Prediction Model for Timing of Death in Potential Donors After Circulatory Death (DCD III): Protocol for a Multicenter Prospective Observational Cohort Study

Abstract

Background Controlled donation after circulatory death (cDCD) is a major source of organs for transplantation. A potential cDCD donor poses considerable challenges in terms of identification of those dying within the predefined time frame of warm ischemia after withdrawal of life-sustaining treatment (WLST) to circulatory arrest. Several attempts have been made to develop models predicting the time between treatment withdrawal and circulatory arrest. This time window determines whether organ donation can occur and influences the quality of the donated organs. However, the selected patients used for these models were not always restricted to potential cDCD donors (eg, patients with cancer or severe infections were also included). This severely limits the generalizability of those data. Objective The objectives of this study are the following: (1) to develop a model predicting time to death within 60 minutes in potential cDCD patients; (2) to validate and update previous prediction models on time to death after WLST; (3) to determine timing and patient characteristics that are associated with prognostication and the decision-making process that leads to initiating end-of-life care; (4) to evaluate the impact of timing of family approach on organ donation approval; and (5) to assess the influence of variation in WLST processes on postmortem organ donor potential and actual postmortem organ donors. Methods In this multicenter observational prospective cohort study, all patients admitted to the intensive care unit of 3 university hospitals and 3 teaching hospitals who met the criteria of the cDCD protocol as defined by the Dutch Transplant Foundation were included. The target of enrolment was set to 400 patients. Previously developed models will be refitted in our data set. To further update previous prediction models, we will apply least absolute shrinkage and selection operator (LASSO) as a tool for efficient variable selection to develop the multivariable logistic regression model. Results This protocol was funded in August 2014 by the Dutch Transplant Foundation. We expect to have the results of this study in July 2020. Patient enrolment was completed in July 2018 and data collection was completed in April 2020. Conclusions This study will provide a robust multimodal prediction model, based on clinical and physiological parameters, that can predict time to circulatory arrest in cDCD donors. In addition, it will add valuable insight in the process of WLST in cDCD donors and will fill an important knowledge gap in this essential field of health care. Trial Registration ClinicalTrials.gov NCT04123275; https://clinicaltrials.gov/ct2/show/NCT04123275 International Registered Report Identifier (IRRID) DERR1-10.2196/16733

External Validation of the DCD-N Score and a Linear Prediction Model to Identify Potential Candidates for Organ Donation After Circulatory Death: A Nationwide Multicenter Cohort Study

“…The retrospective inclusion of patients in our study ended in 2015 because of the start of a new large multicenter prospective study, which aims at developing a novel prediction model for the length of the agonal phase after WLST. 6 Exclusion criteria were infections, lack of mechanical ventilation, and euthanasia. All variables were collected from medical files or electronic patient data management systems (EPIC, Epic Systems Corporation, Madison, WI; ChipSoft, HiX software, Amsterdam, the Netherlands; and Metavision provided by iMDsoft, Needham, MA).…”

Prospective Multicenter Observational Cohort Study on Time to Death in Potential Controlled Donation After Circulatory Death Donors—Development and External Validation of Prediction Models: The DCD III Study

“…A more detailed description of the statistical analysis can be found in the previously published study protocol. 17 Second, for the development of the machine learning models, a light gradient boosting machine (LightGBM) algorithm was used for both variable selection and model development. To overcome the limited amount of data available, 10-fold cross-validation was performed on the complete data set and repeated 50 times to assure stability of the model.…”

“…A more detailed description of the statistical analysis can be found in the previously published study protocol. 17…”

“…The study design has been previously published and registered at clinicaltrials.gov (NCT04123275). 17 In short, hemodynamic, pulmonary, and neurological features were assessed no later than 30 min before WLST. Dosages of analgesics and opioids were recorded from 30 min before WLST until circulatory death.…”

Prediction of Organ Donation After Circulatory Death: In Search of a Better Crystal Ball

“…In this light, the coauthors of this study are currently conducting a multicenter, prospective cohort study that potentially may provide the best quality data on prediction of the length of the agonal phase following WLST to date. 7 The United States organ donation community has a similar opportunity. As noted by Doby et al, detailed clinical information on >75% of all deceased donors in the United States is captured by iTransplant, a proprietary electronic medical record utilized by the majority of US organ procurement organizations.…”