Prognostic significance of malnutrition scores in elderly patients for the prediction of contrast-induced acute kidney injury

Background Malnutrition reflects the general condition of a patient including physical condition, protein turnover, and immune competence. Contrast-induced acute kidney injury (CI-AKI) is a disorder that adversely affects the prognosis of older adults. In our study, we aimed to show the relationship between CI-AKI and malnutrition status in elderly patients over 65 years of age with chronic coronary artery disease (CAD). Methods Study enrolled 360 consecutive patients with coronary angiography performed because of chronic coronary artery disease. Patients pre-procedural and post-procedural blood samples were taken and prognostic nutritional index (PNI), controlling nutritional status (CONUT) score, and geriatric nutritional risk index (GNRI) malnutrition scores were calculated. Results The median age of the patients included in the study was 69 (67-72, IQR) and CI-AKI was seen in 91 (25.2%) patients. Univariate regression analysis showed that age, diabetes mellitus, baseline creatinine, body weight-adapted contrast agent, haemoglobin, left ventricular ejection fraction, CONUT score, PNI score, and GNRI score were independent predictors of CI-AKI. In model 1, increase in CONUT score (2 to 5) (OR: 3.21 (2.11-4.88), in model 2, increase in PNI score (37.4 to 45) (OR: 0.34, (0.24-0.49)), and in model 3, increase in GNRI score (89.5 to 103.8) (OR: 0.55, (0.38-0.81)) were independently associated with the presence of CI-AKI. PNI showed better results than other models in discriminating the predictable capability for CI-AKI. Conclusion Malnutrition assessment of elderly patients before performing diagnostic or interventional coronary procedures could help clinicians to identify patients with elevated risk for CI-AKI.

Automated summary

In elderly patients with chronic coronary artery disease aged over 65, there is a relationship between malnutrition status and CI-AKI, with the PNI score demonstrating better predictive capability compared to other models. Conducting nutritional assessments before coronary procedures could help identify patients at higher risk for CI-AKI.