A simple score to predict early death after kidney transplantation
Résumé
BACKGROUND: Few studies have focused on risk stratification for premature death after transplantation. However, stratification of individual risk is an essential step in personalized care.
METHODS: We have developed a risk score of early post-transplant death (ORLY score) in a prospective multicentre cohort including 942 patients and validated our model in a retrospective independent replication cohort including 874 patients.
RESULTS: 60 patients (6.4%) from the prospective cohort died during the first three-year post-transplant. Age, male gender, diabetes, dialysis duration and chronic respiratory failure were associated with early post-transplant death. The multivariable model exhibited good discrimination ability (C-index = 0.78, 95%CI [0.75-0.81]). ORLY score highly predicted early death after transplantation (1.34; 95%CI, 1.22 to 1.48 for each increase of 1 point in score; P < .001). The predictive value of the score in the validation cohort was close to that observed in the experimental cohort (1.41; 95%CI, 1.27 to 1.56 for each increase of 1 point in score; P < .001). Merging the two cohorts, four categories of risk could be individualized: low, 0-5 (n = 522, mean risk, 1%); intermediate, 6-7 (n = 739, mean risk 4.7%); moderate, 8-10 (n = 429, mean risk 10%); and high risk 11-15 (n = 132, mean risk 19%).
CONCLUSIONS: The ORLY score discriminates patients with high risk of early death.