Silent AR is common during DGF. Prolonged DGF is associated with reduced graft survival after kidney transplantation, and much of this association can be explained by silent AR. In the absence of data from randomized trials, protocol biopsies and treatment of silent AR during prolonged DGF appear to be warranted.

BACKGROUND Hepatorenal syndrome (HRS) is a life-threatening condition among patients with advanced liver disease. Data trends specific to hospital mortality and hospital admission resource utilization for HRS remain limited. AIM To assess the temporal trend in mortality and identify the predictors for mortality among hospital admissions for HRS in the United States. METHODS We used the National Inpatient Sample database to identify an unweighted sample of 4938 hospital admissions for HRS from 2005 to 2014 (weighted sample of 23973 admissions). The primary outcomes were temporal trends in mortality as well as predictors for hospital mortality. We estimated odds ratios from multi-level mixed effect logistic regression to identify patient characteristics and treatments associated with hospital mortality. RESULTS Overall hospital mortality was 32%. Hospital mortality decreased from 44% in 2005 to 24% in 2014 ( P < 0.001), while there was an increase in the rate of liver transplantation ( P = 0.02), renal replacement therapy ( P < 0.001), length of hospital stay ( P < 0.001), and hospitalization cost ( P < 0.001). On multivariable analysis, older age, alcohol use, coagulopathy, neurological disorder, and need for mechanical ventilation predicted higher hospital mortality, whereas liver transplantation, transjugular intrahepatic portosystemic shunt, and abdominal paracentesis were associated with lower hospital mortality. CONCLUSION Although there was an increase in resource utilizations, hospital mortality among patients admitted for HRS significantly improved. Several predictors for hospital mortality were identified.

This study aims to evaluate the risk factors and the association of acute kidney injury with treatments, complications, outcomes, and resource utilization in patients hospitalized for heat stroke in the United States. Hospitalized patients from years 2003 to 2014 with a primary diagnosis of heat stroke were identified in the National Inpatient Sample dataset. End stage kidney disease patients were excluded. The occurrence of acute kidney injury during hospitalization was identified using the hospital diagnosis code. The associations between acute kidney injury and clinical characteristics, in-hospital treatments, outcomes, and resource utilization were assessed using multivariable analyses. A total of 3346 hospital admissions were included in the analysis. Acute kidney injury occurred in 1206 (36%) admissions, of which 49 (1.5%) required dialysis. The risk factors for acute kidney injury included age 20–39 years, African American race, obesity, chronic kidney disease, congestive heart failure, and rhabdomyolysis, whereas age <20 or ≥60 years were associated with lower risk of acute kidney injury. The need for mechanical ventilation and blood transfusion was higher when acute kidney injury occurred. Acute kidney injury was associated with electrolyte and acid-base derangements, sepsis, acute myocardial infarction, ventricular arrhythmia or cardiac arrest, respiratory, circulatory, liver, neurological, hematological failure, and in-hospital mortality. Length of hospital stay and hospitalization cost were higher in acute kidney injury patients. Approximately one third of heat stroke patients developed acute kidney injury during hospitalization. Acute kidney injury was associated with several complications, and higher mortality and resource utilization.

Introduction We aimed to assess the association between serum potassium and mortality in patients receiving continuous renal replacement therapy (CRRT). Methods We studied 1279 acute kidney injury patients receiving CRRT in a tertiary referral hospital in the United States. We used logistic regression to assess the association of serum potassium before CRRT and mean serum potassium during CRRT with 90‐day mortality after CRRT initiation, using serum potassium 4.0–4.4 mmol/L as reference group. Results Before CRRT, there was a U‐shaped association between serum potassium and 90‐day mortality. There was a significant increase in mortality when serum potassium before CRRT was ≤3.4 and ≥4.5 mmol/L. During CRRT, progressively increased mortality was noted when mean serum potassium was ≥4.5 mmol/L. The odds ratio of 90‐day mortality was significantly higher when mean serum potassium was ≥4.5 mmol/L. Conclusion Hypokalemia and hyperkalemia before CRRT and hyperkalemia during CRRT predicts 90‐day mortality.

No abstract

Background: This study aimed to determine the rates of inpatient palliative care service use and assess the impact of palliative care service use on in-hospital treatments and resource utilization in hospital admissions for hepatorenal syndrome. Methods: Using the National Inpatient Sample, hospital admissions with a primary diagnosis of hepatorenal syndrome were identified from 2003 through 2014. The primary outcome of interest was the temporal trend and predictors of inpatient palliative care service use. Logistic and linear regression was performed to assess the impact of inpatient palliative care service on in-hospital treatments and resource use. Results: Of 5571 hospital admissions for hepatorenal syndrome, palliative care services were used in 748 (13.4%) admissions. There was an increasing trend in the rate of palliative care service use, from 3.3% in 2003 to 21.1% in 2014 (p < 0.001). Older age, more recent year of hospitalization, acute liver failure, alcoholic cirrhosis, and hepatocellular carcinoma were predictive of increased palliative care service use, whereas race other than Caucasian, African American, and Hispanic and chronic kidney disease were predictive of decreased palliative care service use. Although hospital admission with palliative care service use had higher mortality, palliative care service was associated with lower use of invasive mechanical ventilation, blood product transfusion, paracentesis, renal replacement, vasopressor but higher DNR status. Palliative care services reduced mean length of hospital stay and hospitalization cost. Conclusion: Although there was a substantial increase in the use of palliative care service in hospitalizations for hepatorenal syndrome, inpatient palliative care service was still underutilized. The use of palliative care service was associated with reduced resource use.

Background: This study aimed to better characterize morbidly obese kidney transplant recipients, their clinical characteristics, and outcomes by using an unsupervised machine learning approach. Methods: Consensus cluster analysis was applied to OPTN/UNOS data from 2010 to 2019 based on recipient, donor, and transplant characteristics in kidney transplant recipients with a pre-transplant BMI ≥ 40 kg/m2. Key cluster characteristics were identified using the standardized mean difference. Post-transplant outcomes, including death-censored graft failure, patient death, and acute allograft rejection, were compared among the clusters. Results: Consensus clustering analysis identified 3204 kidney transplant recipients with a BMI ≥ 40 kg/m2. In this cohort, five clinically distinct clusters were identified. Cluster 1 recipients were predominantly white and non-sensitized, had a short dialysis time or were preemptive, and were more likely to receive living donor kidney transplants. Cluster 2 recipients were older and diabetic. They were likely to have been on dialysis >3 years and receive a standard KDPI deceased donor kidney. Cluster 3 recipients were young, black, and had kidney disease secondary to hypertension or glomerular disease. Cluster 3 recipients had >3 years of dialysis and received non-ECD, young, deceased donor kidney transplants with a KDPI < 85%. Cluster 4 recipients were diabetic with variable dialysis duration who either received non-ECD standard KDPI kidneys or living donor kidney transplants. Cluster 5 recipients were young retransplants that were sensitized. One-year patient survival in clusters 1, 2, 3, 4, and 5 was 98.0%, 94.4%, 98.5%, 98.7%, and 97%, and one-year death-censored graft survival was 98.1%, 93.0%, 96.1%, 98.8%, and 93.0%, respectively. Cluster 2 had the worst one-year patient survival. Clusters 2 and 5 had the worst one-year death-censored graft survival. Conclusions: With the application of unsupervised machine learning, variable post-transplant outcomes are observed among morbidly obese kidney transplant recipients. Recipients with earlier access to transplant and living donation show superior outcomes. Unexpectedly, reduced graft survival in cluster 3 recipients perhaps underscores socioeconomic access to post-transplant support and minorities being disadvantaged in access to preemptive and living donor transplants. Despite obesity-related concerns, one-year patient and graft survival were favorable in all clusters, and obesity itself should be reconsidered as a hard barrier to kidney transplantation.

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.