FREQUENCY RATE OF OBESITY AND LOW MOBILITY IN NORTH AMERICAN AND IRANIAN STROKE PATIENTS
Bibliographic record
Abstract
Abstract INTRODUCTION: Obesity and low mobility are among the risk factors of stroke and cardiovascular diseases. A pilot double-center study evaluated frequency rate of obesity and low mobility in patients with ischemic stroke. METHODS: This prospective clinical study was conducted on 100 consecutive stroke patients in Mackenzie hospital, Canada and 100 consecutive stroke patients in Ghaem hospital, Iran in 2007. The patients were age- and sex- matched. Diagnosis of ischemic stroke was made by stroke neurologists. Obesity and low mobility was detected based on the standard method in the two studied groups. Chi-Square and Fisher tests served for statistical analysis and P < 0.05 was declared as significant. RESULTS: 92 males and 108 females with ischemic stroke were investigated. Obesity was present in 26% of the Canadians and 21% of Iranian stroke patients, df = 1, P = 0.403. Low mobility was reported in 29% of Canadian and 5% of Iranian stroke patients, df = 1, P < 0.0001. The frequency rate of obesity was not significantly different in the two groups and in each gender separately (P > 0.05), while the difference was significant for low mobility, P < 0.05. CONCLUSIONS: There is no significant difference in frequency rate of obesity between Canadian and Iranian stroke patients. However, low mobility is significantly more frequent in the old Canadian individuals with stroke. Keywords: Obesity, Stroke, Race.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".