Objective Estimates Improve Risk Stratification for Primary Graft Dysfunction after Lung Transplantation

Primary graft dysfunction (PGD) is a major cause of early mortality after lung transplant. We aimed to define objective estimates of PGD risk based on readily available clinical variables, using a prospective study of 11 centers in the Lung Transplant Outcomes Group (LTOG). Derivation included 1255 subjects from 2002 to 2010; with separate validation in 382 subjects accrued from 2011 to 2012. We used logistic regression to identify predictors of grade 3 PGD at 48/72 h, and decision curve methods to assess impact on clinical decisions. 211/1255 subjects in the derivation and 56/382 subjects in the validation developed PGD. We developed three prediction models, where low-risk recipients had a normal BMI (18.5–25 kg/m2), chronic obstructive pulmonary disease/cystic fibrosis, and absent or mild pulmonary hypertension (mPAP<40 mmHg). All others were considered higher-risk. Low-risk recipients had a predicted PGD risk of 4–7%, and high-risk a predicted PGD risk of 15–18%. Adding a donor-smoking lung to a higher-risk recipient significantly increased PGD risk, although risk did not change in low-risk recipients. Validation demonstrated that probability estimates were generally accurate and that models worked best at baseline PGD incidences between 5% and 25%. We conclude that valid estimates of PGD risk can be produced using readily available clinical variables. Primary graft dysfunction (PGD) is a major cause of early mortality after lung transplant. We aimed to define objective estimates of PGD risk based on readily available clinical variables, using a prospective study of 11 centers in the Lung Transplant Outcomes Group (LTOG). Derivation included 1255 subjects from 2002 to 2010; with separate validation in 382 subjects accrued from 2011 to 2012. We used logistic regression to identify predictors of grade 3 PGD at 48/72 h, and decision curve methods to assess impact on clinical decisions. 211/1255 subjects in the derivation and 56/382 subjects in the validation developed PGD. We developed three prediction models, where low-risk recipients had a normal BMI (18.5–25 kg/m2), chronic obstructive pulmonary disease/cystic fibrosis, and absent or mild pulmonary hypertension (mPAP<40 mmHg). All others were considered higher-risk. Low-risk recipients had a predicted PGD risk of 4–7%, and high-risk a predicted PGD risk of 15–18%. Adding a donor-smoking lung to a higher-risk recipient significantly increased PGD risk, although risk did not change in low-risk recipients. Validation demonstrated that probability estimates were generally accurate and that models worked best at baseline PGD incidences between 5% and 25%. We conclude that valid estimates of PGD risk can be produced using readily available clinical variables.