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

Donation after circulatory death (DCD) is a procedure in which after planned withdrawal of life-sustaining treatment (WLST), the dying process is monitored. A DCD procedure can only be continued if the potential organ donor dies shortly after WLST. This study performed an external validation of 2 existing prediction models to identify potentially DCD candidates, using one of the largest cohorts. METHODS. This multicenter retrospective study analyzed all patients eligible for DCD donation from 2010 to 2015. The first model (DCD-N score) assigned points for absence of neurological reflexes and oxygenation index. The second model, a linear prediction model (LPDCD), yielded the probability of death within 60 min. This study determined discrimination (c-statistic) and calibration (Hosmer and Lemeshow test) for both models. RESULTS. This study included 394 patients, 283 (72%) died within 60 min after WLST. The DCD-N score had a c-statistic of 0.77 (95% confidence intervals, 0.71-0.83) and the LPDCD model 0.75 (95% confidence intervals, 0.68-0.81). Calibration of the LPDCD 60-min model proved to be poor (Hosmer and Lemeshow test, P < 0.001). CONCLUSIONS. The DCD-N score and the LPDCD model showed good discrimination but poor calibration for predicting the probability of death within 60 min. Construction of a new prediction model on a large data set is needed to obtain better calibration.