Vaibhav Maheshwari

Comparison of toxin removal outcomes in online hemodiafiltration and intra-dialytic exercise in high-flux hemodialysis: A prospective randomized open-label clinical study protocol

BackgroundMaintenance hemodialysis (HD) patients universally suffer from excess toxin load. Hemodiafiltration (HDF) has shown its potential in better removal of small as well as large sized toxins, but its efficacy is restricted by inter-compartmental clearance. Intra-dialytic exercise on the other hand is also found to be effective for removal of toxins; the augmented removal is apparently obtained by better perfusion of skeletal muscles and decreased inter-compartmental resistance. The aim of this trial is to compare the toxin removal outcome associated with intra-dialytic exercise in HD and with post-dilution HDF.Methods/designThe main hypothesis of this study is that intra-dialytic exercise enhances toxin removal by decreasing the inter-compartmental resistance, a major impediment for toxin removal. To compare the HDF and HD with exercise, the toxin rebound for urea, creatinine, phosphate, and β2-microglobulin will be calculated after 2 hours of dialysis. Spent dialysate will also be collected to calculate the removed toxin mass. To quantify the decrease in inter-compartmental resistance, the recently developed regional blood flow model will be employed. The study will be single center, randomized, self-control, open-label prospective clinical research where 15 study subjects will undergo three dialysis protocols (a) high flux HD, (b) post-dilution HDF, (c) high flux HD with exercise. Multiple blood samples during each study session will be collected to estimate the unknown model parameters.DiscussionThis will be the first study to investigate the exercise induced physiological change(s) responsible for enhanced toxin removal, and compare the toxin removal outcome both for small and middle sized toxins in HD with exercise and HDF. Successful completion of this clinical research will give important insights into exercise effect on factors responsible for enhanced toxin removal. The knowledge will give confidence for implementing, sustaining, and optimizing the exercise in routine dialysis care. We anticipate that toxin removal outcomes from intra-dialytic exercise session will be comparable to that obtained by standalone HDF. These results will encourage clinicians to combine HDF with intra-dialytic exercise for significantly enhanced toxin removal.Trial registrationClinicalTrials.gov number, NCT01674153

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

BackgroundCool 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/designThis 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, β2-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.DiscussionThis 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 registrationClinicaltrials.gov Identifier - NCT02064153.

A Novel Multi-Objective Optimization Based Experimental Design and Its Application for Physiological Model of Type 1 Diabetes

Abstract The design of optimal model based experiments is finding increasing use in various fields including chemical, pharmaceutical, biological engineering, and biomedicine. The traditional Model Based Optimal Experimental Design (MBOED) techniques focus on improving the parameter precision but do not consider the undesired possibility of increasing the correlation among the estimated parameters. In this paper, we propose a multi-objective optimization based experimental design technique, which provides the trade-off curve between information measure and correlation measure in the form of a Pareto-optimal front. This Pareto-optimal front gives the experimenter the freedom to choose appropriate experimental designs for real world system under investigation. The proposed methodology is illustrated using an example involving the identification of physiological models for characterizing Type 1 diabetic patients.

A novel mathematical model of protein-bound uremic toxin kinetics during hemodialysis

Protein-bound uremic toxins (PBUTs) are difficult to remove by conventional hemodialysis; a high degree of protein binding reduces the free fraction of toxins and decreases their diffusion across dialyzer membranes. Mechanistic understanding of PBUT kinetics can open new avenues to improve their dialytic removal. We developed a comprehensive model of PBUT kinetics that comprises: (1) a three-compartment patient model, (2) a dialyzer model. The model accounts for dynamic equilibrium between protein, toxin, and the protein-toxin complex. Calibrated and validated using clinical and experimental data from the literature, the model predicts key aspects of PBUT kinetics, including the free and bound concentration profiles for PBUTs and the effects of dialysate flow rate and dialyzer size on PBUT removal. Model simulations suggest that an increase in dialysate flow rate improves the reduction ratio (and removal) of strongly protein-bound toxins, namely, indoxyl sulfate and p-cresyl sulfate, while for weakly bound toxins, namely, indole-3-acetic acid and p-cresyl glucuronide, an increase in blood flow rate is advantageous. With improved dialyzer performance, removal of strongly bound PBUTs improves gradually, but marginally. The proposed model can be used for optimizing the dialysis regimen and for in silico testing of novel approaches to enhance removal of PBUTs.

Multi-Criteria Optimization Based Experimental Design for Parameter Estimation of a Double Feedback Gene Switching Model

Despite the rapid increase in quantity and quality of experimental data in many fields of engineering and science, quantitative measurements of many cellular components are still relatively scarce. This work deals with estimating the parameters of a double feedback gene-switching model. To achieve the goal, a model-based design of experiment (MBDOE) approach for parameter estimation is employed. To overcome the problem of convergence in parameter estimation step (due to correlation among the parameters), a non-dominated sorting genetic algorithm (NSGA-II) based, multi-objective optimization (MOO) based MBDOE has been used. The parameter estimates obtained through the MOO based DOE as well as a standard alphabetical DOE technique are then compared with the known true values from the literature to highlight the efficacy of the MOO-MBDOE technique.

A novel optimal experiment design technique based on multi-objective optimization and its application for toxin kinetics model of hemodialysis patients

Abstract It is increasingly recognized that rapid model development or the refining of currently available models for any system (chemical, biological, medical, environmental etc.) is greatly facilitated by experimental design and particularly by Model Based Optimal Experiment Design (MBOED). MBOED approaches are primarily used in the context of precise parameter estimation and model discrimination. However, the presence of parameter correlation often reduces the confidence in creating practical applications based on the identified model. To overcome this problem, a novel design criterion comprising two conflicting objectives: (1) maximizing the information content (which is the usual objective in traditional OED), and (2) minimizing the correlation between estimated parameters, is proposed. The proposed approach is implemented to suggest the optimal sampling times for estimating the model parameters of toxin kinetics model for patients on maintenance hemodialysis, developed recently by Maheshwari et al., 2011. The resulting parameter estimates can be used for prescribing patient specific dialysis sessions. The proposed multi-objective MBOED criterion is also relevant for use in other biomedical, chemical, and environmental systems.