Brief online certification course for measuring blood pressure with an automated blood pressure device. A free new resource to support World Hypertension Day Oct 17, 2020
Bibliographic record
Abstract
Detection, diagnosis, and treatment of hypertension require accurate blood pressure assessment. However, in clinical practice, lack of training in or nonadherence to measurement recommendations, lack of patient preparation, unsuitable environments where blood pressure is measured, and inaccurate and inappropriate equipment are widespread and commonly lead to inaccurate blood pressure readings. This has led to calls to require regular training and certification for people assessing blood pressure. Hence, the Pan American Health Organization in collaboration with Resolve to Save Lives, the World Hypertension League, Lancet Commission on Hypertension Group, and Hypertension Canada has developed a free brief training and certification course in blood pressure measurement. The course is available at www. The release of the online certification course is timed to help support World Hypertension Day. This year World Hypertension Day has been delayed to October 17 due to the COVID-19 pandemic. For 2020, the World Hypertension League calls on all health care professionals, health care professional organizations, and indeed all of society, to assess the blood pressure of all adults, measure blood pressure accurately, and achieve blood pressure control in those with hypertension.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.462 | 0.182 |
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".