Nomogram for Predicting Patient Survival After Withdrawal of Life-Sustaining Treatment in Patients With Devastating Neurological Injury

G. Xu, X. He.

Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, guangzhou, China
Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, guangzhou, China.

Meeting: 2015 American Transplant Congress

Abstract number: A69

Keywords: Brain death, Donation, Procurement

Objective:Reliable prediction of time of death after withdrawal of life-sustaining treatment in patients with devastating neurological injury is crucial to successful donation after circulatory death. Method: we conducted a multicenter study of 526 neurocritical patients who underwent life support withdrawal at four neurosurgical centers in China. Based on a retrospective cohort, we used multivariate Cox regression analysis to identify prognostic factors for patient survival, which were then integrated into a nomogram. The model was calibrated and validated using data from an external retrospective cohort and a prospective cohort. We identified 11 variables that were incorporated into a nomogram. Result:The C-indexes for predicting the 60-min death probability in the training, external validation, and prospective validation cohorts were 0.96 (0.94-0.99), 0.95 (0.93-0.98), and 1.00 (1.00-1.00), respectively.

[Table1] Proportion of deaths at each time point stratified by different risk groups

Risk groups	number of patients	60-min deaths (%)	120-min deaths (%)	240-min deaths (%)
<22	73	3 (4.1)	36 (49.3)	62 (84.9)
22-25.9	19	1 (5,3)	13 (68.4)	18 (94.7)
26-37	134	91 (67.9)	130 (97.0)	131 (97.8)
>37	193	191 (99.0)	193 (100.00)	193 (100.00)

A total of 46 variables were entered into the univariate and subsequent multivariate analysesThe calibration plots after WLST showed an optimal agreement between the prediction of survival by the nomogram and the actual observation for all cohorts. Then we identified 30, 35, and 50 as cut-points for risk stratification into four groups. Survival curves indicated distinct prognoses between patients in the different risk groups (P<0.001).Conclusion: we have developed and validated a nomogram to accurately identify potential circulatory death donors in neurocritical patients in a Chinese population.

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