Patient preferences and individualized risk prediction for management of acute coronary syndrome in chronic kidney disease

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Chronic kidney disease (CKD) affects over 10% of adult Canadians and is associated with high risks of morbidity and mortality following non-ST-elevation acute coronary syndrome (ACS). ACS is managed invasively or conservatively with medication, however, people with CKD are 20-50% less likely to receive invasive management than patients without CKD. There are important knowledge gaps to support shared decision-making for ACS in this patient population related to risk prediction of clinical outcomes and patient preferences for treatment options. This thesis’ objectives are to: 1) understand patient preferences towards invasive versus conservative management of ACS, 2) develop tools for predicting long-term adverse outcomes following ACS, and 3) estimate net effects of invasive management based on trade-offs in reducing risks of mortality or readmission for myocardial infarction (MI) versus increasing risk of end-stage kidney disease (ESKD). To achieve these objectives, we conducted a discrete choice experiment (DCE) to quantify patient preferences toward treatment decisions for ACS and developed risk prediction models for mortality, readmission for MI, the composite of mortality and readmission for MI, and ESKD. Further, we synthesized patient preference and absolute risk estimates, while incorporating treatment effects from randomized control trials, to conduct a net effect analysis. The DCE found most patients preferred treatment options that lowered their risk of mortality; however, a subgroup of patients was identified with strong preferences toward conservative treatment for ACS. Risk prediction model performance varied. Model calibration was very good; however, discrimination ranged from excellent for predicting ESKD to poor for predicting readmission for MI. The net effect analysis estimated 87% of all patients with CKD were expected to experience net benefit from invasive management with reductions in risks of mortality or readmission for MI outweighing increases in risk of progression to ESKD. This work has addressed knowledge gaps for understanding preferences of patients with CKD toward key attributes of treatment options for ACS and for providing individualized estimates of long-term outcomes according to treatment strategy for ACS for patients with CKD. This work provides knowledge to individualize benefit-harm information and support shared decision-making approaches for ACS treatment for patients with CKD.
Risk Prediction, Discrete Choice Experiment, Shared Decision Making, Chronic Kidney Disease, Acute Coronary Syndrome, Competing Risks
Wilson, T. A. (2021). Patient preferences and individualized risk prediction for management of acute coronary syndrome in chronic kidney disease (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from