Kashani, Kianoush B

ABSTRACT Background Critically ill patients with severe acute kidney injury (AKI) requiring kidney replacement therapy (KRT) have a grim prognosis. Recently, multiple studies focused on the impact of KRT initiation time [i.e., accelerated versus watchful waiting KRT initiation (WWS-KRT)] on patient outcomes. We aim to review the results of all related clinical trials. Methods In this systematic review, we searched all relevant randomized clinical trials from January 2000 to April 2021. We assessed the impacts of accelerated versus WWS-KRT on KRT dependence, KRT-free days, mortality and adverse events, including hypotension, infection, arrhythmia and bleeding. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. Results A total of 4932 critically ill patients with AKI from 10 randomized clinical trials were included in this analysis. The overall 28-day mortality rate was 38.5%. The 28-day KRT-dependence rate was 13.0%. The overall incident of KRT in the accelerated group was 97.4% and 62.8% in the WWS-KRT group. KRT in the accelerated group started 36.7 h earlier than the WWS-KRT group. The two groups had similar risks of 28-day [pooled log odds ratio (OR) 1.001, P = 0.982] and 90-day (OR 0.999, P = 0.991) mortality rates. The accelerated group had a significantly higher risk of 90-day KRT dependence (OR 1.589, P = 0.007), hypotension (OR 1.687, P < 0.001) and infection (OR 1.38, P = 0.04) compared with the WWS-KRT group. Conclusions This meta-analysis revealed that accelerated KRT leads to a higher probability of 90-day KRT dependence and dialysis-related complications without any impact on mortality rate when compared with WWS-KRT. Therefore, we suggest the WWS-KRT strategy for critically ill patients.

Background: We aimed to cluster patients with acute kidney injury at hospital admission into clinically distinct subtypes using an unsupervised machine learning approach and assess the mortality risk among the distinct clusters. Methods: We performed consensus clustering analysis based on demographic information, principal diagnoses, comorbidities, and laboratory data among 4289 hospitalized adult patients with acute kidney injury at admission. The standardized difference of each variable was calculated to identify each cluster’s key features. We assessed the association of each acute kidney injury cluster with hospital and one-year mortality. Results: Consensus clustering analysis identified four distinct clusters. There were 1201 (28%) patients in cluster 1, 1396 (33%) patients in cluster 2, 1191 (28%) patients in cluster 3, and 501 (12%) patients in cluster 4. Cluster 1 patients were the youngest and had the least comorbidities. Cluster 2 and cluster 3 patients were older and had lower baseline kidney function. Cluster 2 patients had lower serum bicarbonate, strong ion difference, and hemoglobin, but higher serum chloride, whereas cluster 3 patients had lower serum chloride but higher serum bicarbonate and strong ion difference. Cluster 4 patients were younger and more likely to be admitted for genitourinary disease and infectious disease but less likely to be admitted for cardiovascular disease. Cluster 4 patients also had more severe acute kidney injury, lower serum sodium, serum chloride, and serum bicarbonate, but higher serum potassium and anion gap. Cluster 2, 3, and 4 patients had significantly higher hospital and one-year mortality than cluster 1 patients (p < 0.001). Conclusion: Our study demonstrated using machine learning consensus clustering analysis to characterize a heterogeneous cohort of patients with acute kidney injury on hospital admission into four clinically distinct clusters with different associated mortality risks.

Background and Objectives: Despite the association between hyperchloremia and adverse outcomes, mortality risks among patients with hyperchloremia have not consistently been observed among all studies with different patient populations with hyperchloremia. The objective of this study was to characterize hyperchloremic patients at hospital admission into clusters using an unsupervised machine learning approach and to evaluate the mortality risk among these distinct clusters. Materials and Methods: We performed consensus cluster analysis based on demographic information, principal diagnoses, comorbidities, and laboratory data among 11,394 hospitalized adult patients with admission serum chloride of >108 mEq/L. We calculated the standardized mean difference of each variable to identify each cluster’s key features. We assessed the association of each hyperchloremia cluster with hospital and one-year mortality. Results: There were three distinct clusters of patients with admission hyperchloremia: 3237 (28%), 4059 (36%), and 4098 (36%) patients in clusters 1 through 3, respectively. Cluster 1 was characterized by higher serum chloride but lower serum sodium, bicarbonate, hemoglobin, and albumin. Cluster 2 was characterized by younger age, lower comorbidity score, lower serum chloride, and higher estimated glomerular filtration (eGFR), hemoglobin, and albumin. Cluster 3 was characterized by older age, higher comorbidity score, higher serum sodium, potassium, and lower eGFR. Compared with cluster 2, odds ratios for hospital mortality were 3.60 (95% CI 2.33–5.56) for cluster 1, and 4.83 (95% CI 3.21–7.28) for cluster 3, whereas hazard ratios for one-year mortality were 4.49 (95% CI 3.53–5.70) for cluster 1 and 6.96 (95% CI 5.56–8.72) for cluster 3. Conclusions: Our cluster analysis identified three clinically distinct phenotypes with differing mortality risks in hospitalized patients with admission hyperchloremia.

AbstractHigh‐dose methotrexate (HDMTX) pharmacokinetics (PKs), including the best estimated glomerular filtration rate (eGFR) equation that reflects methotrexate (MTX) clearance, requires investigation. This prospective, observational, single‐center study evaluated adult patients with lymphoma treated with HDMTX. Samples were collected at predefined time points up to 96 h postinfusion. MTX and 7‐hydroxy‐MTX PKs were estimated by standard noncompartmental analysis. Linear regression determined which serum creatinine‐ or cystatin C‐based eGFR equation best predicted MTX clearance. The 80 included patients had a median (interquartile range [IQR]) age of 68.6 years (IQR 59.2–75.6), 54 (67.5%) were men, and 74 (92.5%) were White. The median (IQR) dose of MTX was 7.6 (IQR 4.8–11.3) grams. Median clearance was similar across three dosing levels at 4.5–5.6 L/h and was consistent with linear PKs. Liver function, weight, age, sex, concomitant chemotherapy, and number of previous MTX doses did not impact clearance. MTX area under the curve (AUC) values varied over a fourfold range and appeared to increase in proportion to the dose. The eGFRcys (ml/min) equation most closely correlated with MTX clearance in both the entire cohort and after excluding outlier MTX clearance values (r = 0.31 and 0.51, respectively). HDMTX as a 4‐h infusion displays high interpatient pharmacokinetic variability. Population PK modeling to optimize MTX AUC attainment requires further evaluation. The cystatin C‐based eGFR equation most closely estimated MTX clearance and should be investigated for dosing and monitoring in adults requiring MTX as part of lymphoma management.

Advances in our understanding of uremic retention solutes, and improvements in hemodialysis membranes and other techniques designed to remove uremic retention solutes, offer opportunities to readdress the definition and classification of uremic toxins. A consensus conference was held to develop recommendations for an updated definition and classification scheme on the basis of a holistic approach that incorporates physicochemical characteristics and dialytic removal patterns of uremic retention solutes and their linkage to clinical symptoms and outcomes. The major focus is on the removal of uremic retention solutes by hemodialysis. The identification of representative biomarkers for different classes of uremic retention solutes and their correlation to clinical symptoms and outcomes may facilitate personalized and targeted dialysis prescriptions to improve quality of life, morbidity, and mortality. Recommendations for areas of future research were also formulated, aimed at improving understanding of uremic solutes and improving outcomes in patients with CKD.

Abstract Early diagnosis of AKI and preventive measures can likely decrease the severity of the injury and improve patient outcomes. Current hemodynamic monitoring variables, including BP, heart and respiratory rates, temperature, and oxygenation status, have been used to identify patients at high risk for AKI. Despite the widespread use of such variables, their ability to accurately and timely detect patients who are high risk has been questioned. Therefore, there is a critical need to develop and validate tools that can measure new and more kidney-specific hemodynamic and laboratory variables, potentially assisting with AKI risk stratification, implementing appropriate and timely preventive measures, and hopefully improved outcomes. The new ultrasonography techniques provide novel insights into kidney hemodynamics and potential management and/or therapeutic targets. Contrast-enhanced ultrasonography; Doppler flow patterns of hepatic veins, portal vein, and intrakidney veins; and ultrasound elastography are among approaches that may provide such information, particularly related to vascular changes in AKI, venous volume excess or congestion, and fluid tolerance. This review summarizes the current state of these techniques and their relevance to kidney hemodynamic management.

AbstractContinuous renal replacement therapy (CRRT) is the preferred extracorporeal kidney support therapy employed to support critically ill patients with acute or chronic kidney dysfunction in intensive care units. Significant heterogeneity in CRRT practice exists in part due to variable logistics, resources, and scarcity of evidence‐based CRRT practices. Importantly, homogenization of practice patterns by developing substantial evidence and effective dissemination among providers is essential for optimizing CRRT practices. The emphasis on quality of CRRT delivery has prompted identification of potential quality indicators, development of multifaceted quality improvement initiatives, effective computer science utilization, and a surge of multidisciplinary quality assurance teams that advocate for “best” CRRT practices. This manuscript provides an overview of quality improvement methodologies and reviews candidate quality indicators of CRRT and the impact of quality improvement on enhancing CRRT delivery practices.

Background: There are limited data on acute myocardial infarction with cardiogenic shock (AMI-CS) stratified by chronic kidney disease (CKD) stages. Objective: To assess clinical outcomes in AMI-CS stratified by CKD stages. Methods: A retrospective cohort of AMI-CS during 2005–2016 from the National Inpatient Sample was categorized as no CKD, CKD stage-III (CKD-III), CKD stage-IV (CKD-IV) and end-stage renal disease (ESRD). CKD-I/II were excluded. Outcomes included in-hospital mortality, use of coronary angiography, percutaneous coronary intervention (PCI) and mechanical circulatory support (MCS). We also evaluated acute kidney injury (AKI) and acute hemodialysis in non-ESRD admissions. Results: Of 372,412 AMI-CS admissions, CKD-III, CKD-IV and ESRD comprised 20,380 (5.5%), 7367 (2.0%) and 18,109 (4.9%), respectively. Admissions with CKD were, on average, older, of the White race, bearing Medicare insurance, of a lower socioeconomic stratum, with higher comorbidities, and higher rates of acute organ failure. Compared to the cohort without CKD, CKD-III, CKD-IV and ESRD had lower use of coronary angiography (72.7%, 67.1%, 56.9%, 61.1%), PCI (53.7%, 43.8%, 38.4%, 37.6%) and MCS (47.9%, 38.3%, 33.3%, 34.2%), respectively (all p < 0.001). AKI and acute hemodialysis use increased with increase in CKD stage (no CKD–38.5%, 2.6%; CKD-III–79.1%, 6.5%; CKD-IV–84.3%, 12.3%; p < 0.001). ESRD (adjusted odds ratio [OR] 1.25 [95% confidence interval {CI} 1.21–1.31]; p < 0.001), but not CKD-III (OR 0.72 [95% CI 0.69–0.75); p < 0.001) or CKD-IV (OR 0.82 [95 CI 0.77–0.87] was predictive of in-hospital mortality. Conclusions: CKD/ESRD is associated with lower use of evidence-based therapies. ESRD was an independent predictor of higher in-hospital mortality in AMI-CS.