Estimating glomerular filtration rate in patients with acute kidney injury: a prospective multicenter study of diagnostic accuracy

Toward Equitable Kidney Function Estimation in Critical Care Practice: Guidance From the Society of Critical Care Medicine's Diversity, Equity, and Inclusion in Renal Clinical Practice Task Force

OBJECTIVES

Accurate glomerular filtration rate (GFR) assessment is essential in critically ill patients. GFR is often estimated using creatinine-based equations, which require surrogates for muscle mass such as age and sex. Race has also been included in GFR equations, based on the assumption that Black individuals have genetically determined higher muscle mass. However, race-based GFR estimation has been questioned with the recognition that race is a poor surrogate for genetic ancestry, and racial health disparities are driven largely by socioeconomic factors. The American Society of Nephrology and the National Kidney Foundation (ASN/NKF) recommend widespread adoption of new "race-free" creatinine equations, and increased use of cystatin C as a race-agnostic GFR biomarker.

DATA SOURCES

Literature review and expert consensus.

STUDY SELECTION

English language publications evaluating GFR assessment and racial disparities.

DATA EXTRACTION

We provide an overview of the ASN/NKF recommendations. We then apply an Implementation science methodology to identify facilitators and barriers to implementation of the ASN/NKF recommendations into critical care settings and identify evidence-based implementation strategies. Last, we highlight research priorities for advancing GFR estimation in critically ill patients.

DATA SYNTHESIS

Implementation of the new creatinine-based GFR equation is facilitated by low cost and relative ease of incorporation into electronic health records. The key barrier to implementation is a lack of direct evidence in critically ill patients. Additional barriers to implementing cystatin C-based GFR estimation include higher cost and lack of test availability in most laboratories. Further, cystatin C concentrations are influenced by inflammation, which complicates interpretation.

CONCLUSIONS

The lack of direct evidence in critically ill patients is a key barrier to broad implementation of newly developed "race-free" GFR equations. Additional research evaluating GFR equations in critically ill patients and novel approaches to dynamic kidney function estimation is required to advance equitable GFR assessment in this vulnerable population.

Estimating Changes in Glomerular Filtration Rate With Fluorescein Isothiocyanate-Sinistrin During Renal Replacement Therapy

Excreted exclusively by the kidneys, fluorescein isothiocyanate (FITC)-sinistrin can be used to measure glomerular filtration rate (GFR) and is detectable transdermally. Determination of changes in native kidney GFR (NK-GFR) in patients with acute kidney injury, particularly during continuous renal replacement therapy, improves clinical decision-making capability. To test feasibility of measuring changes in NK-GFR during CRRT with FITC-sinistrin, in vitro circuits (n = 2) were utilized to simultaneously clear FITC-sinistrin by removal of ultrafiltrate at varying rates, simulating kidney function, and by dialysis at a constant rate. Clearance calculated by fluorescence-measuring devices on the circuit showed good agreement with clearance calculated from assay of fluid samples ( R2 = 0.949). In vivo feasibility was studied by dialyzing anesthetized pigs (n = 3) and measuring FITC-sinistrin clearance during progression from normal, to unilaterally, then bilaterally nephrectomized. FITC-sinistrin clearance was reduced in vitro , when ultrafiltrate was decreased or with successive nephrectomies in vivo . Transdermal readers showed 100% sensitivity in detecting a decrease in NK-GFR in pigs with a bias of 6.5 ± 13.4% between transdermal-derived GFR (tGFR) and plasma-measured methods determining proportional changes in clearance. Clearance of FITC-sinistrin by dialysis remained consistent. In patients receiving a constant dialysis prescription, transdermal measurement of FITC-sinistrin can detect relative changes in NK-GFR.

Machine-learning enhancement of urine dipstick tests for chronic kidney disease detection

OBJECTIVE

Screening for chronic kidney disease (CKD) requires an estimated glomerular filtration rate (eGFR, mL/min/1.73 m2) from a blood sample and a proteinuria level from a urinalysis. We developed machine-learning models to detect CKD without blood collection, predicting an eGFR less than 60 (eGFR60 model) or 45 (eGFR45 model) using a urine dipstick test.

MATERIALS AND METHODS

The electronic health record data (n = 220 018) obtained from university hospitals were used for XGBoost-derived model construction. The model variables were age, sex, and 10 measurements from the urine dipstick test. The models were validated using health checkup center data (n = 74 380) and nationwide public data (KNHANES data, n = 62 945) for the general population in Korea.

RESULTS

The models comprised 7 features, including age, sex, and 5 urine dipstick measurements (protein, blood, glucose, pH, and specific gravity). The internal and external areas under the curve (AUCs) of the eGFR60 model were 0.90 or higher, and a higher AUC for the eGFR45 model was obtained. For the eGFR60 model on KNHANES data, the sensitivity was 0.93 or 0.80, and the specificity was 0.86 or 0.85 in ages less than 65 with proteinuria (nondiabetes or diabetes, respectively). Nonproteinuric CKD could be detected in nondiabetic patients under the age of 65 with a sensitivity of 0.88 and specificity of 0.71.

DISCUSSION AND CONCLUSIONS

The model performance differed across subgroups by age, proteinuria, and diabetes. The CKD progression risk can be assessed with the eGFR models using the levels of eGFR decrease and proteinuria. The machine-learning-enhanced urine-dipstick test can become a point-of-care test to promote public health by screening CKD and ranking its risk of progression.

Measured versus estimated creatinine clearance in critically ill patients with acute kidney injury: an observational study

Background

Acute kidney injury (AKI) commonly occurs in critically ill patients. Estimation of renal function and antibiotics dose adjustment in patients with AKI is a challenging issue.

Methods

Urinary creatinine clearance was measured in a 6-hour urine collection from patients with acute kidney injuries. The correlations between different formulas including the modified Cockcroft-Gault, modification of diet in renal disease, chronic kidney disease-epidemiology collaboration, Jelliffe, kinetic-glomerular filtration rate (GFR), Brater, and Chiou formulas were considered. The pattern of the prescribed antimicrobial agents was also compared with the patterns in the available resources.

Results

Ninety-five patients with acute kidney injuries were included in the research. The mean age of the participants was 63.11±17.58 years old. The most patients (77.89%) were in stage 1 of AKI according to the Acute Kidney Injury Network criteria, followed by stage 2 (14.73%) and stage 3 (7.36), respectively. None of the formulations had a high or very high correlation with the measured creatinine clearance. In stage 1, Chiou (r=0.26), and in stage 2 and 3, kinetic-GFR (r=0.76 and r=0.37) had the highest correlation coefficient. Antibiotic over- and under-dosing were frequently observed in the study.

Conclusions

The results showed that none of the static methods can predict the measured creatinine clearance in the critically ill patients. The dynamic methods such as kinetic-GFR can be helpful for patients who do not receive diuretics and vasopressors. Further studies are needed to confirm our results.

Acute kidney injury: Incidence, risk factors, and outcomes in severe COVID-19 patients

Background

COVID-19 is a multisystemic disorder that frequently causes acute kidney injury (AKI). However, the precise clinical and biochemical variables associated with AKI progression in patients with severe COVID-19 remain unclear.

Methods

We performed a retrospective study on 278 hospitalized patients who were admitted to the ward and intensive care unit (ICU) with COVID-19 between March 2020 and June 2020, at the University Hospital, São Paulo, Brazil. Patients aged ≥ 18 years with COVID-19 confirmed on RT-PCR were included. AKI was defined according to the Kidney Disease Improving Global Outcomes (KDIGO) criteria. We evaluated the incidence of AKI, several clinical variables, medicines used, and outcomes in two sub-groups: COVID-19 patients with AKI (Cov-AKI), and COVID-19 patients without AKI (non-AKI). Univariate and multivariate analyses were performed.

Results

First, an elevated incidence of AKI (71.2%) was identified, distributed across different stages of the KDIGO criteria. We further observed higher levels of creatinine, C-reactive protein (CRP), leukocytes, neutrophils, monocytes, and neutrophil-to-lymphocyte ratio (NLR) in the Cov-AKI group than in the non-AKI group, at hospital admission. On univariate analysis, Cov-AKI was associated with older age (>62 years), hypertension, CRP, MCV, leucocytes, neutrophils, NLR, combined hydroxychloroquine and azithromycin treatment, use of mechanical ventilation, and vasoactive drugs. Multivariate analysis showed that hypertension and the use of vasoactive drugs were independently associated with a risk of higher AKI in COVID-19 patients. Finally, we preferentially found an altered erythrocyte and leukocyte cellular profile in the Cov-AKI group compared to the non-AKI group, at hospital discharge.

Conclusions

In our study, the development of AKI in patients with severe COVID-19 was related to inflammatory blood markers and therapy with hydroxychloroquine/azithromycin, with vasopressor requirement and hypertension considered potential risk factors. Thus, attention to the protocol, hypertension, and some blood markers may help assist doctors with decision-making for the management of COVID-19 patients with AKI.