A prospective population-based study of stroke in the Central Region of Iran: The Qom Incidence of Stroke Study
Bibliographic record
Abstract
OBJECTIVE: Based on the few population-based studies that have been conducted in the Middle East, we determined the incidence of stroke in Qom, one of the central provinces of Iran. METHODS: The Qom province includes an estimated at-risk population of about 1 million. During a 12-month period (November 2018-November 2019), all first-ever strokes occurring in the target population were registered. Hospitalized cases were ascertained by discharge codes. Out-of-hospital cases were ascertained by a prospective screening of emergency medical services, emergency departments, ambulances records, primary care clinics, rural and urban public health centers, primary care physician offices, and neurologists' offices. Crude and age-adjusted incidence rates (per 100,000 person-years) were calculated. RESULTS: During the study period, 1462 first-ever strokes occurred with a mean age of 68.1 (17-103) years; of these 45.2% were females (661 cases). The crude annual incidence rate per 100,000 at-risk populations was 145.4 (95% confidence interval, 138.1-153.0) for all types of stroke (156.5 for males and 134.3 for females), 26.4 (95% confidence interval, 23.5-29.8) for hemorrhagic stroke, and 114 (95% confidence interval, 105-121) for ischemic stroke. The incidence rate adjusted to the world population was 201.4 (95% confidence interval, 193-210) per 100,000 at-risk populations (adj incidence, 218.5 for males vs 187.4 for females). The total fatality rate during the first 28 days was 19.6%. CONCLUSION: This study states that in this region there is a high incidence of stroke, which occurs at a younger age than the global average. There was a high prevalence of underlying stroke risk factors.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".