Indonesia Stroke Registry (S12.003)
Bibliographic record
Abstract
Background: Indonesia Basic Health Research 2007 on 33 provinces showed that prevalence of stroke was 8.2 per 1000 population, and the highest prevalence came from province of Aceh (16.6/‰). Stroke was also the number 1 killer in Indonesia (15.4%), Methods: Prospective observational study was carried out from October 2012 until April 2013 using standardized Stroke Case Report Form. 11 hospital involved in this epidemiology research. Results: 1807 stroke patients collected from October 2012 - April 2013, Ischemic stroke accounted for the majority of cases (67.1%) and hemorrhagic was 32.9%. and hypertension is the most common risk factor for both hemorrhage (71.2%) and ischemic stroke (63.4%), followed by diabetes mellitus and dyslipidemia. Mortality was recorded 20.3% death after 48 hours, 18.3% ≤ 48hours in stroke hemorrhage, compared with 8.3% death in stroke ischemic after 48 hours, and 3.5% ≤ 48 hours. Data of recurrence stroke showed relatively high in both types of stroke. It was also evaluated the functional and cognitive outcome by using NIHSS, Barthel Index, and MMSE, MoCA-Ina (Montreal Cognitive Assessment Indonesia). Conclusion: Having the high prevalence of first ever and recurrent stroke, hypertension is the most common risk factor for both ischemic and hemorrhage stroke. This study was very useful for our country and our specialty to make some national plans to educate people to modify the life style, to train the general practitioners in primary health care as the first gate health service to provide community program for controlling some risk factors of stroke, Those must be the first priority of combating stroke in Indonesia Keywords: Stroke registry, risk factor, functional outcome, cognitive outcome Disclosure: Center for Applied Health Technology and Clinical Epidemiology, National Institute of Health Research and Development, Ministry of Health Republic Indonesia
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.279 | 0.263 |
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".