Performance of the automated BpTRU™ measurement device in the assessment of white-coat hypertension and white-coat effect
Bibliographic record
Abstract
OBJECTIVES: BpTRU (VSM MedTech Ltd, Vancouver, Canada) is an automated oscillometric device that provides serial blood pressure measurements in an office setting in the absence of a healthcare professional. We sought to determine whether the white-coat effect is reduced by a blood pressure measurement protocol using BpTRU compared with casual office measurements. Secondarily, we also sought to determine whether a blood pressure measurement protocol using BpTRU reduced white-coat hypertension compared with the casual office measurements, and reduced white-coat effect and white-coat hypertension compared with blood pressure obtained by a research nurse. METHODS: Blood pressure was measured in 107 adult hypertensive patients referred for ambulatory blood pressure monitoring using an ambulatory blood pressure monitor, a standardized protocol by a trained research nurse, and a protocol using BpTRU (five readings over 25 min, using the 5-min blood pressure measurement interval setting). Casual office blood pressure was also recorded in the family physicians' offices. Using the mean daytime ambulatory blood pressure as the reference standard, the proportion of patients with white-coat effect and white-coat hypertension were determined for measurements obtained by BpTRU, the research nurse, and the family physicians' offices. RESULTS: Casual office blood pressure measurements demonstrated a white-coat effect in 39 (36.4%) patients; seven (6.5%) patients demonstrated a white-coat effect using BpTRU (P<0.0001). White-coat hypertension was also less common using BpTRU than with the casual office readings (13 vs. 1 patient, P<0.0001). White-coat effect was also reduced with BpTRU compared with the research nurse measurements. Unfortunately, percentage agreement for the diagnosis of hypertension between the protocol using BpTRU and the reference standard was only 48%. This resulted in substantial misclassification of hypertension by the BpTRU measurement protocol. CONCLUSIONS: Although BpTRU reduces white-coat effect and white-coat hypertension, blood pressure is underestimated by the device, leading to misclassification of hypertension. BpTRU, when set at 5-min blood pressure measurement intervals, should not be used in clinical practice.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".