Stroke Pentagon: Stroke Management Approach in Resource Poor Settings
Bibliographic record
Abstract
Stroke is a neurological condition that is characterized by sudden onset focal neurological deficit due to spontaneous cerebral vascular occlusion or rupture. It is a neurological emergency and its prevalence is very high, especially in developing countries where it assumes an epidemic proportion. It is globally the second most common cause of death after ischaemic heart disease. The poor indices in developing countries are multifactorial and related to late case presentation, ignorance, poverty, and unavailability of comprehensive and well-coordinated stroke care. There is a need to identify the available and cheap stroke management steps in the developing countries and strengthen the system to maximize the benefits in reduction of the morbidity and mortality of stroke. It is against this background that we identified Stroke prevention, acute stroke management, Stroke rehabilitation, Stroke research, and Stroke support as five pillars (stroke pentagon) in stroke management in developing countries. There is a need to sensitize the stakeholders in stroke management as highlighted in the stroke pentagon to assume more responsibility. Moreover, there is the need to have a more coordinated and concerted stroke management approach which will involve all the identified five pillars to ensure improved stroke indices in the developing countries.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".