Key result
Including CAD history in the ASE algorithm recategorizes ~59% to DD+, reducing LVDD underdiagnosis.
Why the study?
The ability of 2016 ASE guidelines to detect early LV diastolic dysfunction is not well established, particularly in subclinical CAD, and may depend on knowledge of CAD history.
Does knowledge of coronary artery disease history improve the accuracy of the 2016 ASE algorithm in diagnosing early left ventricular diastolic dysfunction in patients with preserved LVEF?
Observational (n=34)
Does knowledge of coronary artery disease history improve the accuracy of the 2016 ASE algorithm in diagnosing early left ventricular diastolic dysfunction in patients with preserved LVEF?
p-value: p=<.0001
Knowledge of coronary artery disease history or the addition of isovolumetric relaxation time (IVRT) significantly improves the detection of early left ventricular diastolic dysfunction using the 2016 ASE guidelines.
Incorporating CAD history may reduce early LVDD underdiagnosis with the 2016 ASE algorithm; leaves open prospective validation before practice change.
BACKGROUND: In 2016, the American Society of Echocardiography (ASE) released guidelines for identifying left ventricular (LV) diastolic dysfunction (DD), but its ability to detect early hemodynamic abnormalities is not well established, especially in the setting of subclinical coronary artery disease (CAD). We hypothesize that the accuracy of ASE categorization of early LVDD is affected by knowledge of whether CAD history is present. METHODS: We studied 34 patients (age 62 ± 7 years) with NYHA class I to II symptoms and with transthoracic echocardiography without findings suggesting myocardial disease (all with preserved LV ejection fraction), who underwent cardiac catheterization with high-fidelity LV pressure measurement. Echocardiographic images were evaluated for LVDD using ASE algorithm without and with knowledge of CAD history and angiography findings. CAD was considered as having DD for the algorithm. RESULTS: CAD was identified in 22 patients at catheterization (65%). Using ASE guidelines without including history of CAD or angiographic results, 29 patients were DD-, 3 were DD+ (all grade II), and 2 were indeterminate. Inclusion of CAD history recategorized 59% (n = 20) patients to DD+ (all grade I) from DD- (P < .0001). Nineteen of the recategorized patients (95%) had increased isovolumetric relaxation time (IVRT). The addition of echocardiographic IVRT improved discrimination between DD- and DD+, when the presence of CAD is unknown. CONCLUSIONS: 2016-ASE algorithm reasonably accurately identifies early LVDD at rest as reflected by LV catheterization when CAD is disclosed, but without knowledge of the presence of CAD, it underdiagnoses DD+ grade I. The addition of IVRT may improve early LVDD diagnostics.
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Sharifov et al. (2020) conducted an observational in Left ventricular diastolic dysfunction (n=34). 2016 ASE algorithm with knowledge of CAD history vs. 2016 ASE algorithm without knowledge of CAD history was evaluated on Recategorization to DD+ from DD- (p=<.0001). Including coronary artery disease history in the 2016 ASE algorithm recategorized 59% of patients from DD- to DD+ (P<.0001), reducing underdiagnosis of early left ventricular diastolic dysfunction.
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