Association of Bioimpedance Guided Fluid Management in Patients Receiving Peritoneal Dialysis and Cardiovascular Outcomes: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Fluid management in patients receiving peritoneal dialysis is a major challenge for nephrologists. This systematic review and meta-analysis evaluates the association with bioimpedance guided fluid management in patients receiving peritoneal dialysis and cardiovascular outcomes. Methods: PubMed, Embase and CENTRAL were searched from database inception to 09-Jan-2022 for randomized clinical trials comparing bioimpedance and clinical examination guided fluid management in patients receiving peritoneal dialysis. A randomeffects meta-analysis was used to estimate the pooled treatment-effect. The primary outcome measure was a composite cardiovascular outcome. Secondary outcome measures included all-cause mortality, cardiovascular mortality, hospitalizations, technique failure, change in systolic blood pressure (mmHg), weight (kg) and urine output (ml/day). Results: Seven trials were eligible for inclusion (n=1238) (mean follow-up: 19 months). The association of bioimpedance guided fluid management compared to clinical examination guided fluid management and cardiovascular outcomes was notsignificant (Odds Ratio (OR) 0.81, 95% Confidence Interval (CI),0.49-1.33;Absolute Risk Reduction (ARR) 2.2%,-3to7.1). Bioimpedance guided fluid management compared to clinical examination guided fluid management was associated with a significant reduction in cardiovascular mortality (OR0.50,95%CI, 0.26-0.98,ARR4.5%,0.3-8.7), systolic blood pressure (mean reduction -0.2 mmHg [-0.36 to -0.04]) but not all-cause mortality, weight (kg) or residual urine output (ml/day). Conclusions: Bioimpedance guided fluid management in patients receiving peritoneal dialysis compared to control was not associated with a lower incidence of cardiovascular outcomes. However, bioimpedance guided fluid management, compared to control, was associated with statistically significant lower cardiovascular mortality and lower systolic blood pressure without a reduction in residual urine output.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".