Supine blood pressure—A clinically relevant determinant of vascular target organ damage in hypertensive patients
Bibliographic record
Abstract
Night-time blood pressure (BP) is an important predictor of cardiovascular outcomes. Its assessment, however, remains challenging due to limited accessibility to ambulatory BP devices in many settings, costs, and other factors. We hypothesized that BP measured in a supine position during daytime may perform similarly to night-time BP when modeling their association with vascular hypertension-mediated organ damage (HMOD). Data from 165 hypertensive patients were used who as part of their routine clinic workup had a series of standardized BP measurements including seated attended office, seated and supine unattended office, and ambulatory BP monitoring. HMOD was determined by assessment of kidney function and pulse wave velocity. Correlation analysis was carried out, and univariate and multivariate models were fitted to assess the extent of shared variance between the BP modalities and their individual and shared contribution to HMOD variables. Of all standard non-24-hour systolic BP assessments, supine systolic BP shared the highest degree of variance with systolic night-time BP. In univariate analysis, both systolic supine and night-time BP were strong determinants of HMOD variables. In multivariate models, supine BP outperformed night-time BP as the most significant determinant of HMOD. These findings indicate that supine BP may not only be a clinically useful surrogate for night-time BP when ambulatory BP monitoring is not available, but also highlights the possibility that unattended supine BP may be more closely related to HMOD than other BP measurement modalities, a proposition that requires further investigations in prospective studies.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".