Optimizing observer performance of clinic blood pressure measurement: A position statement from the Lancet Commission on Hypertension Group
Bibliographic record
Abstract
High blood pressure (BP) is a highly prevalent modifiable cause of cardiovascular disease, stroke, and death. Accurate BP measurement is critical, given that a 5-mmHg measurement error may lead to incorrect hypertension status classification in 84 million individuals worldwide. This position statement summarizes procedures for optimizing observer performance in clinic BP measurement, with special attention given to low-to-middle-income settings, where resource limitations, heavy workloads, time constraints, and lack of electrical power make measurement more challenging. Many measurement errors can be minimized by appropriate patient preparation and standardized techniques. Validated semi-automated/automated upper arm cuff devices should be used instead of auscultation to simplify measurement and prevent observer error. Task sharing, creating a dedicated measurement workstation, and using semi-automated or solar-charged devices may help. Ensuring observer training, and periodic re-training, is critical. Low-cost, easily accessible certification programs should be considered to facilitate best BP measurement practice.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".