Reverse cardiac remodeling after fluid balance optimization in patients with <scp>end‐stage</scp> renal disease
Bibliographic record
Abstract
BACKGROUND: In patients with end-stage renal disease (ESRD) undergoing hemodialysis, cardiovascular diseases, and in particular chronic heart failure are the leading causes of morbidity and mortality. Nevertheless, few data are available about the impact of fluid optimization on echocardiographic parameters of cardiac function in patients with ESRD. METHODS AND RESULTS: In five patients with ESRD undergoing hemodialysis who had developed nonischemic dilated cardiomyopathy, an optimal fluid volume management based on a strict bioelectrical impedance analysis-assisted dry weight target and dietary sodium and water restriction led to left ventricular reverse remodeling and improvement in hemodynamic parameters. The reverse remodeling further improved after kidney transplantation. CONCLUSIONS: This case series supports the possible beneficial effect of volume status optimization on cardiac function and the potential reversibility of cardiac dysfunction after kidney transplantation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".