BACKGROUND: In this study we sought to construct a novel scoring system to pre-operatively stratify a patient's risk of 1-year mortality after lung transplantation (LTx) based on recipient- and donor-specific characteristics. METHODS: The UNOS database was queried for adult (≥18 years) patients undergoing LTx between May 1, 2005 and December 31, 2012. The population was randomly divided in a 4:1 fashion into derivation and validation cohorts. A multivariable logistic regression model for 1-year mortality was constructed within the derivation cohort. Points were then assigned to independent predictors (p < 0.05) based on relative odds ratios. Risk groups were established based on score ranges. RESULTS: During the study period, 9,185 patients underwent LTx and the 1-year mortality was 18.0% (n = 1,654). There was a similar distribution of variables between the derivation (n = 7,336) and validation (n = 1,849) cohorts. Of the 14 covariates included in the final model, 9 were ultimately allotted point values (maximum score = 70). The model exhibited good predictive strength (c = 0.65) in the derivation cohort and demonstrated a strong correlation between the observed and expected rates of 1-year mortality in the validation cohort (r = 0.87). The low-risk (score 0 to 11), intermediate-risk (score 12 to 21) and high-risk (score ≥22) groups had a 10.8%, 17.1% and 32.0% risk of mortality (p < 0.001), respectively. CONCLUSIONS: This is the first scoring system that incorporates both recipient- and donor-related factors to predict 1-year mortality after LTx. Its use could assist providers in the identification of patients at highest risk for poor post-transplant outcomes.
BACKGROUND: In this study we sought to construct a novel scoring system to pre-operatively stratify a patient's risk of 1-year mortality after lung transplantation (LTx) based on recipient- and donor-specific characteristics. METHODS: The UNOS database was queried for adult (≥18 years) patients undergoing LTx between May 1, 2005 and December 31, 2012. The population was randomly divided in a 4:1 fashion into derivation and validation cohorts. A multivariable logistic regression model for 1-year mortality was constructed within the derivation cohort. Points were then assigned to independent predictors (p < 0.05) based on relative odds ratios. Risk groups were established based on score ranges. RESULTS: During the study period, 9,185 patients underwent LTx and the 1-year mortality was 18.0% (n = 1,654). There was a similar distribution of variables between the derivation (n = 7,336) and validation (n = 1,849) cohorts. Of the 14 covariates included in the final model, 9 were ultimately allotted point values (maximum score = 70). The model exhibited good predictive strength (c = 0.65) in the derivation cohort and demonstrated a strong correlation between the observed and expected rates of 1-year mortality in the validation cohort (r = 0.87). The low-risk (score 0 to 11), intermediate-risk (score 12 to 21) and high-risk (score ≥22) groups had a 10.8%, 17.1% and 32.0% risk of mortality (p < 0.001), respectively. CONCLUSIONS: This is the first scoring system that incorporates both recipient- and donor-related factors to predict 1-year mortality after LTx. Its use could assist providers in the identification of patients at highest risk for poor post-transplant outcomes.
Authors: Catherine F Borders; Yoshikazu Suzuki; Jared Lasky; Christian Schaufler; Djamila Mallem; James Lee; Kevin Carney; Scarlett L Bellamy; Christian A Bermudez; A Russell Localio; Jason D Christie; Joshua M Diamond; Edward Cantu Journal: J Thorac Cardiovasc Surg Date: 2016-12-15 Impact factor: 5.209
Authors: Marco Schiavon; Giulio Faggi; Lorenzo Rosso; Luca Luzzi; Giovanni Maria Comacchio; Dario Gregori; Mario Nosotti; Francesco Damarco; Andrea Dell'Amore; David Bennet; Antonella Fossi; Piero Paladini; Luigi Santambrogio; Federico Rea Journal: J Thorac Dis Date: 2019-11 Impact factor: 2.895
Authors: Su Hwan Lee; Moo Suk Park; Joo Han Song; Young Sam Kim; Jin Gu Lee; Hyo Chae Paik; Song Yee Kim Journal: J Thorac Dis Date: 2017-10 Impact factor: 2.895
Authors: Nadia M Chu; Xiaomeng Chen; Sunjae Bae; Daniel C Brennan; Dorry L Segev; Mara A McAdams-DeMarco Journal: Transplantation Date: 2021-09-01 Impact factor: 5.385
Authors: Farhan Zafar; Md Monir Hossain; Yin Zhang; Alia Dani; Marc Schecter; Don Hayes; Maurizio Macaluso; Christopher Towe; David L S Morales Journal: Transplantation Date: 2022-04-06 Impact factor: 5.385