Effects of Medium Cut-Off Versus High-Flux Hemodialysis Membranes on Biomarkers: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Medium cut-off (MCO) membranes enhance large middle-molecule clearance while selectively retaining molecules >45 000 Da. OBJECTIVES: We undertook a systematic review and meta-analysis comparing the effects of MCO versus high-flux membranes on biomarkers. METHODS: We searched MEDLINE, Embase, CINAHL, Cochrane Library, and Web of Science from January 2015 to July 2020, and gray literature sources from 2017. We included randomized (RS) and nonrandomized studies (NRS) comparing MCO and high-flux membranes in adults (>18 years) receiving maintenance hemodialysis. We performed study selection, data extraction, and quality appraisals in duplicate and used the Grading of Recommendations Assessment, Development, and Evaluation framework. Outcomes included solute removal (plasma clearance or dialysate quantitation), reduction ratios, and predialysis serum concentrations for a range of prespecified large middle molecules. RESULTS: = 56%; high certainty) after 24 weeks. We also found with high certainty that MCO dialysis resulted in a large increase (standardized mean difference [SMD]> 2.0 for all) in β2-microglobulin, κ- and λ-free light chains, and myoglobin removal, resulting in moderate (SMD > 0.5) to large (SMD > 0.8) reductions in predialysis concentrations for all of these solutes. Medium cut-off dialysis increased the reduction ratio for tumor necrosis factor-alpha (TNF-α) by 7.7% (95% CI, 4.7 to 10.6; moderate certainty), and reduced predialysis TNF-α by SMD -0.48 (95% CI, -0.91 to -0.04; moderate certainty). We found with moderate certainty that MCO dialysis had little to no effect on predialysis interleukin-6 (IL-6) plasma concentrations. Medium cut-off dialysis reduced mRNA expression of TNF-α and IL-6 in peripheral leukocytes by MD -15% (95% CI, -19.6 to -10.4; moderate certainty) and -8.8% (95% CI, -10.2 to -7.4; moderate certainty), respectively. CONCLUSION: Medium cut-off dialysis increases the clearance of a wide range of large middle molecules and likely reduces inflammatory mediators with a concomitant transient reduction in serum albumin concentration. The net effect of MCO dialysis on large middle molecules could translate into important clinical effects.
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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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".