ArticleTransplantation2016
iChoose Kidney: A Clinical Decision Aid for Kidney Transplantation Versus Dialysis Treatment.
Article in Transplantation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
48 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mortality Risk Prediction Models for People With Kidney Failure: A Systematic Review.JAMA network open · 2025Pooled it
- Measurement Characteristics of the Knowledge Assessment of Renal Transplantation.Transplantation · 2019Trial
- Association between the "Timed Up and Go Test" at transplant evaluation and outcomes after kidney transplantation.Clinical transplantation · 2018Trial
- Effect of the iChoose Kidney decision aid in improving knowledge about treatment options among transplant candidates: A randomized controlled trial.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2018Trial
- A Randomized Trial to Reduce Disparities in Referral for Transplant Evaluation.Journal of the American Society of Nephrology : JASN · 2017Trial
- A Novel Pre-Kidney Transplant Risk Score to Optimize Waiting List Management.Journal of clinical medicine · 2026Article
- A Prediction Model for Risk of Death in Kidney Transplant Recipients.JAMA network open · 2026Article
- Leveraging ICT Tools to Improve Kidney Health: A Comprehensive Review of Innovations in Nephrology.Healthcare (Basel, Switzerland) · 2026Review
- New Tools and a Population-Based Approach to Improve Kidney Transplant Opportunity and Preemptive Waitlisting.Clinical transplantation · 2026Article
- Predicting Three-Year Survival in Patients Receiving Maintenance Dialysis: An External Validation and Updated Multivariable Prediction Model for iChoose Kidney in Ontario, Canada.Canadian journal of kidney health and disease · 2026Article
- Assessing Deceased-Donor Kidneys Through Posttransplant Survival Prediction Algorithms.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2026Article
- Ethics and Algorithms to Navigate AI's Emerging Role in Organ Transplantation.Journal of clinical medicine · 2025Review
- Competing and Noncompeting Risk Models for Predicting Kidney Allograft Failure.Journal of the American Society of Nephrology : JASN · 2025Article
- Referral and Beyond: Restructuring the Kidney Transplant Process to Support Greater Access in the United States.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2024Article
- Predicting Kidney Transplantation Outcomes from Donor and Recipient Characteristics at Time Zero: Development of a Mobile Application for Nephrologists.Journal of clinical medicine · 2024Article
- Article
- Mobile health management among end stage renal disease patients: a scoping review.Frontiers in medicine · 2024Article
- Prediction of chronic kidney disease progression using recurrent neural network and electronic health records.Scientific reports · 2023Article
- Exploring the Potential of Chatbots in Critical Care Nephrology.Medicines (Basel, Switzerland) · 2023Review
- Risk Factors for Lower Extremity Amputation in Patients with End-Stage Kidney Disease: A Nationwide Cohort Study.Journal of clinical medicine · 2023Article
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Authors and funding
12 authors.
Funding
Abstract
backgroundDespite a significant survival advantage of kidney transplantation compared with dialysis, nearly one third of end-stage renal disease (ESRD) patients are not educated about kidney transplantation as a treatment option at the time of ESRD diagnosis. Access to individualized, evidence-based prognostic information is needed to facilitate and encourage shared decision making about the clinical implications of whether to pursue transplantation or long-term dialysis.
methodsWe used a national cohort of incident ESRD patients in the US Renal Data System surveillance registry from 2005 to 2011 to develop and validate prediction models for risk of 1- and 3-year mortality among dialysis versus kidney transplantation. Using these data, we developed a mobile clinical decision aid that provides estimates of risks of death and survival on dialysis compared with kidney transplantation patients.
resultsFactors included in the mortality risk prediction models for dialysis and transplantation included age, race/ethnicity, dialysis vintage, and comorbidities, including diabetes, hypertension, cardiovascular disease, and low albumin. Among the validation cohorts, the discriminatory ability of the model for 3-year mortality was moderate (c statistic, 0.7047; 95% confidence interval, 0.7029-0.7065 for dialysis and 0.7015; 95% confidence interval, 0.6875-0.7155 for transplant). We used these risk prediction models to develop an electronic, user-friendly, mobile (iPad, iPhone, and website) clinical decision aid called iChoose Kidney.
conclusionsThe use of a mobile clinical decision aid comparing individualized mortality risk estimates for dialysis versus transplantation could enhance communication between ESRD patients and their clinicians when making decisions about treatment options.
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