Relationship of Family History Scores for Stroke and Hypertension to Quantitative Measures of White-Matter Hyperintensities and Stroke Volume in Elderly Males
Bibliographic record
Abstract
White-matter hyperintensities (WMHI) are frequently associated with cerebrovascular risk factors in the elderly, particularly hypertension, and have been interpreted as a subclinical form of ischemic brain damage. WMHI, clinical stroke and blood pressures show significant genetic influences. The objective of this study was to determine whether a relationship exists between family history of stroke and/or hypertension in first degree relatives and WMHI in the elderly. WMHI and stroke (CVA) volumes were quantified from brain MRI performed on 414 white, male twins born between 1917 and 1927 (average age 72.3 +/- 2.9 years). WMHI, adjusted for age and head size, was significantly correlated with the family history score (r = 0.21, p < 0.001). Dividing the family history scores into quintiles revealed significant differences in WMHI by quintile mean (p < 0.05). Subjects in the highest quintile of family history score had the highest mean WMHI. Recalculation of the family history score, by only counting relatives reported to have had a clinical stroke as a positive event, revealed a nonsignificant correlation with WMHI, but the correlation of the family history score with MRI CVA volume was significant (p < 0.05). Stepwise multivariate analysis including ApoE status, current smoking status, smoking packyear history, Doppler ankle/arm blood pressure ratios, current and long term hypertensive status and current systolic and diastolic pressures indicated that the stroke/hypertension family history score was the single best predictor (p < 0.01) of WMHI volumes. Family history was not an independent predictor of CVA volume.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".