Masked hypertension incidence and risk factors in a prospective cohort study
Bibliographic record
Abstract
Aims Masked hypertension may affect up to 30% of the general population and is associated with a high cardiovascular disease risk. No previous study has examined the incidence of masked hypertension and its risk factors. The study aim was to determine the incidence of masked hypertension and to examine its related risk factors. Methods This is a cohort study including 1836 initially normotensive participants followed up on average for 2.9 years. Blood pressure was measured using Spacelabs 90207. Manual blood pressure was defined as the mean of the first three readings taken at rest. Ambulatory blood pressure was defined as the mean of the next readings recorded every 15 minutes during daytime working hours. Masked hypertension incidence at follow-up was defined as manual blood pressure less than 140 and less than 90 mmHg and ambulatory blood pressure at least 135 or at least 85 mmHg. Generalised estimating equations were used. Results The cumulative incidence of masked hypertension was 10.3% and was associated with male gender (relative risk (RR) 1.51, 95% confidence interval (CI) 1.18–1.94), older age (RR40–49 years 1.56, 95% CI 1.16–2.11, RR≥50 years 1.50, 95% CI 1.06–2.10), higher education (RRcollege 1.31, 95% CI 1.03–1.65), body mass index (RR≥27 1.43, 95% CI 1.11–1.85), smoking (RR 1.51, 95% CI 1.09–2.010) and alcohol intake (RR≥6/week 1.65, 95% CI 1.13–2.03). Conclusion The present study is the first to identify risk factors for the incidence of masked hypertension. Current guidelines for hypertension detection recommend ambulatory blood pressure in patients with an elevated blood pressure reading at the clinic. As it is impractical to measure ambulatory blood pressure in all normotensive patients, factors identified in the present study should be considered for the screening of at-risk individuals and for primary prevention of masked hypertension.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".