Joint Trajectories of Blood Pressure and Heart Rate and Their Association with Relative Change in Relative Wall Thickness in Hypertensive Patients: A Group-Based Multi-Trajectory Modeling Analysis (Preprint)
Bibliographic record
Abstract
<sec> <title>BACKGROUND</title> Introduction: Ambulatory blood pressure monitoring (ABPM) can objectively assess circadian rhythms of blood pressure. However, the joint trajectories of blood pressure (BP) and heart rate (HR) and their association with early cardiac remodeling, particularly changes in relative wall thickness (RWT), remain incompletely characterized. </sec> <sec> <title>OBJECTIVE</title> Objective: To identify distinct subgroups of hypertensive patients based on joint trajectories of BP and HR using Group-Based Multi-Trajectory Modeling (GBMTM), characterize these groups, and examine their associations with ΔRWT, a marker of cardiac remodeling. </sec> <sec> <title>METHODS</title> Methods: We enrolled a total of 213 hypertensive patients from three community health centers in Zhongshan City, Guangdong Province, China (November 2022–January 2025). Participants completed four ABPM sessions in 9 months, with 24-hour mean BP and HR recorded. Using GBMTM, we identified joint trajectories of 24-hour mean BP and HR within 9 months. Multivariate linear regression analysis was applied to examine the association of trajectory groups with ΔRWT . </sec> <sec> <title>RESULTS</title> Results: We identified four joint trajectory groups via GBMTM. Compared with Group 4 (stage 2 hypertension, high heart rate), Group 2 (sustained optimal BP control) showed reduced RWT. Adjusted analyses revealed that antidiabetic medication use was associated with RWT reduction, while waking before 7:00 a.m. was linked to RWT increase. </sec> <sec> <title>CONCLUSIONS</title> Conclusions: Hypertensive cardiac remodeling exhibits significant differences across different trajectory groups. Stable BP control (even with high HR), glycemic management, and regular sleep patterns exert a protective effect against the development of hypertensive cardiac remodeling. </sec>
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".