Is Transient Ischemic Attack a Medical Emergency? An Evidence-Based Analysis.
Bibliographic record
Abstract
BACKGROUND: Transient ischemic attack (TIA) is a brief episode of dysfunction in a confined area of the brain. The risk of stroke following TIA is approximately 4% within the first 2 days and 9% within the first month. Therefore, early diagnosis and treatment is critical to reduce mortality and risk of stroke in patients who have experienced a TIA. OBJECTIVES: This systematic review aimed to investigate the impact of the urgent evaluation and initiation of treatment of patients with TIA on the risk of subsequent stroke and death. DATA SOURCES: A literature search was performed for studies published from January 1, 2007, until December 21, 2012. The search was updated monthly to April 1, 2013. RESULTS: All identified studies showed that urgent assessment and initiation of treatment of TIA is an effective strategy in reducing the incidence of stroke. Among these, a large observational study found a large effect in that the risk of stroke was reduced by 80%, and a Canadian study found that providing urgent care significantly reduced the rate of stroke in high-risk patients. Another Canadian study reported a significant reduction in the rate of death among patients referred to stroke prevention clinics, compared to patients not referred to such services. One study showed that patients discharged from an emergency department with standard care had significantly higher rates of stroke and subsequent TIA in the first month, compared to those who were hospitalized. However, another study showed that for patients at low to moderate risk, rate of stroke was similar between inpatients and those managed in a TIA clinic. LIMITATIONS: Our analysis was restricted to the effect of the combined interventions. The magnitude of benefit of each individual component of the intervention cannot be determined through this review. CONCLUSIONS: The results of this systematic review have important clinical and health system implications. Urgent management of TIA patients in specialized TIA clinics rather than regular practice results in a lower rate of stroke and disability.
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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 | 0.013 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".