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Updated: May 13, 2026

Measurement of Tissue Oxygenation Using Near-Infrared Spectroscopy in Patients Undergoing Hemodialysis
Published on: October 2, 2020
Association between inflammatory markers and mortality in hemodialysis patients
Cigdem Cindoglu1, Burcu Beyazgül2, Derya Abuşka3
1Harran University, Faculty of Medicine, Department of Internal Medicine, Sanliurfa, Turkey.
Introduction:
This study aimed to evaluate the association between mortality and biomarkers reflecting inflammatory and nutritional status in hemodialysis (HD) patients, including the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein-to-albumin ratio (CAR), hemoglobin, albumin, lymphocyte and platelet (HALP) score, and prognostic nutritional index (PNI).
Methods:
This retrospective cohort study included 135 patients on routine HD. Baseline sociodemographic data, complete blood count, and biochemical parameters were recorded. Patients were followed for one year and classified as survivors or non-survivors. Predictors of mortality were analyzed using logistic regression (Enter method), with multicollinearity assessed by the variance inflation factor (VIF) and tolerance statistics.
Results:
The mean age of the patients included in the study was 55.2 ± 16.6 years, and 47.4% were male. In univariate analyses, age, albumin, calcium, CRP, white blood cell count, neutrophil count, hematocrit, hemoglobin, SII, NLR, CAR, and PNI were found to be significantly associated with survival (all p < 0.05). In the multivariate logistic regression analysis, only CAR (aOR = 1.374; 95% CI 1.011-1.869), PNI (aOR = 0.861; 95% CI 0.775-0.956), and hemoglobin (aOR = 0.725; 95% CI 0.532-0.988) were identified as independent predictors. The model's accuracy rate was 82%, and the AUC value was calculated as 0.87.
Conclusion:
Our study demonstrated that easily accessible and low-cost parameters, particularly CAR and PNI, are clinically valuable in predicting survival. The identification of hemoglobin levels as an independent predictor further supports the prognostic significance of hematological parameters. This study may serve as a basis for future research on the prognostic use of these biomarkers, emphasizing the need for large-scale and prospective studies.
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