The effect of marital and job strain on 3 year left ventricular mass in men and women with mild hypertension
Bibliographic record
Abstract
The purpose of the study was to evaluate whether marital adjustment and job strain, measured by self-report (Dyadic Adjustment Scale, DAS and Job Content Questionnaire), influence left ventricular mass index (LVMI) measured over 3 years. Patients (n=72) with repeatedly elevated diastolic blood pressure (BP) who were not medicated, employed, and living with significant other for a minimum of 6 months underwent 24 hr ambulatory BP monitoring and M-mode echocardiography at baseline and 3 years later. At entry the mean age was 47.8±9 years, 41% were female, and 26% had marital distress (population norm 16–20%) 24 hr systolic BP was 136.5±10mmHg and 24 hr diastolic BP was 86.7±7mmHg. At follow up, 6% had left ventricular hypertrophy; LVMI males>females (93±19gm/msq vs. 81±18, p=.006). Baseline marital adjustment, smoking, drinking, and baseline LVMI contributed significantly to the prediction of 3 year LVMI (semi partial correlation, sr2=0.04, 0.07, 0.03, and 0.22 respectively, p=0.03, 0.008, 0.08, and 0.0001) together accounting for 36% of the total variability in follow-up LVMI. Job strain was not related to LVMI nor did gender impact on DAS score. A 10 point diminution of the DAS score (ie. clinically noticeable) was associated with a 3 gm/m2 increase in LVMI. Marital adjustment was related to 3 year LVMI. Confirmation of these results with a larger sample and including objective marital assessment and the participation of normotensive subjects is required to clarify the role of marital and job strain in relation to left ventricular mass. Supported by the Heart and Stroke Foundation
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".