Day-to-day blood pressure variability in older persons – optimizing measurement
Bibliographic record
Abstract
BACKGROUND: Higher blood pressure variability (BPV) is associated with adverse clinical outcomes but lack of standardized methodology hampers clinical translation. Day-to-day BPV seems most promising for an older population, especially those with cognitive impairment. This study aimed to determine the optimal number of measurements for obtaining day-to-day BPV in this population. METHODS: We included 127 patients attending the geriatric outpatient memory clinic, who measured blood pressure for seven days, morning and evening. Blood pressure measurements of day one were discarded and the coefficient of variation was calculated to assess BPV. Concordance between 7-day BPV (CV 7days ) and a reduced number of measurement days (CV 6days - CV 3days ) was analysed with Bland-Altman plots, intraclass correlation coefficient (ICC), and an a priori determined threshold of a 95% confidence interval (CI) with a lower bound of 0.75. RESULTS: The mean age was 74.6 ± 8.6 years, 49% were female, and had dementia or mild cognitive impairment in 37% and 33% respectively. Reducing the number of measurement days resulted in wider limits of agreement. Concordance decreased when reducing measurement days and reached our predefined threshold with four measurement days (ICC = 0.91, 95% CI = 0.87 - 0.93). BPV derived from five measurement days showed a similar relationship with diagnosis as our reference BPV value obtained with seven days. CONCLUSION: Our results suggest that systolic home blood pressure should be measured in the morning and evening for at least five consecutive days in duplicate to obtain reliable day-to-day BPV values in older adults with cognitive complaints.
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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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".