Methodology and technology for peripheral and central blood pressure and blood pressure variability measurement
Bibliographic record
Abstract
Office blood pressure measurement has been the basis for hypertension evaluation for almost a century. However, the evaluation of blood pressure out of the office using ambulatory or self-home monitoring is now strongly recommended for the accurate diagnosis in many, if not all, cases with suspected hypertension. Moreover, there is evidence that the variability of blood pressure might offer prognostic information that is independent of the average blood pressure level. Recently, advancement in technology has provided noninvasive evaluation of central (aortic) blood pressure, which might have attributes that are additive to the conventional brachial blood pressure measurement. This position statement, developed by international experts, deals with key research and practical issues in regard to peripheral blood pressure measurement (office, home, and ambulatory), blood pressure variability, and central blood pressure measurement. The objective is to present current achievements, identify gaps in knowledge and issues concerning clinical application, and present relevant research questions and directions to investigators and manufacturers for future research and development (primary goal).
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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 | 0.029 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.007 |
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".