Treatment options for patients with coronary artery disease identified as high risk by T-wave alternans testing

An α-glucosidase inhibitor could reduce T-wave alternans in type 2 diabetes patients

BACKGROUND

We tested the hypothesis that an alpha-glucosidase inhibitor (α-GI), miglitol, is effective in protecting the cardiovascular system in type 2 diabetes mellitus (T2DM).

METHODS

We studied 19 hospitalized heart disease patients with T2DM in whom we performed continuous glucose monitoring, Holter electrocardiogram, and ambulatory blood pressure (BP) monitoring simultaneously for 48h. The α-GI miglitol was administered for half of the study period by a cross-over fashion. T-wave alternans (TWA), a marker of future fatal arrhythmic events, was also analyzed by Holter ECG.

RESULTS

Of the 19 patients, the measures of glucose variability were significantly lower during miglitol therapy than in control period. BP variability was similar with/without miglitol. However, TWA was significantly lower during the miglitol period compared to control period (63±4.8 vs. 75.8±5.1μV, p=0.032).

CONCLUSION

An α-GI, miglitol, can reduce TWA by reducing the fluctuation of glucose in heart disease patients with T2DM.

The detection of T-wave variation linked to arrhythmic risk: an industry perspective

Although the scientific literature contains ample descriptions of peculiar patterns of repolarization linked to arrhythmic risk, the objective quantification and classification of these patterns continues to be a challenge that impacts their widespread adoption in clinical practice. To advance the science, computerized algorithms spawned in the academic environment have been essential in order to find, extract and measure these patterns. However, outside the strict control of a core lab, these algorithms are exposed to poor quality signals and need to be effective in the presence of different forms of noise that can either obscure or mimic the T-wave variation (TWV) of interest. To provide a practical solution that can be verified and validated for the market, important tradeoffs need to be made that are based on an intimate understanding of the end-user as well as the key characteristics of either the signal or the noise that can be used by the signal processing engineer to best differentiate them. To illustrate this, two contemporary medical devices used for quantifying T-wave variation are presented, including the modified moving average (MMA) for the detection of T-wave Alternans (TWA) and the quantification of T-wave shape as inputs to the Morphology Combination Score (MCS) for the trending of drug-induced repolarization abnormalities.