Clinical and Imaging Phenotypes and Outcomes in a Costa Rican Cohort of Acute Ischemic Stroke Survivors: A Retrospective Study
Bibliographic record
Abstract
Background: We characterized clinical and imaging phenotypes and their association with clinical outcomes in acute ischemic stroke (AIS) survivors in the understudied region of Costa Rica. Methods: We conducted a retrospective cohort study in AIS patients treated at a tertiary stroke center in Costa Rica from 2011–2015. Participants underwent detailed phenotyping for cardiovascular risk factors and stroke etiology. We assessed the association of ischemic brain lesion features and clinical outcomes using the Oxfordshire Community Stroke Project (OCSP) classification. Results: We included 684 AIS survivors (60.2% males, aged 68.1 ± 13.6 years, mean ± SD). While the cardiovascular risk profiles and mortality rates of our patients were similar to populations in European and North American countries, only 20.2% of patients with atrial fibrillation (AF) received anticoagulation. On multivariable analysis, patients with total anterior circulation infarct (TACI) displayed an increased risk of complications (OR: 4.2; 95% CI: 2.2–7.8; p < 0.001), higher mortality (OR: 6.9; 95% CI: 2.9–16.1; p < 0.001) and lower chance of functional independence at discharge (OR: 8.9; 95% CI: 4.1–19; p < 0.001) compared to non-TACI. The comorbidity of bronchopneumonia increased the probability of death by 14.5 times. Conclusions: Our observations in a Costa Rican cohort of AIS survivors might help improve local measures for preventing and managing AIS.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".