Why the study?
LVEF has well-known limitations including modest reproducibility, load dependence, and representation of LV volume change rather than myocardial contractility, prompting assessment of the prognostic value of cardiac contractility index.
Does cardiac contractility index (CCI) improve prognostic accuracy compared to LVEF in patients newly diagnosed with chronic heart failure?
Does cardiac contractility index (CCI) improve prognostic accuracy compared to LVEF in patients newly diagnosed with chronic heart failure?
Cardiac contractility index provides better prognostic accuracy than LVEF in chronic heart failure and identifies a high-risk subset of HFpEF patients with reduced contractility.
May identify high-risk HFpEF patients; leaves open whether CCI improves prognostication over LVEF in new HF diagnoses.
Background Left ventricular ejection fraction (LVEF) has well-known limitations including modest reproducibility, load dependence, and representation of the percentage change in left ventricular (LV) volume rather than myocardial contractility. We aimed to assess the prognostic value of systolic blood pressure: indexed left ventricular end-systolic volume ratio, or ‘cardiac contractility index’ (CCI). Methods We conducted a prospective cohort study in 728 unselected individuals newly diagnosed with chronic heart failure. We divided patients into tertiles of LVEF and CCI, and also divided those with heart failure with reduced (HFrEF) or preserved ejection fraction (HFpEF) by the median value of CCI (4.43mmHg/ml/m 2 ) into four groups. Mortality rates for CCI and LVEF as continuous variables were assessed using unadjusted and adjusted Poisson regression models. Results There was a modest, positive correlation between LVEF and CCI (r=0.70 [0.66-0.74], R 2 0.49; p <0.0001), although the latter was distributed widely for any given value of LVEF, especially for those with HFpEF. We observed distinct clinical characteristics across tertiles of both LVEF and CCI, with an inverse relationship with conventional markers of risk including N-terminal B-type natriuretic peptide ( p <0.001 in both comparisons). There was a clear relationship between tertiles of CCI and all-cause mortality risk, which was less evident when patients were divided by LVEF. When modelled as continuous variables there was a curvi-linear relationship between all-cause mortality rates and CCI, but the relationship between LVEF and mortality risk was more complex, with no clear association across a wide range from 25-55%. In models including relevant covariates, the association between LVEF and mortality was no longer evident except for those with LVEF 60% (relative to 50%) but remained evident for all specified values of CCI. Patients with HFpEF and CCI below the median value had an all-cause mortality risk ∼40% higher than those with CCI above median ( p <0.001), similar to those with HFrEF. Conclusions CCI is a non-invasive, relatively afterload independent measure left ventricular contractility which provided additional prognostic information beyond conventional assessment by LVEF. Furthermore, CCI was able to reclassify around a third of patients with HFpEF, and these patients had distinct characteristics and a worse prognosis. Clinical perspective What’s new? In an unselected population with chronic heart failure, cardiac contractility index (CCI) provided better prognostic accuracy than left ventricular ejection fraction. CCI was able to reclassify around a third of patients with a preserved ejection fraction who had evidence of reduced left ventricular contractility, and these patients had distinct characteristics and all-cause mortality risk similar to those with a reduced ejection fraction. What are the clinical implications? CCI is a simple, relatively afterload independent measure of left ventricular contractility, which utilises data already part of a standard echocardiographic assessment. The identification of subtle or concomitant systolic dysfunction in heart failure with a preserved ejection fraction may help better define risk and refine the phenotypic classification of this heterogenous group.
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Straw et al. (2022) studied this question.
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