European Society of Hypertension practice guidelines for ambulatory blood pressure monitoring
Bibliographic record
Abstract
Given the increasing use of ambulatory blood pressure monitoring (ABPM) in both clinical practice and hypertension research, a group of scientists, participating in the European Society of Hypertension Working Group on blood pressure monitoring and cardiovascular variability, in year 2013 published a comprehensive position paper dealing with all aspects of the technique, based on the available scientific evidence for ABPM. The present work represents an updated schematic summary of the most important aspects related to the use of ABPM in daily practice, and is aimed at providing recommendations for proper use of this technique in a clinical setting by both specialists and practicing physicians. The present article details the requirements and the methodological issues to be addressed for using ABPM in clinical practice, The clinical indications for ABPM suggested by the available studies, among which white-coat phenomena, masked hypertension, and nocturnal hypertension, are outlined in detail, and the place of home measurement of blood pressure in relation to ABPM is discussed. The role of ABPM in pharmacological, epidemiological, and clinical research is also briefly mentioned. Finally, the implementation of ABPM in practice is considered in relation to the situation of different countries with regard to the reimbursement and the availability of ABPM in primary care practices, hospital clinics, and pharmacies.
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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 | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 0.014 |
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".