Supplementary Material for: Blood Pressure Variability and Outcomes in End-Stage Renal Disease Patients on Dialysis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Objective: Previous studies have suggested that blood pressure variability (BPV) is associated with an increased risk of mortality and cardiovascular events in patients on dialysis. However, the results are inconsistent. A comprehensive literature review was conducted to analyze the association between BPV and outcomes in patients on dialysis. Methods: Articles in Embase, Medline, and Web of Science from the date of inception through January 1, 2020, were identified. The outcomes were all-cause and cardiovascular mortality and cardiovascular events. The risk of bias was assessed using the Newcastle-Ottawa scale tool. Random effects models were used to pool the overall effect sizes. Two reviewers extracted the data independently. Meta-regression and subgroup analyses were performed to explore potential heterogeneity. Results: Fifteen eligible studies were included, and all enrolled hemodialysis recipients only. The overall risk of bias for the included studies was low. A 1-SD increase in systolic BPV was associated with higher risks of all-cause mortality (HR = 1.18; 95% CI 1.11–1.26, I2 = 53.8%), cardiovascular mortality (HR = 1.23; 95% CI 1.10–1.37, I2 = 57.2%), and cardiovascular events (HR = 1.27; 95% CI 1.07–1.51, I2 = 69.3%). Likewise, a 1-SD increase in diastolic BPV was associated with higher HR for all-cause and cardiovascular mortality (HR = 1.14; 95% CI 1.05–1.23, I2 = 0.0%, and HR = 1.14; 95% CI 0.94–1.38, I2 = 0.0%, respectively). Conclusions: A greater BPV is associated with higher risks of cardiovascular and mortality outcomes in patients on hemodialysis. Further research is required to determine whether BPV may be useful either as a marker enabling individualized treatment of cardiovascular risk or as a treatment target in its own right.
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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 | 0.006 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.560 | 0.023 |
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".