95%CI 16-38) had evidence of persisting neurological deficits on the neurologist's assessment. A wide variety of mild neurological deficits were identified. None of these deficits appeared to be explained by progression of symptoms. CONCLUSION: Physicians referring patients with TIA syndromes for emergent assessment do not reliably detect mild residual deficits in one-quarter of patients. We are questioning the validity of neurological deficit resolution as a triage rule. The findings suggest that studies of TIA likely include a proportion of minor stroke patients and this should be remembered when extrapolating the results to other populations.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".