Age-dependent changes in blood pressure over consecutive office measurements
Bibliographic record
Abstract
OBJECTIVES: Based on anecdotal belief that blood pressure (BP) drops over consecutive measurements, guidelines recommend discarding the first BP reading (Canadian Hypertension Education Program guidelines) or take only one reading if SBP less than 140 mmHg (National Institute for Health and Care Excellence). However, the extent to which SBP fluctuations affect BP classification as well as the potential effect of age are unknown. We sought to assess the change in SBP classification over consecutive measurements following different guidelines, among younger (<50 years) and older individuals (≥50 years). Furthermore, we aimed to investigate the direction of the change in SBP over consecutive measurements (increase or decrease) and the impact of age on SBP differences. METHODS: BP was measured among 20 716 adults from a general population. SBP was classified using the first reading (normal SBP or hypertension) and compared with the average SBP using different guideline protocols (reclassification). RESULTS: Reclassification from normal SBP to hypertension was greatest with Canadian Hypertension Education Program guidelines (3% younger, 12% older individuals) and reclassification from hypertension to normal SBP was greatest with National Institute for Health and Care Excellence guidelines (70% younger, 44% older individuals). SBP increased between the first two measures in 37%, decreased in 56% and did not change in 7% of the population. Age had a strong interaction with SBP level (P < 0.0001) so that younger individuals exhibited greater SBP differences over repeated measures. CONCLUSION: This study highlights the need for an improvement in the evidence-base regarding the best way to assess office BP for correct hypertension diagnosis.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".