Notice: Users may be experiencing issues with displaying some pages on stanfordhealthcare.org. We are working closely with our technical teams to resolve the issue as quickly as possible. Thank you for your patience.
 

Learn about the flu shot, COVID-19 vaccine, and our masking policy »

Stanford Health Care

Objective Estimates Improve Risk Stratification for Primary Graft Dysfunction after Lung Transplantation. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons Shah, R. J., Diamond, J. M., Cantu, E., Flesch, J., Lee, J. C., Lederer, D. J., Lama, V. N., Orens, J., Weinacker, A., Wilkes, D. S., Roe, D., Bhorade, S., Wille, K. M., Ware, L. B., Palmer, S. M., Crespo, M., Demissie, E., Sonnet, J., Shah, A., Kawut, S. M., Bellamy, S. L., Localio, A. R., Christie, J. D. 2015; 15 (8): 2188-96

Abstract

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/m(2) ), 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.

View details for DOI 10.1111/ajt.13262

View details for PubMedID 25877792