Bioimpedance-Guided Monitoring of Volume Status in Patients With Kidney Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background and Objective: Bioimpedance technologies are increasingly used to determine fluid status in patients with chronic kidney disease and those with end-stage kidney disease on dialysis. We aimed to determine whether this technology improves clinical outcomes as compared with usual care. Methods: We performed a systematic review and meta-analysis of trials, comparing fluid management guided by bioimpedance technologies to standard of care in patients with chronic kidney disease. Our primary outcome was all-cause mortality. Secondary outcomes included blood pressure control, all-cause hospitalization, major adverse cardiovascular events, and change in left ventricular mass index. Results: Our search identified 819 citations of which 12 randomized controlled trials were included (2420 patients). No studies of non-dialysis-dependent chronic kidney disease patients met inclusion criteria. Mean age was 55 years and mean follow-up was 1 year. There was a statistically significant difference in all-cause mortality between both arms studied (risk ratio [RR] 0.64, 95% confidence interval [CI]: 0.44, 0.99). Better blood pressure control was observed in the bioimpedance arm of the included articles, weighted mean differences (WMD) -3.13 mm Hg (95% CI: -5.73, -0.53 mm Hg) for systolic blood pressure and WMD -2.50 mm Hg (95% CI: -4.36, -0.64 mm Hg) for diastolic blood pressure. No difference was observed concerning the other outcomes. Conclusions: Among patients on maintenance dialysis, bioimpedance-guided volume management showed decreased all-cause mortality and blood pressure but no significant difference in all-cause hospitalization, major adverse cardiac event, or change in left ventricular mass index. This may be due to a younger population sample than previous articles. Moreover, our study identified a knowledge gap by highlighting the lack of studies evaluating this technology in non-dialysis-dependent chronic kidney disease patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.031 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".