Background The near-death experiences (NDE) in dialysis patients of our country have not been previously studied. The objective of this study is to investigate the characteristics of NDEs in patients on dialysis. Materials and Methods We performed a cross sectional study of the adult patients of chronic kidney disease stage 5 without dialysis and on dialysis who survived cardiac arrest by cardiopulmonary resuscitation (CPR) as per ACLS (Advanced Cardiac Life Support) guidelines and who sustained pulseless ventricular tachycardia/ventricular fibrillation and received CPR and/or direct cardioversion. We used two scales, Greyson’s NDE scale and Ring’s Weighted Core Experience Index (WCEI). Results We performed the study between 2016 and 2018. A total of 29 patients were included. The data based on Greyson’s NDE scale and Ring’s Weighted Core Experience Index (WCEI)were collected. Conclusions Our study brings a perspective of NDE in CKD and dialysis patients. A similar study of NDE in dialysis patients should be considered by other nephrologists.

Background: The development of atopic dermatitis (AD) drugs is confronted by many disease phenotypes and trial design options, which are hard to explore experimentally. Objective: Optimize AD trial design using simulations. Methods: We constructed a quantitative systems pharmacology (QSP) model of AD and standard of care (SoC) treatments and generated a phenotypically diverse virtual population whose parameter distribution is a) derived from known relationships between AD biomarkers and disease severity and b) calibrated using disease severity evolution under SoC regimens. Results: We applied this workflow to the immunomodulator OM-85, currently being investigated for its potential use in AD, and calibrated investigational treatment model with the efficacy profile of an existing trial (thereby enriching it with plausible marker levels and dynamics). We assessed the sensitivity of trial outcomes to trial protocol and found that for this particular example, a) the choice of endpoint is more important than the choice of dosing-regimen and b) patient selection by model-based responder enrichment could increase the expected effect size. A global sensitivity analysis reveals that only a limited subset of baseline biomarkers is needed to predict the drug response of the full virtual population. Conclusion: This AD QSP workflow built around knowledge of marker-severity relationships as well as SoC efficacy can be tailored to specific development cases so as to optimize several trial protocol parameters and biomarker-stratification and therefore holds promise to become a powerful model-informed drug development tool.

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