Maternal component in the familial aggregation of hypertension
Bibliographic record
Abstract
To assess maternal versus paternal contributions to the familial aggregation of hypertension, we examined family history data from 344 hypertensive probands (69 African American, 153 US Caucasian, 122 Greek Caucasian) ascertained without respect to parental hypertension status. The proportion of hypertensive mothers (81.7, 65.0 and 84.8% for African Americans, US Caucasians and Greek Caucasians, respectively) of these probands was significantly greater than the proportion of hypertensive fathers (50.0, 44.9 and 48.3%, respectively) in all three ethnic groups. The lifetime risk of hypertension was significantly greater for mothers compared with fathers of these hypertensive probands (p<0.001). Examination of the proband's siblings indicated that maternal history of hypertension was associated with greater lifetime risk for hypertension than paternal history (p<0.01). In conclusion, we observe a consistent maternal component in the inheritance of hypertension. Although we cannot separate a maternal genetic from epigenetic or environmental effect, our findings suggest that genetic research should include studies of the mitochondrial as well as nuclear genome. Furthermore, when assessing a patient's risk for hypertension, particular attention should be paid to the maternal family history.
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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 | 0.006 |
| 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 | 0.000 | 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".