From BpTRU to OMRON: The impact of changing automated blood pressure measurement devices on adult population estimates of blood pressure and hypertension
Bibliographic record
Abstract
Background: In Cycle 7 (2022), the Canadian Health Measures Survey (CHMS) introduced the OMRON (OM) IntelliSense HEM-907XL blood pressure (BP) monitor after using the BpTRU (BT) BPM-300 BP monitor for six cycles. This study assessed differences between adult BP values measured by both devices and whether equations could be developed to compare BP measurements taken using the two devices. Data and methods: In Cycle 6 (2018 to 2019) of the CHMS, BP was measured using BT and OM devices. Between-device estimates of systolic BP (SBP), diastolic BP (DBP), and hypertension prevalence were compared for 1,072 adults aged 18 to 79 years. Sex, age, body mass index (BMI), and the use of antihypertensive medication were examined in linear regression models to predict SBP and DBP values measured with OM based on those measured with BT. Results: Average SBP measured with OM was 6 millimetres of mercury (mmHg) higher than average SBP measured with BT, and average DBP measured with OM was 2 mmHg lower than DBP measured with BT. Hypertension prevalence based on OM readings was 35.4%, compared with 34.0% based on BT readings. Between-device BP differences varied in magnitude by sex, age group, and BMI category. Average model-predicted estimates of BP were comparable to measured estimates, but predicted values were lower at higher levels of BP. Interpretation: Switching BP monitors will substantively affect population estimates of adult SBP and DBP but may have less impact on estimates of adult hypertension prevalence. The prediction equations proposed in this study can be applied to adult BP data from cycles 1 to 6 of the CHMS for comparison with BP measurements taken in Cycle 7, with some caveats. The impact of changing to the OM monitor in Cycle 7 should be acknowledged when reporting estimates of adult BP based on the CHMS.
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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 | 0.018 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".