Attended versus unattended blood pressure measurement in real-life settings in patients with chronic kidney disease
Bibliographic record
Abstract
F -Literature Search, G -Funds collectionBackground.Systolic Blood Pressure intervention trial (SPrint) has raised interest in unattended automated office blood pressure (BP) measurement.it remains to be determined whether unattended BP measurement may yield lower values than conventional attended measurements in patients with very high cardiovascular risk, e.g. with chronic kidney disease (cKD).Objectives. the aim of the study was to investigate the differences in attended (aBP) vs unattended BP (naBP) in hospitalised patients with cKD.Material and methods.60 patients were included (33 M, 27 F; age 65.6 ± 14.0 years, eGFr 41.6 ± 28.5 (5.2 -94.4 ml/min)).BP (blood pressure) was first measured using the conventional auscultatory method by a medical staff member, and after a five-minute rest, three additional automated measurements with oMron M10-it were taken without the presence of medical staff.the same procedure was repeated over two consecutive days without any modification of antihypertensive treatment.Results.Mean unattended systolic blood pressure (naSBP) and unattended diastolic blood pressure (naDBP) were 143.6 and 77.9 mm hg, respectively.the respective values of attended blood pressure (aBP) were 150.8 and 81.4 mm hg.all aBP values were significantly higher than unattended blood pressure values (p = 0.009, p = 0.04 and p = 0.01, respectively).the differences between aBP and naBP did not correlate with eGFr. the difference between aBP and naBP was similar in diabetic and non-diabetic patients, as well as smokers vs non-smokers.Conclusions.attended BP is significantly higher than unattended BP in patients with cKD regardless of eGFr.automated BP measurement could become routine practice in patients with cKD.
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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 | 0.009 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".