Blood pressure measurement techniques: Assessing performance in outpatient settings of a tertiary‐level hospital in Rwanda
Bibliographic record
Abstract
Cardiovascular diseases (CVD) are the leading cause of mortality globally. Hypertension is a known modifiable risk factor for CVD. Diagnosis and management of hypertension hinges upon accurate blood pressure (BP) measurement. In this study, we assessed performance to recommended guidelines for BP measurement in Rwanda. In 2017, a cross-sectional study investigating performance on 11 techniques recommended for BP measurement was undertaken across outpatient settings of 3 departments at the University Teaching Hospital of Kigali, Rwanda. Performance was checked by an inside observer. The study enrolled 164 patients. The overall mean performance on the 11 BP measurement techniques was 5.69 (±1.02) out of the 11 possible points. There was no significant difference in performance across departments (P = .28). The findings suggest that performance on currently recommended guidelines for BP measurement is not optimal. Going forward, it is important to implement interventions that will enhance performance given that diagnosis and management of hypertension depend upon accurate BP measurement.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".