The association of overhydration with chronic inflammation in chronic maintenance hemodiafiltration patients
Bibliographic record
Abstract
INTRODUCTION: Achieving euvolemia is one of the major challenges when treating end-stage renal disease (ESRD) patients receiving maintenance renal replacement therapy. Fluid overload is recognized as an independent predictor of mortality in ESRD, but its association with chronic inflammation is less well explored especially in chronic maintenance hemodiafiltration. METHODS: We performed a cross-sectional study of 87 prevalent ESRD patients receiving chronic maintenance hemodiafiltration (vintage 66.5 ± 57.1 months) with bioimpedance analysis to characterize the degree of percent overhydration (OH%). We also compared the levels of inflammatory markers, including C-reactive protein (CRP), serum albumin, neutrophil/lymphocyte ratio (NLR), and hemoglobin red cell distribution width (RDW) for the overhydrated (OH% ≥ 15%) versus euvolemic (OH% < 15%) groups. Linear regression analysis was performed to explore relationships between the degree of OH and inflammatory indicators. FINDINGS: The cohort represented an all-European population with a mean age of 60.9 ± 14.7 years and prevalence of diabetes mellitus of 27%. The entire cohort's OH% was 14.9% ± 5.1% (range -11.1% to 39.0%); further, the <15% group of patients' OH% was 8.0% ± 8.5% versus 20.9% ± 5.1% in the OH% ≥ 15% group (P < 0.0001). Forty-seven patients (53%) were overhydrated by traditional criteria (OH% ≥15%) and 20 patients (23%) were severely overhydrated (OH% > 20%). The euvolemic (OH% <15%) versus severely overhydrated (OH% > 20%) groups had significant differences in markers of inflammation: CRP (9.8 ± 10.6 vs. 21.5 ± 21.6 mg/L, P < 0.006), serum albumin (37.6 ± 02.9 vs. 34.5 ± 5.3 g/L, P < 0.004), and NLR (3.06 ± 1.25 vs. 3.92 ± 2.04; P < 0.004). On linear regression, significant correlations were found between OH% and CRP (r = 0.2899, P < 0.006), serum albumin (r = -0.3670; P < 0.0005), RDW (r = 0.2992; P < 0.005), and NLR (r = 0.2900; P < 0.006). DISCUSSION: In a prevalent hemodiafiltration cohort, OH was common and correlated with several inflammatory markers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".