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Impact of co-morbid burden on mortality in patients with coronary heart disease, heart failure, and cerebrovascular accident: a systematic review and meta-analysis

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/ehjqcco/qcw025

Keywords

Charlson Co-morbidity Index; Cardiovascular disease; Mortality

Funding

  1. Medical Research Council [MR/K006665/1, MC_PC_13042] Funding Source: researchfish
  2. National Institute for Health Research [ACF-2013-06-001] Funding Source: researchfish
  3. MRC [MR/K006665/1] Funding Source: UKRI

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Aims We sought to investigate the prognostic impact of co-morbid burden as defined by the Charlson Co-morbidity Index (CCI) in patients with a range of prevalent cardiovascular diseases. Methods and results We searched MEDLINE and EMBASE to identify studies that evaluated the impact of CCI on mortality in patients with cardiovascular disease. A random-effects meta-analysis was undertaken to evaluate the impact of CCI on mortality in patients with coronary heart disease (CHD), heart failure (HF), and cerebrovascular accident (CVA). A total of 11 studies of acute coronary syndrome (ACS), 2 stable coronary disease, 5 percutaneous coronary intervention (PCI), 13 HF, and 4 CVA met the inclusion criteria. An increase in CCI score per point was significantly associated with a greater risk of mortality in patients with ACS [pooled relative risk ratio (RR) 1.33; 95% CI 1.15-1.54], PCI (RR 1.21; 95% CI 1.12-1.31), stable coronary artery disease (RR 1.38; 95% CI 1.29-1.48), and HF (RR 1.21; 95% CI 1.13-1.29), but not CVA. A CCI score of.2 significantly increased the risk of mortality in ACS (RR 2.52; 95% CI 1.58-4.04), PCI (RR 3.36; 95% CI 2.14-5.29), HF (RR 1.76; 95% CI 1.65-1.87), and CVA (RR 3.80; 95% CI 1.20-12.01). Conclusion Increasing co-morbid burden as defined by CCI is associated with a significant increase in risk of mortality in patients with underlying CHD, HF, and CVA. CCI provides a simple way of predicting adverse outcomes in patients with cardiovascular disease and should be incorporated into decision-making processes when counselling patients.

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