Revisiting Unattended Versus Attended Automated Office Blood Pressure Measurements: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: Standardized automated office blood pressure (AOBP) measurement is widely accepted as the preferred method for monitoring blood pressure (BP) in health care settings. However, disagreements persist as to the need to perform AOBP unattended, where the patient is left alone in a quiet room. Thus, this study aimed to assess the BP differences between unattended and attended AOBP. METHODS: This systematic review and meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and registered on PROSPERO (International Prospective Register of Systematic Reviews). Studies were included if unattended and attended AOBP measurements were performed on the same participants in a randomized or alternating sequence order during a single visit, using the same device and measurement protocol. The primary outcome was the difference between unattended and attended systolic BP and the secondary outcome, the difference in diastolic BP. Pooled results were expressed as weighted mean differences (95% CI) obtained using random-effects meta-analysis. RESULTS: From 8088 screened studies, data were extracted from 15 studies (n=1747 participants). The unattended systolic BP and diastolic BP were -2.7 (-4.7 to -0.6) and -0.9 (-1.8 to -0.1) mm Hg lower than attended BPs. In a leave-one-out analysis, the overall difference was largely driven by a single outlier study. After excluding that study, the estimated difference was -2.0 mmHg (95% CI -4.1 to 0.0). CONCLUSIONS: Standardized unattended AOBP measurements result in slightly lower readings than attended AOBP. Whether these small measurement differences translate into clinically significant changes in management remains uncertain. Therefore, attended AOBP appears to be a reasonable option for BP measurement in a real-world clinical setting.
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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 | 0.028 | 0.066 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.048 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".