First-Ever Stroke and Transient Ischemic Attack Incidence and 30-Day Case-Fatality Rates in a Population-Based Study in Argentina
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Epidemiological data about stroke are scarce in low- and middle-income Latin-American countries. We investigated annual incidence of first-ever stroke and transient ischemic attack (TIA) and 30-day case-fatality rates in a population-based setting in Tandil, Argentina. METHODS: We prospectively identified all first-ever stroke and TIA cases from overlapping sources between January 5, 2013, and April 30, 2015, in Tandil, Argentina. We calculated crude and standardized incidence rates. We estimated 30-day case-fatality rates. RESULTS: We identified 334 first-ever strokes and 108 TIAs. Age-standardized incidence rate per 100 000 for Segi's World population was 76.5 (95% confidence interval [CI], 67.8-85.9) for first-ever stroke and 25.1 (95% CI, 20.2-30.7) for first-ever TIA, 56.1 (95% CI, 48.8-64.2) for ischemic stroke, 13.5 (95% CI, 9.9-17.9) for intracerebral hemorrhage, and 4.9 (95% CI, 2.7-8.1) for subarachnoid hemorrhage. Stroke incidence was slightly higher for men (87.8; 95% CI, 74.6-102.6) than for women (73.2; 95% CI, 61.7-86.1) when standardized for the Argentinean population. Thirty-day case-fatality rate was 14.7% (95% CI, 10.8-19.5) for ischemic stroke, 24.1% (95% CI, 14.2-36.6) for intracerebral hemorrhage, and 1.9% (95% CI, 0.4-5.8) for TIA. CONCLUSIONS: This study provides the first prospective population-based stroke and TIA incidence and case-fatality estimate in Argentina. First-ever stroke incidence was lower than that reported in previous Latin-American studies, but first-ever TIA incidence was higher. Thirty-day case-fatality rates were similar to those of other population-based Latin-American studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".