Which is the best Myocardial Work index for the prediction of coronary artery disease? A data meta-analysis

Early diagnosis of Coronary Artery Disease (CAD) plays a key role to prevent adverse cardiac events such as myocardial infarction and Left Ventricular (LV) dysfunction. Myocardial Work (MW) indices derived from echocardiographic speckle tracking data in combination with non-invasive blood pressure recordings seems promising to predict CAD even in the absence of impairments of standard echocardiographic parameters. Our aim was to compare the diagnostic accuracy of MW indices to predict CAD and to assess intra- and inter-observer variability of MW through a meta-analysis.

Electronic databases were searched for observational studies evaluating the MW indices diagnostic accuracy for predicting CAD and intra- and inter-observer variability of MW indices. Pooled sensitivity, specificity, and Summary Receiver Operating Characteristic (SROC) curves were assessed.

Five studies enrolling 501 patients met inclusion criteria. Global Constructive Work (GCW) had the best pooled sensitivity (89%) followed by GLS (84%), Global Work Index (GWI) (82%), Global Work Efficiency (GWE) (80%), and Global Wasted Work (GWW) (75%). GWE had the best pooled specificity (78%) followed by GWI (75%), GCW (70%), GLS (68%), and GWW (61%). GCW had the best accuracy according to SROC curves, with an area under the curve of 0.86 compared to 0.84 for GWI, 0.83 for GWE, 0.79 for GLS, and 0.74 for GWW. All MW indices had an excellent intra- and inter-observer variability.

GCW is the best MW index proving best diagnostic accuracy in the prediction of CAD with an excellent reproducibility.