Reproducibility of sequential ambulatory blood pressure and pulse wave velocity measurements in normotensive and hypertensive individuals
Bibliographic record
Abstract
OBJECTIVE: Errors in blood pressure (BP) measurement account for a large proportion of misclassified hypertension diagnoses. Ambulatory blood pressure monitoring (ABPM) is often considered to be the gold standard for measurement of BP, but uncertainty remains regarding the degree of measurement error. The aim of this study was to determine reproducibility of sequential ABPM in a population of normotensive and well controlled hypertensive individuals. METHODS: Individual participant data from three randomized controlled trials, which had recorded ABPM and carotid-femoral pulse wave velocity (PWV) at least twice were combined ( n = 501). We calculated within-individual variability of daytime and night-time BP and compared the variability between normotensive ( n = 324) and hypertensive ( n = 177) individuals. As a secondary analysis, variability of PWV measurements was also calculated, and multivariable linear regression was used to assess characteristics associated with blood pressure variability (BPV). RESULTS: Within-individual coefficient of variation (CoV) for systolic BP was 5.4% (day) and 7.0% (night). Equivalent values for diastolic BP were 6.1% and 8.4%, respectively. No statistically significant difference in CoV was demonstrated between measurements for normotensive and hypertensive individuals. Within-individual CoV for PWV exceeded that of BP measurements (10.7%). BPV was associated with mean pressures, and BMI for night-time measurements. PWV was not independently associated with BPV. CONCLUSION: The variability of single ABPM measurements will still yield considerable uncertainty regarding true average pressures, potentially resulting in misclassification of hypertensive status and incorrect treatment regimes. Repeated ABPM may be necessary to refine antihypertensive therapy.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".