Effect of cool vs. warm dialysate on toxin removal: rationale and study design.

BACKGROUND: Cool dialysate is often recommended for prevention of intra-dialytic hypotensive episodes in maintenance hemodialysis (HD) patients. However, its effect on toxin removal is not studied. It is known that inter-compartmental resistance is the main barrier for toxin removal. Cool dialysate can potentially increase this resistance by vasoconstriction and thus impair the toxin removal. The aim of this trial is to compare the toxin removal outcome associated with cool vs. warm dialysate. METHOD/DESIGN: This study is based on the hypothesis that dialysate temperature, a potential maneuver to maintain hemodynamic stability during HD, may influence inter-compartmental resistance and hence, toxin removal. Only stable HD patients will be recruited for this study. The quantum of removed toxins will be assessed by the total spent dialysate, which is a gold standard to quantify the efficacy of a single dialysis session. Collected samples will be analyzed for urea, creatinine, phosphate, ß2-microglobulin, and uric acid. The study is a single center, self-controlled, randomized prospective clinical research where 20 study subjects will undergo 2 dialysis sessions: (a) cool dialysis with dialysate at 35.5°C, and (b) warm dialysis with dialysate at 37°C. Pre- and post-dialysis blood samples will be collected to quantify the dialysis adequacy and toxin reduction ratio. DISCUSSION: This is the first clinical research to investigate the effect of dialysate temperature on removal of both small and large-sized toxins. Successful completion of this research will provide important knowledge pertaining to dialysate temperature prescription. Results can also lead to the hypothesis that cool dialysate may help in by preventing intra-dialytic hypotensive episodes, but prolonged prescription of cool dialysate may lead to comorbidities associated with excess toxin accumulation. The new knowledge will encourage for personalized dialysate temperature profiling. TRIAL REGISTRATION: Clinicaltrials.gov Identifier--NCT02064153.

Personalized blood glucose models for exercise, meal and insulin interventions in type 1 diabetic children.

Modern healthcare is rapidly evolving towards a personalized, predictive, preventive and participatory approach of treatment to achieve better quality of life (QoL) in patients. Identification of personalized blood glucose (BG) prediction models incorporating the lifestyle interventions can help in devising optimal patient specific exercise, food, and insulin prescriptions, which in turn can prevent the risk of frequent hypoglycemic episodes and other diabetes complications. Hence, we propose a modeling methodology based on multi-input single-output time series models, to develop personalized BG models for 12 type 1 diabetic (T1D) children, using the clinical data from Diabetes Research in Children's Network. The multiple inputs needed to develop the proposed models were rate of perceived exertion (RPE) values (which quantify the exercise intensity), carbohydrate absorption dynamics, basal insulin infusion and bolus insulin absorption kinetics. Linear model classes like Box-Jenkins (1 patient), state space (1 patient) and process transfer function models (7 patients) of different orders were found to be the most suitable as the personalized models for 9 patients, whereas nonlinear Hammerstein-Wiener models of different orders were found to be the personalized models for 3 patients. Hence, inter-patient variability was captured by these models as each patient follows a different personalized model.

A regional blood flow model for ß2-microglobulin kinetics and for simulating intra-dialytic exercise effect.

A kinetic model based on first principles, for ß(2)-microglobulin, is presented to obtain precise parameter estimates for individual patient. To reduce the model complexity, the number of model parameters was reduced using a priori identifiability analysis. The model validity was confirmed with the clinical data of ten renal patients on post-dilution hemodiafiltration. The model fit resulted in toxin distribution volume (V(d)) of 14.22 ± 0.75 L, plasma fraction in extracellular compartment (f(P)) of 0.39 ± 0.03, and inter-compartmental clearance of 44 ± 4.1 mL min(-1). Parameter estimates suggest that V(d) and f(P) are much higher in hemodialysis patients than in normal subjects. The developed model predicts larger removed toxin mass than that predicted by the two-pool model. On the application front, the developed model was employed to explain the effect of intra-dialytic exercise on toxin removal. The presented simulations suggest that intra-dialytic exercise not only increases the blood flow to low flow region, but also decreases the inter-compartmental resistance. Combined, they lead to increased toxin removal during dialysis and reduced post-dialysis rebound. The developed model can assist in suggesting the improved dialysis dose based on ß(2)-microglobulin, and also lead to quantitative inclusion of intra-dialytic exercise in the future.