Evidenced based therapies in a population with chronic kidney disease presenting with an acute coronary syndrome

Abstract

Introduction: There is variation in the evidence based treatment of patients with chronic kidney disease (CKD) presenting with an acute coronary syndrome (ACS). We characterised the clinical factors impacting on management of patients with ACS and CKD in an unselected multicentre Australian registry population. Methods: Of the 2435 patients presenting and surviving an ACS, 593 had CKD (glomerular filtration rate (GFR) <60 mL/min). Patient predictors of coronary angiography (CA), receipt of evidence based medications (EBM), cardiac rehabilitation (CR) and all three indicators of optimal management (OM) were identified using multivariate logistic regression modelling. Results: Compared to patients with normal renal function patients with CKD had lower likelihood of being discharged on EBM (37.6% vs 48.0%, p<0.0001), receiving CA (64.8% vs 83.9%, p<0.0001), CR (49.7% vs 63.7%, p<0.0001), and OM (18.6% vs 30.7%, p<0.0001). Predictors of failure to be discharged on EBM included a history of atrial arrhythmias (OR=0.59, 95% CI: 0.37-0.96; p<0.0001) and peripheral vascular disease (OR=0.53, 95% CI: 0.30-0.96; p=0.0372). Coronary angiography was less likely in CKD patients with prior heart failure (OR=0.37, 95% CI: 0.23-0.59; p<0.0001), atrial arrhythmias (OR=0.51, 95% CI: 0.32-0.81; p=0.0049), impaired mobility (OR=0.53, 95% CI: 0.31-0.91; p=0.0203), prior CA (OR=0.33, 95% CI: 0.23-0.49; p<0.0001) and worsening CKD (OR (per CKD stage)=0.39, 95% CI: 0.28-0.53; p<0.0001). CR referral was less common in older patients (OR (per year)=0.98, 95% CI: 0.97-1.00; p=0.0339), patients with malignancy (OR=0.52, 95% CI: 0.29-0.93; p=0.0280), patients without a family history of coronary artery disease (OR=0.58, 95% CI: 0.38-0.87; p=0.0088) and those who had not undergone CA (OR=0.46, 95% CI: 0.31-0.68; p=0.0001) or percutaneous coronary intervention (OR=0.35, 95% CI: 0.23-0.55; p<0.0001) during the index admission. Failure to receive OM was predicted by not speaking English (OR=0.46, 95% CI: 0.24-0.88; p=0.0189), older age (OR (per year)=0.98, 95% CI: 0.96-0.99; p=0.0088), lower GFR (OR (per mL/min)=0.98, 95% CI: 0.96-0.99; p=0.0082), exertional angina (OR=0.49, 95% CI: 0.30-0.82; p=0.0067) and atrial arrhythmia during admission (OR=0.41, 95% CI: 0.21-0.80; p=0.0094). Conclusion: Under-treatment of patients with CKD is predicted by several patient factors. Standardising hospital care and targeting patients with clinical characteristics that predict treatment gaps are required to improve outcomes in this population.