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A simple score to predict early death after kidney transplantation
Author(s) -
Bamoulid Jamal,
Frimat Marie,
Courivaud Cécile,
Crepin Thomas,
Gaiffe Emilie,
Hazzan Marc,
Ducloux Didier
Publication year - 2020
Publication title -
european journal of clinical investigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.164
H-Index - 107
eISSN - 1365-2362
pISSN - 0014-2972
DOI - 10.1111/eci.13312
Subject(s) - medicine , cohort , transplantation , prospective cohort study , framingham risk score , kidney transplantation , retrospective cohort study , dialysis , cohort study , risk assessment , disease , computer security , computer science
Abstract 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. Material and 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.