Incidence of hospital admissions in bioimpedance‐guided fluid management among maintenance hemodialysis patients—Results of a randomized controlled trial
Bibliographic record
Abstract
INTRODUCTION: Hemodialysis is life-sustaining in kidney failure. However, proper regulation of body fluids depends on an accurate estimate of target weight. This trial aims to compare clinical endpoints between target weight estimation guided by bioimpedance spectroscopy and usual care in hemodialysis patients. METHODS: This is an open-label, parallel-group, controlled trial that randomized, through a table of random numbers, adult patients on maintenance hemodialysis to target weight estimation based on monthly clinical evaluation alone or added to evaluation by bioimpedance twice a year. The primary outcome was survival, and the secondary outcomes were the rate of hospital admissions, change in blood pressure (BP), and antihypertensive drugs load. Participants were followed for 2 years. Survival analysis was performed using Kaplan-Meier estimator and Log-rank test, and hospital admissions were analyzed by the incidence-rate ratio. FINDINGS: One hundred and ten patients were randomized to the usual care (52) or bioimpedance (58) groups, with a mean age of 57.4 (15.4) years, 64 (58%) males. There was no difference between the groups at baseline. Survival was not significantly different between groups (log-rank test p = 0.68), but the trial was underpowered for this outcome. There was also no difference between the groups in the change in systolic or diastolic BP or in the number of antihypertensive drugs being used. The incidence rate of hospital admissions was 3.1 and 2.1 per person-year in usual care and bioimpedance groups, respectively, with a time-adjusted incidence rate ratio of 1.48 (95% CI: 1.20-1.82, p = 0.0001) and attributable fraction of risk among exposed individuals of 0.32 (95% CI: 0.17-0.45). DISCUSSION: The inclusion of bioimpedance data to guide the estimation of target weight in hemodialysis patients had no detectable impact on survival or BP control, but significantly reduced the incidence rate of hospital admissions. The study was registered at ClinicalTrials.gov Identifier: NCT05272800.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".