Browsing by Author "Hartwig, Matthew G."

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Development and Validation of Primary Graft Dysfunction Predictive Algorithm for Lung Transplant Candidates
    (Elsevier, 2024) Diamond, Joshua M.; Anderson, Michaela R.; Cantu, Edward; Clausen, Emily S.; Shashaty, Michael G. S.; Kalman, Laurel; Oyster, Michelle; Crespo, Maria M.; Bermudez, Christian A.; Benvenuto, Luke; Palmer, Scott M.; Snyder, Laurie D.; Hartwig, Matthew G.; Wille, Keith; Hage, Chadi; McDyer, John F.; Merlo, Christian A.; Shah, Pali D.; Orens, Jonathan B.; Dhillon, Ghundeep S.; Lama, Vibha N.; Patel, Mrunal G.; Singer, Jonathan P.; Hachem, Ramsey R.; Michelson, Andrew P.; Hsu, Jesse; Localio, A. Russell; Christie, Jason D.; Medicine, School of Medicine
    Background: Primary graft dysfunction (PGD) is the leading cause of early morbidity and mortality after lung transplantation. Accurate prediction of PGD risk could inform donor approaches and perioperative care planning. We sought to develop a clinically useful, generalizable PGD prediction model to aid in transplant decision-making. Methods: We derived a predictive model in a prospective cohort study of subjects from 2012 to 2018, followed by a single-center external validation. We used regularized (lasso) logistic regression to evaluate the predictive ability of clinically available PGD predictors and developed a user interface for clinical application. Using decision curve analysis, we quantified the net benefit of the model across a range of PGD risk thresholds and assessed model calibration and discrimination. Results: The PGD predictive model included distance from donor hospital to recipient transplant center, recipient age, predicted total lung capacity, lung allocation score (LAS), body mass index, pulmonary artery mean pressure, sex, and indication for transplant; donor age, sex, mechanism of death, and donor smoking status; and interaction terms for LAS and donor distance. The interface allows for real-time assessment of PGD risk for any donor/recipient combination. The model offers decision-making net benefit in the PGD risk range of 10% to 75% in the derivation centers and 2% to 10% in the validation cohort, a range incorporating the incidence in that cohort. Conclusion: We developed a clinically useful PGD predictive algorithm across a range of PGD risk thresholds to support transplant decision-making, posttransplant care, and enrich samples for PGD treatment trials.
  • Thumbnail Image
    Item
    Quantitative Evidence for Revising the Definition of Primary Graft Dysfunction after Lung Transplant
    (American Thoracic Society, 2018-01-15) Cantu, Edward; Diamond, Joshua M.; Suzuki, Yoshikazu; Lasky, Jared; Schaufler, Christian; Lim, Brian; Shah, Rupal; Porteous, Mary; Lederer, David J.; Kawut, Steven M.; Palmer, Scott M.; Snyder, Laurie D.; Hartwig, Matthew G.; Lama, Vibha N.; Bhorade, Sangeeta; Bermudez, Christian; Crespo, Maria; McDyer, John; Wille, Keith; Orens, Jonathan; Shah, Pali D.; Weinacker, Ann; Weill, David; Wilkes, David; Roe, David; Hage, Chadi; Ware, Lorraine B.; Bellamy, Scarlett L.; Christie, Jason D.; Medicine, School of Medicine
    RATIONALE: Primary graft dysfunction (PGD) is a form of acute lung injury that occurs after lung transplantation. The definition of PGD was standardized in 2005. Since that time, clinical practice has evolved, and this definition is increasingly used as a primary endpoint for clinical trials; therefore, validation is warranted. OBJECTIVES: We sought to determine whether refinements to the 2005 consensus definition could further improve construct validity. METHODS: Data from the Lung Transplant Outcomes Group multicenter cohort were used to compare variations on the PGD definition, including alternate oxygenation thresholds, inclusion of additional severity groups, and effects of procedure type and mechanical ventilation. Convergent and divergent validity were compared for mortality prediction and concurrent lung injury biomarker discrimination. MEASUREMENTS AND MAIN RESULTS: A total of 1,179 subjects from 10 centers were enrolled from 2007 to 2012. Median length of follow-up was 4 years (interquartile range = 2.4-5.9). No mortality differences were noted between no PGD (grade 0) and mild PGD (grade 1). Significantly better mortality discrimination was evident for all definitions using later time points (48, 72, or 48-72 hours; P < 0.001). Biomarker divergent discrimination was superior when collapsing grades 0 and 1. Additional severity grades, use of mechanical ventilation, and transplant procedure type had minimal or no effect on mortality or biomarker discrimination. CONCLUSIONS: The PGD consensus definition can be simplified by combining lower PGD grades. Construct validity of grading was present regardless of transplant procedure type or use of mechanical ventilation. Additional severity categories had minimal impact on mortality or biomarker discrimination.
  • Thumbnail Image
    Item
    The Impact of Donor Smoking on Primary Graft Dysfunction and Mortality after Lung Transplantation
    (American Thoracic Society, 2024) Diamond, Joshua M.; Cantu, Edward; Calfee, Carolyn S.; Anderson, Michaela R.; Clausen, Emily S.; Shashaty, Michael G. S.; Courtwright, Andrew M.; Kalman, Laurel; Oyster, Michelle; Crespo, Maria M.; Bermudez, Christian A.; Benvenuto, Luke; Palmer, Scott M.; Snyder, Laurie D.; Hartwig, Matthew G.; Todd, Jamie L.; Wille, Keith; Hage, Chadi; McDyer, John F.; Merlo, Christian A.; Shah, Pali D.; Orens, Jonathan B.; Dhillon, Gundeep S.; Weinacker, Ann B.; Lama, Vibha N.; Patel, Mrunal G.; Singer, Jonathan P.; Hsu, Jesse; Localio, A. Russell; Christie, Jason D.; Medicine, School of Medicine
    Rationale: Primary graft dysfunction (PGD) is the leading cause of early morbidity and mortality after lung transplantation. Prior studies implicated proxy-defined donor smoking as a risk factor for PGD and mortality. Objectives: We aimed to more accurately assess the impact of donor smoke exposure on PGD and mortality using quantitative smoke exposure biomarkers. Methods: We performed a multicenter prospective cohort study of lung transplant recipients enrolled in the Lung Transplant Outcomes Group cohort between 2012 and 2018. PGD was defined as grade 3 at 48 or 72 hours after lung reperfusion. Donor smoking was defined using accepted thresholds of urinary biomarkers of nicotine exposure (cotinine) and tobacco-specific nitrosamine (4-[methylnitrosamino]-1-[3-pyridyl]-1-butanol [NNAL]) in addition to clinical history. The donor smoking–PGD association was assessed using logistic regression, and survival analysis was performed using inverse probability of exposure weighting according to smoking category. Measurements and Main Results: Active donor smoking prevalence varied by definition, with 34–43% based on urinary cotinine, 28% by urinary NNAL, and 37% by clinical documentation. The standardized risk of PGD associated with active donor smoking was higher across all definitions, with an absolute risk increase of 11.5% (95% confidence interval [CI], 3.8% to 19.2%) by urinary cotinine, 5.7% (95% CI, −3.4% to 14.9%) by urinary NNAL, and 6.5% (95% CI, −2.8% to 15.8%) defined clinically. Donor smoking was not associated with differential post–lung transplant survival using any definition. Conclusions: Donor smoking associates with a modest increase in PGD risk but not with increased recipient mortality. Use of lungs from smokers is likely safe and may increase lung donor availability.