Diabetes mellitus: Complex interplay between metformin, AKI and lactic acidosis.

Debate exists regarding the safety of metformin and the risk of metformin-associated lactic acidosis, particularly in the setting of kidney dysfunction. Data from two studies examining the interplay between metformin, acute kidney injury, and complications including lactic acidosis suggest that metformin should be used conservatively in patients with kidney dysfunction

Infrequent dialysis: a new paradigm for hemodialysis initiation.

Nearly a half-century ago, the thrice-weekly hemodialysis schedule was empirically established as a means to provide an adequate dialysis dose while also treating the greatest number of end-stage renal disease (ESRD) patients using limited resources. Landmark trials of hemodialysis adequacy have historically been anchored to thrice-weekly regimens, but a recent randomized controlled trial demonstrated that frequent hemodialysis (six times per week) confers cardiovascular and survival benefits. Based on these collective data and experience, clinical practice guidelines advise against a less than thrice-weekly treatment schedule in patients without residual renal function, yet provide limited guidance on the optimal treatment frequency when substantial native kidney function is present. Thus, during the transition from Stage 5 chronic kidney disease to ESRD, the current paradigm is to initiate hemodialysis on a "full-dose" thrice-weekly regimen even among patients with substantial residual renal function. However, emerging data suggest that frequent hemodialysis accelerates residual renal function decline, and infrequent regimens may provide better preservation of native kidney function. Given the high mortality rates during the first 6 months of hemodialysis and the survival benefits of preserved native kidney function, initiation with twice-weekly treatment schedules ("infrequent hemodialysis") with an incremental increase in frequency over time may provide an opportunity to optimize patient survival. This review outlines the clinical benefits of post-hemodialysis residual renal function, studies of twice-weekly treatment regimens, and the potential risks and benefits of infrequent hemodialysis

High-Dimensional Fixed Effects Profiling Models and Applications in End-Stage Kidney Disease Patients: Current State and Future Directions

Profiling analysis aims to evaluate health care providers, including hospitals, nursing homes, or dialysis facilities among others with respect to a patient outcome, such as 30-day unplanned hospital readmission or mortality. Fixed effects (FE) profiling models have been developed over the last decade, motivated by the overall need to (a) improve accurate identification or “flagging” of under-performing providers, (b) relax assumptions inherent in random effects (RE) profiling models, and (c) take into consideration the unique disease characteristics and care/treatment processes of end-stage kidney disease (ESKD) patients on dialysis. In this paper, we review the current state of FE methodologies and their rationale in the ESKD population and illustrate applications in four key areas: profiling dialysis facilities for (1) patient hospitalizations over time (longitudinally) using standardized dynamic readmission ratio (SDRR), (2) identification of dialysis facility characteristics (e.g., staffing level) that contribute to hospital readmission, and (3) adverse recurrent events using standardized event ratio (SER). Also, we examine the operating characteristics with a focus on FE profiling models. Throughout these areas of applications to the ESKD population, we identify challenges for future research in both methodology and clinical studies

Multivariate spatiotemporal functional principal component analysis for modeling hospitalization and mortality rates in the dialysis population.

Dialysis patients experience frequent hospitalizations and a higher mortality rate compared to other Medicare populations, in whom hospitalizations are a major contributor to morbidity, mortality, and healthcare costs. Patients also typically remain on dialysis for the duration of their lives or until kidney transplantation. Hence, there is growing interest in studying the spatiotemporal trends in the correlated outcomes of hospitalization and mortality among dialysis patients as a function of time starting from transition to dialysis across the United States Utilizing national data from the United States Renal Data System (USRDS), we propose a novel multivariate spatiotemporal functional principal component analysis model to study the joint spatiotemporal patterns of hospitalization and mortality rates among dialysis patients. The proposal is based on a multivariate Karhunen-Loéve expansion that describes leading directions of variation across time and induces spatial correlations among region-specific scores. An efficient estimation procedure is proposed using only univariate principal components decompositions and a Markov Chain Monte Carlo framework for targeting the spatial correlations. The finite sample performance of the proposed method is studied through simulations. Novel applications to the USRDS data highlight hot spots across the United States with higher hospitalization and/or mortality rates and time periods of elevated risk