Abstract 71: Cognitive Impairment And The Risk Of Incident Stroke In Hypertensive Patients
Bibliographic record
Abstract
Background: Research has shown that post-stroke cognitive impairment is associated with worse functional outcome and stroke recurrence, but has not fully explored if cognitive impairment is associated with the risk of first-ever clinical stroke. Methods: We performed a post-hoc analysis of non-stroke SPRINT trial participants randomized to either a systolic blood pressure target <140mm Hg versus <120mm Hg. The primary outcome was incident stroke (ischemic and hemorrhagic). The study exposure was the baseline Montreal Cognitive Assessment (MoCA) score, into categories of <20, 20-25, and 26-30. We fit Cox models adjusting for age, race, sex, randomization arm, baseline blood pressure, atrial fibrillation, prior TIA, diabetes, and smoking. We verified the proportional hazards assumption of our Cox model. Results: We included 9126 patients (mean age 67.9, males 64.4%, non-Hispanic white 57.8%), of which 169 (1.8%) developed incident stroke during a mean follow-up of 3.8±0.9 years. The rate of stroke in the MoCA categories was 32/2713 (1.2%) for MoCA 26-30, 85/4649 (1.8%) for MOCA 20-25, and 50/1764 (2.8%) for MoCA <20 (p<0.001). In the adjusted Cox model, compared to the reference of MoCA 26-30, the hazard ratio for stroke was 1.42 (95% CI 0.94-2.14, p=0.099) in MoCA 20-25 and 2.22 (95% CI 1.38-3.56, p=0.001) in MoCA <20. The Kaplan-Meier curve for the MoCA stratification is presented in Figure 1. Conclusion: Severe cognitive impairment (MoCA <20) is a significant risk factor for incident stroke in hypertensive patients. Further research is needed to understand the mediators of this observation, in particular the control of vascular risk factors during follow-up.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".