20. Association of Dipping Status on Ambulatory Blood Pressure Monitoring with Cardiocerebrovascular Events in Patients with Essential Hypertension: A Meta-Analysis Study
Bibliographic record
Abstract
Background: Essential hypertension is a major risk factor for the occurrence of cardiocerebrovascular events (CCE). Ambulatory blood pressure monitoring (ABPM) has become an important tool in blood pressure monitoring in patients with hypertension, and the concept of “dipping status” which refers to a decrease in blood pressure during sleep, has gained significant attention as a potential predictor for cardiovascular events. Objective: to evaluate the association between dipping status on ABPM and cardiovascular events in patients with essential hypertension. Method: This study was a systematic review and meta-analysis of prospective cohort studies. Study searches were conducted in PubMed, Sciencedirect, and Proquest as well as manual searches using the snowballing method. Inclusion criteria were studies with research subjects of essential hypertension patients who underwent ABPM examination. Dipping status was considered positive if there was a >10% decrease in blood pressure at night during sleep. Included studies must contain data on the outcomes of CCE for a minimum period of six months. Study review was conducted according to the PRISMA flowchart. Study quality and risk of bias were assessed using the Newcastle Ottawa Scale for cohort studies. Study results were displayed as forest plots. Result: The meta-analysis included data from seven observational studies that included 10990 patients with essential hypertension. That patients with dipping status on ABPM had a lower risk of CCE compared with patients without dipping status (OR 0.74, 95% CI: 0.59-0.92, p Conclusion: that dipping status on ABPM is a protective factor against CCE in patients with essential 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 | 0.019 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.055 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".