Visit-to-visit blood pressure variability is common in primary care patients: Retrospective cohort study of 221,803 adults
Bibliographic record
Abstract
OBJECTIVE: Although high visit-to-visit blood pressure variability (BPV) is an independent risk factor for cardiovascular events, the frequency of high BPV is unknown. We conducted this study to define the frequency of high BPV in primary care patients, clinical correlates, and association with antihypertensive therapies. METHODS: Retrospective cohort study using electronic medical record data (with previously validated case definitions based on billing codes, free text analysis of progress notes, and prescribing data) from the Canadian Primary Care Sentinel Surveillance Network of 221,803 adults with multiple clinic visits over a 2-year period. We a priori defined a standard deviation>13.0 mm Hg in visit-to-visit systolic blood pressure (SBP) as "high BPV" based on prior literature. RESULTS: Overall, 85,455 (38.5%) patients had hypertension (mean 6.56 visits with SBP measurement, mean SBP 134.4 with Standard Deviation [SD] 11.3, 33.2% exhibited high BPV) and 136,348 did not (mean 3.96 visits with SBP measurement, mean SBP 120.9 with SD 8.2, 16.5% had high BPV). BPV increased with age regardless of whether individuals had hypertension or not; at all ages BPV varied across antihypertensive treatment regimens and was greater in those receiving renin angiotensin blockers or beta-blockers (p<0.001). High BPV was more frequent in patients with diabetes, chronic kidney disease, dementia, depression, chronic obstructive pulmonary disease, or Parkinson's disease. CONCLUSIONS: High visit-to-visit BPV is present in one sixth of non-hypertensive adults and one third of hypertensive individuals and is more common in those with comorbidities. The frequency of high BPV varies across antihypertensive treatment regimens.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".