Ejection fraction as a statistical index of left ventricular systolic function: the first full allometric scrutiny of its appropriateness and accuracy. (20th February 2018)

• Record Type: Journal Article
• Authors: Lolli, Lorenzo; Batterham, Alan M; Atkinson, Greg
• Is Part Of: Clinical physiology and functional imaging. Volume 38:Number 6(2018:Nov.)
• Page Start: 976
• Page End: 985
• Publication Date: 2018-02-20
• Subjects: allometry -- ejection fraction -- heart failure -- left ventricle -- normalization; Physiology, Pathological -- Periodicals; Diagnostic imaging -- Periodicals; 612
• DOI: 10.1111/cpf.12510
• Languages: English
• ISSNs: 1475-0961

Abstract

Summary: Left ventricular ejection fraction (EF) is a ratio that is deemed to accurately normalize stroke volume (SV) to end‐diastolic volume (EDV). Ratios are now well‐recognized for not normalizing the numerator, in this case SV, consistently for the denominator, EDV. We aimed to provide the first allometric‐based scrutiny of the conventional assumptions that underpin the EF ratio. We allometrically modelled untransformed SV and EDV measurements from 112 preclinical heart failure patients in the Multi‐Ethnic Study of Atherosclerosis (MESA), and 864 chronic heart failure patients in the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) study. An information‐theoretic approach was adopted to assess the relative quality of twelve candidate models for normalizing SV to EDV. None of the conventional underlying assumptions for accurate ratio normalization, for example an allometric exponent ≈1, were upheld for EF. A two‐parameter power function with normal, heteroscedastic error was the best model for scaling SV to EDV in both samples. The allometric exponent (95% confidence interval) was 0·776 (0·682 to 0·869) in MESA, and 0·860 (0·857 to 0·864) in TOPCAT. EF was inversely correlated with EDV in MESA (r = −0·67, 95% CI: −0·76 to −0·55) and TOPCAT (r = −0·41, 95% CI: −0·46 to −0·35). Consequently, for fundamental statistical reasons, EF was biased low for people with generally larger EDVs, and vice versa . For the first time, we have demonstrated that EF is an inaccurate statistic for scaling SV to EDV, leading to potential biased inferences for research and individual patients.