Post-Coronary Artery Bypass Medications in Dialysis Patients: Do We Need to Change Strategies?

Coronary Artery Bypass Grafting in Dialysis-Dependent Patients - Key Peri-Operative Considerations

Cardiovascular disease represents the leading cause of mortality in dialysis-dependent (DD) patients, with the great majority of these patients afflicted by severe coronary artery disease. As rates of end-stage renal disease increase worldwide, DD patients represent a growing proportion of the coronary artery bypass grafting (CABG) cohort. Yet, these patients are complex, with crucial changes in their haemodynamic and physiologic profiles that complicate revascularisation surgery. First, this comprehensive literature review explores the outcomes and prognostic factors for DD patients undergoing CABG. We then summarise the intricacies relating to important peri-operative decisions such as use of cardio-pulmonary bypass and choice of conduit.

Improving the prediction of long-term readmission and mortality using a novel biomarker panel

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.