Jeremiah R Brown1, Jeffrey P Jacobs2, Shama S Alam3, Heather Thiessen-Philbrook4, Allen Everett5, Donald S Likosky6, Kevin Lobdell7, Moritz C Wyler von Ballmoos8, Devin M Parker3, Amit X Garg9, Todd Mackenzie3, Marshall L Jacobs2, Chirag R Parikh4. 1. Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, Lebanon, New Hampshire; Department of Epidemiology, Geisel School of Medicine, Lebanon, New Hampshire; Department of Biomedical Data Science, Geisel School of Medicine, Lebanon, New Hampshire. Electronic address: jbrown@dartmouth.edu. 2. Division of Cardiovascular Surgery, Johns Hopkins All Children's Heart Institute, Johns Hopkins All Children's Hospital, St. Petersburg, Tampa, and Orlando, Florida; Division of Cardiac Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland. 3. Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, Lebanon, New Hampshire. 4. Department of Medicine, Johns Hopkins University, Baltimore, Maryland. 5. Department of Pediatric Cardiology, Johns Hopkins Children's Center, Baltimore, Maryland. 6. Department of Cardiac Surgery, University of Michigan, Ann Arbor, Michigan. 7. Carolinas HealthCare System, Charlotte, North Carolina. 8. Duke University School of Medicine, Durham, North Carolina. 9. Western University, London, Ontario, Canada.
Abstract
BACKGROUND: Hospital readmission within 30 days is associated with higher risks of complications, death, and increased costs. Accurate statistical models to stratify the risk of 30-day readmission or death after cardiac surgery could help clinical teams focus care on those patients at highest risk. We hypothesized biomarkers could improve prediction for readmission or mortality. METHODS: Levels of ST2, galectin-3, N-terminal pro-brain natriuretic peptide, cystatin C, interleukin-6, and interleukin-10 were measured in samples from 1,046 patients discharged after isolated coronary artery bypass graft surgery from eight medical centers, with external validation in 1,194 patients from five medical centers. Thirty-day readmission or mortality were ascertained using Medicare, state all-payer claims, and the National Death Index. We tested and externally validated the clinical models and the biomarker panels using area under the receiver-operating characteristics (AUROC) statistics. RESULTS: There were 112 patients (10.7%) who were readmitted or died within 30 days after coronary artery bypass graft surgery. The Society of Thoracic Surgeons augmented clinical model resulted in an AUROC of 0.66 (95% confidence interval: 0.61 to 0.71). The biomarker panel with The Society of Thoracic Surgeons augmented clinical model resulted in an AUROC of 0.74 (bootstrapped 95% confidence interval: 0.69 to 0.79, p < 0.0001). External validation of the model showed limited improvement with the addition of a biomarker panel, with an AUROC of 0.51 (95% confidence interval: 0.45 to 0.56). CONCLUSIONS: Although biomarkers significantly improved prediction of 30-day readmission or mortality in our derivation cohort, the external validation of the biomarker panel was poor. Biomarkers perform poorly, much like other efforts to improve prediction of readmission, suggesting there are many other factors yet to be explored to improve prediction of readmission.
BACKGROUND: Hospital readmission within 30 days is associated with higher risks of complications, death, and increased costs. Accurate statistical models to stratify the risk of 30-day readmission or death after cardiac surgery could help clinical teams focus care on those patients at highest risk. We hypothesized biomarkers could improve prediction for readmission or mortality. METHODS: Levels of ST2, galectin-3, N-terminal pro-brain natriuretic peptide, cystatin C, interleukin-6, and interleukin-10 were measured in samples from 1,046 patients discharged after isolated coronary artery bypass graft surgery from eight medical centers, with external validation in 1,194 patients from five medical centers. Thirty-day readmission or mortality were ascertained using Medicare, state all-payer claims, and the National Death Index. We tested and externally validated the clinical models and the biomarker panels using area under the receiver-operating characteristics (AUROC) statistics. RESULTS: There were 112 patients (10.7%) who were readmitted or died within 30 days after coronary artery bypass graft surgery. The Society of Thoracic Surgeons augmented clinical model resulted in an AUROC of 0.66 (95% confidence interval: 0.61 to 0.71). The biomarker panel with The Society of Thoracic Surgeons augmented clinical model resulted in an AUROC of 0.74 (bootstrapped 95% confidence interval: 0.69 to 0.79, p < 0.0001). External validation of the model showed limited improvement with the addition of a biomarker panel, with an AUROC of 0.51 (95% confidence interval: 0.45 to 0.56). CONCLUSIONS: Although biomarkers significantly improved prediction of 30-day readmission or mortality in our derivation cohort, the external validation of the biomarker panel was poor. Biomarkers perform poorly, much like other efforts to improve prediction of readmission, suggesting there are many other factors yet to be explored to improve prediction of readmission.
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