Metabolic Syndrome and Fatal Outcomes in the Post-Stroke Event: A 5-Year Cohort Study in Cameroon
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Determinants of post-acute stroke outcomes in Africa have been less investigated. We assessed the association of metabolic syndrome (MetS) and insulin resistance with post-stroke mortality in patients with first-ever-in-lifetime stroke in the capital city of Cameroon (sub-Saharan Africa). METHODS: Patients with an acute first-stroke event (n = 57) were recruited between May and October 2006, and followed for 5 years for mortality outcome. MetS definition was based on the Joint Interim Statement 2009, insulin sensitivity/resistance assessed via glucose-to-insulin ratio, quantitative insulin sensitivity check index and homeostatic model assessment. RESULTS: Overall, 24 (42%) patients deceased during follow-up. The prevalence of MetS was higher in patients who died after 28 days, 1 year and 5 years from any cause or cardiovascular-related causes (all p≤0.040). MetS was associated with an increased overall mortality both after 1 year (39% vs. 9%) and 5 years of follow-up (55% vs. 26%, p = 0.022). Similarly, fatal events due to cardiovascular-related conditions were more frequent in the presence of MetS both 1 year (37% vs. 9%) and 5 years after the first-ever-in-lifetime stroke (43% vs. 13%, p = 0.017). Unlike biochemical measures of insulin sensitivity and resistance (non-significant), in age- and sex-adjusted Cox models, MetS was associated with hazard ratio (95% CI) of 2.63 (1.03-6.73) and 3.54 (1.00-12.56) respectively for all-cause and cardiovascular mortality 5 years after stroke onset. CONCLUSION: The Joint Interim Statement 2009 definition of MetS may aid the identification of a subgroup of black African stroke patients who may benefit from intensification of risk factor management.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".