Jeremiah R Brown1,2, Devin M Parker1, Meagan E Stabler1, Marshall L Jacobs3, Jeffrey P Jacobs4, Allen D Everett5, Kevin W Lobdell6, Moritz C Wyler von Ballmoos7, Heather Thiessen-Philbrook8, Chirag Parikh8, Todd Mackenzie2, Anthony DiScipio9, David Malenka9, Michael E Matheny10, Alexander Turchin11, Donald S Likosky12. 1. Department of Epidemiology, Dartmouth Geisel School of Medicine, Hanover, New Hampshire, USA. 2. Department of Biomedical Data Science, Geisel School of Medicine, Lebanon, New Hampshire, USA. 3. Division of Pediatric Cardiology, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 4. Division of Thoracic and Cardiovascular Surgery, Department of Surgery, University of Florida, Gainesville, Florida, USA. 5. Division of Cardiac Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 6. Regional Cardiovascular and Thoracic Quality, Education, and Research, Atrium Health, Charlotte, North Carolina, USA. 7. Division of Cardiovascular and Thoracic Surgery, Duke University Medical Center, Durham, North Carolina, USA. 8. Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA. 9. Division of Cardiology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA. 10. Department of Biomedical Informatics, Vanderbilt University Medical School, Nashville, Tennessee, USA. 11. Division of Endocrinology, Diabetes and Hypertension, Harvard Medical School, Boston, Massachusetts, USA. 12. Department of Cardiac Surgery, Michigan Medicine, Ann Arbor, Michigan, USA.
Abstract
OBJECTIVE: Several short-term readmission and mortality prediction models have been developed using clinical risk factors or biomarkers among patients undergoing coronary artery bypass graft (CABG) surgery. The use of biomarkers for long-term prediction of readmission and mortality is less well understood. Given the established association of cardiac biomarkers with short-term adverse outcomes, we hypothesized that 5-year prediction of readmission or mortality may be significantly improved using cardiac biomarkers. MATERIALS AND METHODS: Plasma biomarkers from 1149 patients discharged alive after isolated CABG surgery from eight medical centers were measured in a cohort from the Northern New England Cardiovascular Disease Study Group between 2004 and 2007. We assessed the added predictive value of a biomarker panel with a clinical model against the clinical model alone and compared the model discrimination using the area under the receiver operating characteristic (AUROC) curves. RESULTS: In our cohort, 461 (40%) patients were readmitted or died within 5 years. Long-term outcomes were predicted by applying the STS ASCERT clinical model with an AUROC of 0.69. The biomarker panel with the clinical model resulted in a significantly improved AUROC of 0.74 (p value <.0001). Across 5 years, the hazard ratio for patients in the second to fifth quintile predicted probabilities from the biomarker augmented STS ASCERT model ranged from 2.2 to 7.9 (p values <.001). CONCLUSIONS: We report that a panel of biomarkers significantly improved prediction of long-term readmission or mortality risk following CABG surgery. Our findings suggest biomarkers help clinical care teams better assess the long-term risk of readmission or mortality.
OBJECTIVE: Several short-term readmission and mortality prediction models have been developed using clinical risk factors or biomarkers among patients undergoing coronary artery bypass graft (CABG) surgery. The use of biomarkers for long-term prediction of readmission and mortality is less well understood. Given the established association of cardiac biomarkers with short-term adverse outcomes, we hypothesized that 5-year prediction of readmission or mortality may be significantly improved using cardiac biomarkers. MATERIALS AND METHODS: Plasma biomarkers from 1149 patients discharged alive after isolated CABG surgery from eight medical centers were measured in a cohort from the Northern New England Cardiovascular Disease Study Group between 2004 and 2007. We assessed the added predictive value of a biomarker panel with a clinical model against the clinical model alone and compared the model discrimination using the area under the receiver operating characteristic (AUROC) curves. RESULTS: In our cohort, 461 (40%) patients were readmitted or died within 5 years. Long-term outcomes were predicted by applying the STS ASCERT clinical model with an AUROC of 0.69. The biomarker panel with the clinical model resulted in a significantly improved AUROC of 0.74 (p value <.0001). Across 5 years, the hazard ratio for patients in the second to fifth quintile predicted probabilities from the biomarker augmented STS ASCERT model ranged from 2.2 to 7.9 (p values <.001). CONCLUSIONS: We report that a panel of biomarkers significantly improved prediction of long-term readmission or mortality risk following CABG surgery. Our findings suggest biomarkers help clinical care teams better assess the long-term risk of readmission or mortality.
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Authors: Jeremiah R Brown; Jeffrey P Jacobs; Shama S Alam; Heather Thiessen-Philbrook; Allen Everett; Donald S Likosky; Kevin Lobdell; Moritz C Wyler von Ballmoos; Devin M Parker; Amit X Garg; Todd Mackenzie; Marshall L Jacobs; Chirag R Parikh Journal: Ann Thorac Surg Date: 2018-08-04 Impact factor: 4.330