Bibliographic record
Abstract
BACKGROUND: Aetiology of young stroke populations varies markedly between countries. AIM: We present one of the largest prospective studies of stroke in young adults, with specific attention given to aetiology and black-white differences to assist with secondary prevention and economic planning. SETTING: Durban, KwaZulu-Natal, South Africa. METHODS: Only first occurrence of stroke by World Health Organisation definition was recorded in patients who had undergone anatomical brain imaging. A hierarchy of investigative modalities divided into three tiers was applied and a range of standardised scales was scored for each patient. This protocol allowed for quantification of clinical deficit, aetiopathogenesis, disability and handicap. Cognitive impairment was evaluated separately according to predefined criteria. RESULTS: Young stroke patients (15-49 years) comprised one-quarter of patients seen at this tertiary referral institution (320:1, 260, 25.4%). Significant black-white differences were encountered for mean age, risk factors, severity of clinical stroke, topography of stroke, severity of neurological deficit (Canadian Neurological scale), handicap (Rankin scale), aetiology (Trial of Org 10172 in Acute Stroke (TOAST) classification) and frequency and subtype of cognitive impairment. In blacks, HIV-associated stroke was highest in the otherwise unknown aetiological TOAST category. CONCLUSION: In South Africa, race and endemic disease both appear to be important determinants of stroke in young adults. Knowledge of these variations will streamline the increasingly expensive diagnostic and therapeutic approach.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".