Association of neutrophil-to-lymphocyte ratio and hemodialysis access failure in patients with end stage renal disease: A systematic review and meta-analysis
Bibliographic record
Abstract
This systematic review and meta-analysis aimed to assess the association of neutrophil-to-lymphocyte ratio (NLR) with an elevated risk of vascular access failure in end-stage renal disease (ESRD) patients undergoing hemodialysis. A comprehensive database search of MEDLINE (via PubMed), Scopus, and Cochrane Central was performed. Studies reporting the values of NLR in both functional and non-functional AVF groups in ESRD patients were selected. Quality assessment was performed using the Modified Newcastle-Ottawa scale for observational studies. Meta-analysis was performed using an inverse variance random effects model. Seven observational studies met the inclusion criteria, including 1313 participants with 554 cases and 759 controls. Pooled results showed significantly high NLR levels in patients with non-functional arteriovenous fistula (AVF) compared to functional AVF (SMD = 1.19, 95% CI = 0.74-1.65, p < 0.001). Subgroup analysis confirmed the consistency of the association between NLR and AVF failure across study design (SMD = 1.76, 95% CI = 0.78-2.73, p = 0.0004 in prospective vs SMD = 0.87, 95% CI = 0.42-1.32, p = 0.0001 in retrospective studies), etiology (SMD = 1.63, 95% CI = 0.75-2.52, p = 0.0003 in stenosis or thrombosis; and SMD = 0.80, 95% CI = 0.27-1.34, p = 0.003 in failure to mature of AVF), and NLR measurement timing (SMD = 0.98, 95% CI = 0.42-1.54, p = 0.0006 in preoperative vs SMD = 1.58, 95% CI = 0.47-2.69, p = 0.005 in postoperative NLR). The pooled odds ratio revealed high NLR values as a significant predictor of AVF failure in ESRD patients (OR = 3.91, 95% CI = 1.91-7.98, p = 0.0002). The pooled sensitivity and specificity were 89.72% (95% CI = 77.51%-95.67%) and 72.95% (95% CI = 63.82%-80.47%), respectively. The high NLR is a useful and predictive marker for AVF failure in hemodialysis patients. Future studies should prioritize larger cohort studies to validate and reinforce these observations.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.037 |
| Bibliometrics | 0.007 | 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) | 0.002 | 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".