MO956: Sarcopenia Predicts Mortality in Renal Transplant Candidates. (3rd May 2022)

• Record Type: Journal Article
• Authors: Coban, Harun; Barutcu Atas, Dilek; Kursun, Meltem; Tugcu, Murat; Asicioglu, Ebru; Hakki Arikan, Izzet; Cimsit, Canan; Serhan Tuglular, Z.; Velioglu, Arzu
• Is Part Of: Nephrology dialysis transplantation. Volume 37(2022)Supplement 3
• Publication Date: 2022-05-03
• Subjects: Nephrology -- Periodicals; Hemodialysis -- Periodicals; Kidneys -- Transplantation -- Periodicals; Hemodialysis; Kidneys -- Transplantation; Nephrology; Periodicals; 616.61
• DOI: 10.1093/ndt/gfac087.014
• Languages: English
• ISSNs: 0931-0509

Abstract

Abstract: BACKGROUND AND AIMS: Sarcopenia is common in chronic kidney disease (CKD) and is associated with increased mortality and morbidity. Sarcopenia in CKD can be defined as a decreased muscle mass, mainly due to the catabolic state caused by the uremic environment. Malnutrition and inflammation are also common in sarcopenic patients. In this study, we aimed to investigate the prevalence of sarcopenia defined as low muscle mass determined by Psoas Muscle Index (PMI) in waitlisted end-stage renal disease (ESRD) patients and its association between 'Prognostic Nutritional Index (PNI)', 'C-reactive protein (CRP) to Albumin Ratio (CAR)' and mortality. METHOD: ESRD patients registered to national kidney transplant waiting list and had abdomen CT at admission were included in the study. Kidney donor candidates were constituted as healthy controls. PMI ​​(cm 2 /m 2 ) were calculated by proportioning the psoas muscle area detected in the abdomen CT with the square of the height. The PMI of the controls at the fifth percentile according to gender was accepted as the limit value for sarcopenia. PNI and CAR were calculated using albumin, CRP and absolute lymphocyte count. The associations between PMI, PNI, CAR and all-cause mortality were investigated. RESULTS: A total of 162 ESRD patients and 87 age matched healthy controls were included in the study. The mean age of the patients was 44.7 ± 14.2 years and follow-up time was 3.37 (0.35–9.60) years. The mean PMI were similar between the groups (5.24 ± 1.71 versus 5.48 ± 1.87 cm 2 /m 2 P = 0.302). While prevalence of sarcopenia (16.7% versus 3.4%, P = 0.002) and CAR [1.47 (0.12–37.10) versus 0.74 (0.21–10.20), P < 0.001] was higher; PNI [40 (20.4–52.2) versus 44 (36.1–53.0), P < 0.001] was lower in ESRD patients than controls. When ESRD patients compared according to sarcopenia PMI [3.45 ± 0.9 versus 5.59 ± 1.6, P < 0.001] and PNI [39 (20.4–51) versus 41 (23–52.2), P = 0.005] was significantly lower and CAR [2.03 (0.28–34.65) versus 1.28 (0.12–37.1), P = 0.041] was higher in sarcopenic ESRD group than non-sarcopenic ESRD group (Table 1 ). In the correlation analysis, PMI was positively correlated with PNI ​​( r = 0.246, P = 0.002), no correlated with CAR ( r = −0.061, P = 0.445). In the follow-up, 67 waitlisted patients had been transplanted. In the five-year survival analysis, the non-sarcopenic transplant group [95% CI: 4.612–5.123 versus 95% CI: 2.721–5.413, P = 0.001] had better survival than sarcopenic transplant group (Figure 1 ). Mortality rates were similar in both sarcopenic transplant group and non-sarcopenic-non-transplant group. Multivariate regression analysis showed that sarcopenia (HR: 10.277, 95% CI: 3.912–27.000, P < 0.001), not having a transplant (HR: 3.949, 95% CI: 1.301–11.993, P = 0.015), low PNI (HR: 3.532, 95% CI: 1.303–9.574, P = 0.013) and duration of renal replacement therapy (HR: 1.009, 95% CI: 1.002–1.015, P = 0.008) were independent risk factors for mortality in all ESRD group. CONCLUSION: In this study we observed that sarcopenia, as defined by low muscle mass, is almost seen five times more frequent in ESRD patients than controls and positively correlated with PNI. Sarcopenia is an independent risk factor for mortality in waitlisted patients.