Resting blood pressure and heart rate measurement in the Canadian Health Measures Survey, cycle 1.
Bibliographic record
Abstract
BACKGROUND: Directly measured blood pressure (BP) data have not been collected in Canada since the Canadian Heart Health Surveys, conducted between 1985 and 1992. Because hypertension is often asymptomatic, a large proportion of those with the condition are unaware of it. DATA AND METHODS: These analyses use BP and heart rate (HR) data from cycle 1 of the 2007-2009 Canadian Health Measures Survey (CHMS) for respondents aged 6 to 79 years. Methods and quality assurance and control procedures are explained. Logistical and feasibility issues that arose during data collection are discussed. The reasons for repeating a series of measures are given. Between- and within- series variations and inter-tester variability are assessed. RESULTS: The BP and HR of almost all respondents who attended the examination centre were measured. Only one series of measurements was taken for 88% of respondents. The series was repeated for around 5% with variability in their BP or HR measurements. About 3% had HR or BP values above the screening cut-offs for the fitness tests. Almost 35% of respondents with HR or BP values above the screening cut-offs after their first series had values below the cut-points after the second series; a further 3% had values below after the third series. Within a series of six measurements, BP decreased until about the fourth measure, after which it remained stable. Mean BP and HR values indicated no inter-tester variability. INTERPRETATION: The protocol for measuring BP and HR by oscillometry in the CHMS appears to have produced reliable estimates. No benefit to repeating the series of six measurements a third time for screening purposes is evident. Four measurements may be sufficient to provide reliable BP and HR data. Oscillometry appears to eliminate inter-tester variability.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".