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Observational Study
. 2021 Jun 1;105(6):1311-1316.
doi: 10.1097/TP.0000000000003430.

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

Maaike F Nijhoff  1 , Robert A Pol  1 , Meint Volbeda  2 , Angela M M Kotsopoulos  3 , Johan P C Sonneveld  4 , Luuk Otterspoor  5 , Wilson F Abdo  6 , Vera M Silderhuis  7 , Mostafa El Moumni  1 , Cyril Moers  1
Affiliations
Observational Study

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

Maaike F Nijhoff et al. Transplantation. .

Abstract

Background: 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.

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Conflict of interest statement

The authors declare no funding or conflicts of interest.

Figures

FIGURE 1.
FIGURE 1.
A, Receiver operating characteristic curve based on the multivariable DCD-N model for prediction of death within 30 min. B, Receiver operating characteristic curve based on the multivariable DCD-N model for prediction of death within 60 min. C, Receiver operating characteristic curve based on the multivariable DCD-N model for prediction of death within 120 min. DCD-N, circulatory death in patients in neurocritical; ROC, receiver-operator curve.
FIGURE 2.
FIGURE 2.
A, Receiver operating characteristic curve based on the LPDCD multivariable model for prediction of death within 30 min. B, Calibration plot with the combination of the observed proportion and the predicted mortality for the LPDCD 30-min model. C, Receiver operating characteristic curve based on the LPDCD multivariable model for prediction of death within 60 min. D, Calibration plot with the combination of the observed proportion and the predicted mortality for the LPDCD 60-min model. E, Receiver operating characteristic curve based on the LPDCD multivariable model for prediction of death within 120 min. F, Calibration plot with the combination of the observed proportion and the predicted mortality for the LPDCD 120-min model. LPDCD, linear prediction for donation after circulatory death model.
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