Distinct phenotypes of hospitalized patients with hyperkalemia by machine learning consensus clustering and associated mortality risks.

BACKGROUND: Hospitalized patients with hyperkalemia are heterogeneous, and cluster approaches may identify specific homogenous groups. This study aimed to cluster patients with hyperkalemia on admission using unsupervised machine learning (ML) consensus clustering approach, and to compare characteristics and outcomes among these distinct clusters. METHODS: Consensus cluster analysis was performed in 5133 hospitalized adult patients with admission hyperkalemia, based on available clinical and laboratory data. The standardized mean difference was used to identify each cluster's key clinical features. The association of hyperkalemia clusters with hospital and 1-year mortality was assessed using logistic and Cox proportional hazard regression. RESULTS: Three distinct clusters of hyperkalemia patients were identified using consensus cluster analysis: 1661 (32%) in cluster 1, 2455 (48%) in cluster 2 and 1017 (20%) in cluster 3. Cluster 1 was mainly characterized by older age, higher serum chloride and acute kidney injury (AKI), but lower estimated glomerular filtration rate (eGFR), serum bicarbonate and hemoglobin. Cluster 2 was mainly characterized by higher eGFR, serum bicarbonate and hemoglobin, but lower comorbidity burden, serum potassium and AKI. Cluster 3 was mainly characterized by higher comorbidity burden, particularly diabetes and end-stage kidney disease, AKI, serum potassium, anion gap, but lower eGFR, serum sodium, chloride and bicarbonate. Hospital and 1-year mortality risk was significantly different among the three identified clusters, with highest mortality in cluster 3, followed by cluster 1 and then cluster 2. CONCLUSION: In a heterogeneous cohort of hyperkalemia patients, three distinct clusters were identified using unsupervised ML. These three clusters had different clinical characteristics and outcomes.

Kidney allograft survival after acute rejection, the value of follow-up biopsies.

Kidney allografts are frequently lost due to alloimmunity. Still, the impact of early acute rejection (AR) on long-term graft survival is debated. We examined this relationship focusing on graft histology post-AR and assessing specific causes of graft loss. Included are 797 recipients without anti-donor antibodies (DSA) at transplant who had 1 year protocol biopsies. 15.2% of recipients had AR diagnosed by protocol or clinical biopsies. Compared to no-AR, all histologic types of AR led to abnormal histology in 1 and 2 years protocol biopsies, including more fibrosis + inflammation (6.3% vs. 21.9%), moderate/severe fibrosis (7.7% vs. 13.5%) and transplant glomerulopathy (1.4% vs. 8.3%, all p < 0.0001). AR were associated with reduced graft survival (HR = 3.07 (1.92-4.94), p < 0.0001). However, only those AR episodes followed by abnormal histology led to reduced graft survival. Early AR related to more late alloimmune-mediated graft losses, particularly transplant glomerulopathy (31% of losses). Related to this outcome, recipients with AR were more likely to have new DSA class II 1 year posttransplant (no-AR, 11.1%; AR, 21.2%, p = 0.039). In DSA negative recipients, early AR often leads to persistent graft inflammation and increases the risk of new DSA II production. Both of these post-AR events are associated with increased risk of graft loss.

Cardiac troponin T before and after kidney transplantation: determinants and implications for posttransplant survival.

Pretransplant cardiac troponin T(cTnT(pre) ) is a significant predictor of survival postkidney transplantation. We assessed correlates of cTnT levels pre- and posttransplantation and their relationship with recipient survival. A total of 1206 adult recipients of kidney grafts between 2000 and 2010 were included. Pretransplant cTnT was elevated (≥0.01 ng/mL) in 56.4%. Higher cTnT(pre) was associated with increased risk of posttransplant death/cardiac events independent of cardiovascular risk factors. Elevated cTnT(pre) declined rapidly posttransplant and was normal in 75% of recipients at 3 weeks and 88.6% at 1 year. Elevated posttransplant cTnT was associated with reduced patient survival (cTnT(3wks) : HR = 5.575, CI 3.207-9.692, p < 0.0001; cTnT(1year) : 3.664, 2.129-6.305, p < 0.0001) independent of age, diabetes, pretransplant dialysis, heart disease and allograft function. Negative/positive predictive values for high cTnT(3wks) were 91.4%/50% respectively. Normalization of cTnT posttransplant was associated with reduced risk. Variables related to elevated cTnT posttransplant included pretransplant diabetes, older age, time on dialysis, high cTnT(pre) and lower graft function. Patients with delayed graft function and those with GFR < 30 mL/min at 3 weeks were more likely to have an elevated cTnT(3wks) and remained at high risk. When allografts restore sufficient kidney function cTnT normalizes and patient survival improves. Lack of normalization of cTnT posttransplant identifies a group of individuals with high risk of death/cardiac events.