Abstract
Abstract Background and Aims Acute Kidney Injury (AKI) is one of the most frequent complications in Intensive Care Unit (ICU). It’s now clearly established that AKI may be associated with the installation and/or worsening of Chronic Kidney Disease (CKD). However, few patients are currently screened for CKD after hospitalization in the ICU. In addition, ICU patients often have changes in their volume of distribution and muscle mass that may interfere with plasma Creatinine (pCreat) dosing and thus the estimated GFR (eGFR) value using CKD-Epi equation. Method Since 2019, we are prospectively screening for CKD patients who developed moderate-to-severe AKI (KDIGO 2 and 3) in ICU. Patients are referred to Nephrology consultation within 2 to 3 months after discharge from the ICU. The screening for CKD is performed according to the GFR estimation using the CKD-Epi equation. In this cohort, we will assess the incidence of CKD after ICU discharge and factors associated with CKD installation and worsening (univariate and multivariate analysis). In addition, for some patients, we planned to measure GFR using Iohexol clearance to compare measured GFR (mGFR) to eGFR using both CKD-Epi equation and Cystatin C-based equations. Results So far, 43 patients have been referred in Nephrology consultation, 72% of male and a mean age of 62 (±16) years. The time between the ICU discharge and the consultation was 55 (±21) days. The main co-morbidities were diabetes (37%) and hypertension (58%). The mean eGFR before the ICU (basal renal function) was 78 (±24) ml/min/1.73m2 and the pCreat was 89 (±21) µmol/l. At baseline, twenty-one percent of the patients had an eGFR < 60 ml/min/1.73m2. The length of stay in the ICU was 14 (±14) days. Nearly half of the patients (47%) were ventilated and 56% received vasopressive drugs. Most of the patients (74%) developed KDIGO Stage 3 AKI and 26% developed Stage 2 AKI. The mean entry pCreat was 252 (± 178) µmol/l, reaching a maximum of 382 (± 198) µmol/l during the hospitalization. Sixty percent of the patients underwent renal replacement therapy. The patients lost in average 10 kgs during the hospitalization. The pCreat at discharge was 175 µmol/l (± 175). At the time of the consultation, the eGFR was 70 (± 27) ml/min/1.73m2 with 35% of the patients with an eGFR < 60 ml/min/1.73m2. Univariate and multivariate analysis will be performed to evaluate the mains factors associated with CKD. At this time, 8 patients had a GFR measure using Iohexol. Mean mGFR was 32,8 (±14) ml/min/1,73m2, lower than the CKD-Epi (57±19), the CKD-Epi Cystatin (35±13) and the CKD-Creatinine-Cystatin (43±14). Compared to the mGFR, the CKD-Epi Cystatin equation appears to perform better with a bias of 4 ml/min/1.73m2 versus a bias of 24 ml/min/1.73m2 for the CKD-Epi equation and 12.7 ml/min/1.73m2 for the CKD-Epi Creatinine-Cystatin equation. Based on the Iohexol measure and the CKD-Epi Cystatin equation, all the patients (100%) had a GFR < 60 ml/min/1,73m2 against only 33% with the CKD-Epi equation. Conclusion In this analysis on the first 43 patients of our cohort, AKI seems to be associated with an increase of CKD 2 months after ICU discharge with 35% of patients with an eGFR below 60 ml/min/1,73m2. This proportion of CKD patients may be underestimated by the GFR estimation based on pCreat. Given the results of the analysis of our first 8 patients who have benefited from GFR measurement, Cystatin C-based equations may be an interesting tool to better assess renal function in this specific population.
Published Version
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