Cognitive function in adolescence and the risk of early-onset stroke
Bibliographic record
Abstract
Background Stroke is increasingly prevalent at younger ages but the risk factors are uncertain. We examined the association between adolescent cognitive function and early-onset stroke. Methods This was a nationwide population-based cohort study of 1 741 345 Israeli adolescents (42% women) who underwent comprehensive cognitive function tests at age 16–20 years, before mandatory military service, during 1987–2012. Cognitive function (range: 1–9) was categorised as low (1–3, corresponding to IQ score below 89), medium (4–7, IQ score range: 89–118), or high (8–9, IQ score above 118). Participant data were linked to the Israeli National Stroke Registry. Cox proportional hazard models were used to estimate risks for the first occurrence of ischaemic stroke during 2014–2018. Results During 8 689 329 person-years of follow-up, up to a maximum age of 50 years, 908 first stroke events occurred (767 ischaemic and 141 haemorrhagic). Compared with a reference group of people with high cognitive function, body mass index-adjusted and sociodemographic-adjusted HRs (95% CIs) for early-onset stroke were 1.78 (1.33–2.38) in medium and 2.68 (1.96–3.67) in low cognitive function groups. There was evidence of a dose–response relationship (P for trend <0.0001) such that one-unit of lower cognitive function z-score was associated with a 33% increased risk of stroke (1.33; 1.23–1.42). These associations were similar for ischaemic stroke but lower for haemorrhagic stroke; persisted in sensitivity analyses that accounted for diabetes status and hypertension; and were evident before age 40 years. Conclusions Alongside adolescent obesity and hypertension, lower cognitive function may be a risk factor for early-onset stroke.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".