Nutritional Status is Associated With Preserved Kidney Function in Patients With Autosomal Dominant Polycystic Kidney Disease.

OBJECTIVE: Malnutrition is a common complication in autosomal dominant polycystic kidney disease (ADPKD). We examined whether nutritional status is associated with the preservation of kidney function, using a cohort of typical ADPKD. METHODS: We enrolled ambulatory ADPKD patients in 9 tertiary medical centers in Korea from May 2019 to December 2021. We excluded patients who were aged less than 18 years, who had known end-stage kidney disease at the time of enrollment, who had a diagnosis of atypical ADPKD, and who were Tolvaptan users. The primary outcome was an estimated glomerular filtration rate (eGFR) decline >3 mL/min/1.73 m2, based on nutritional status assessed by subjective global assessment (SGA). We also evaluated an eGFR decline >1 mL/min/1.73 m2, an increase in urine protein-creatinine ratio (UPCR) > 0, and an increase in UPCR >0.3 as secondary outcomes, based on SGA after the 1-year follow-up. A logistic regression (LR) model was used to calculate the odds ratio (OR) for the primary outcome. Because there were differences in several baseline variables, such as Mayo classification, serum hemoglobin, serum creatinine, and UPCR between SGA groups, we matched propensity scores. RESULTS: In total, 805 patients were prospectively enrolled. Among them, 236 patients who had 1-year follow-up data and typical imaging findings were analyzed to evaluate the effect of nutritional status on kidney function. SGA was used to assess the nutritional status. The mean age was 45.0 ± 13.3 years, and 49.6% of the patients were female. The mean eGFR was 81.9 mL/min/1.73 m2. Among the 236 patients, 91 (38.6%) experienced a 1-year eGFR decline >3 mL/min/1.73 m2. When a multivariable LR was applied, SGA 3-6 was identified as a significant factor related to a 1-year eGFR decline >3 mL/min/1.73 m2 (adjusted OR = 1.22 [1.04-1.43]; P = .017). Despite matching propensity scores, the 1-year eGFR decline >3 mL/min/1.73 m2 was still higher in the SGA 3-6 group regardless of proteinuria. CONCLUSION: Good nutritional status is associated with better-preserved kidney function in non-obese typical ADPKD patients who do not take Tolvaptan.

Impact of delayed graft function on clinical outcomes in highly sensitized patients after deceased-donor kidney transplantation.

Background: We investigated whether the development of delayed graft function (DGF) in pre-sensitized patients affects the clinical outcomes after deceased-donor kidney transplantation (DDKT). Methods: The study included 709 kidney transplant recipients (KTRs) from three transplant centers. We divided KTRs into four subgroups (highly sensitized DGF, highly sensitized non-DGF, low-sensitized DGF, and low-sensitized non-DGF) according to panel reactive antibody level of 50%, or DGF development. We compared post-transplant clinical outcomes among the four subgroups. Results: Incidence of biopsy-proven acute rejection (BPAR) was higher in two highly sensitized subgroups than in low-sensitized subgroups. It tended to be higher in highly sensitized DGF subgroups than in the highly sensitized non-DGF subgroups. In addition, the highly sensitized DGF subgroup showed the highest risk for BPAR (hazard ratio, 3.051; P=0.005) and independently predicted BPAR. Allograft function was lower in the two DGF subgroups than in the non-DGF subgroup until one month after transplantation, but thereafter it was similar. Death-censored graft loss rates and patient mortality tended to be low when DGF developed, but it did not reach statistical significance. Conclusions: DGF development in highly sensitized patients increases the risk for BPAR in DDKT compared with patients without DGF, suggesting the need for strict monitoring and management of such cases.

Structured Learning of Gaussian Graphical Models.

We consider estimation of multiple high-dimensional Gaussian graphical models corresponding to a single set of nodes under several distinct conditions. We assume that most aspects of the networks are shared, but that there are some structured differences between them. Specifically, the network differences are generated from node perturbations: a few nodes are perturbed across networks, and most or all edges stemming from such nodes differ between networks. This corresponds to a simple model for the mechanism underlying many cancers, in which the gene regulatory network is disrupted due to the aberrant activity of a few specific genes. We propose to solve this problem using the perturbed-node joint graphical lasso, a convex optimization problem that is based upon the use of a row-column overlap norm penalty. We then solve the convex problem using an alternating directions method of multipliers algorithm. Our proposal is illustrated on synthetic data and on an application to brain cancer gene expression data.