Key result
Automated beat-to-beat QT algorithm yields low variance and accurately detects moxifloxacin-induced changes.
Why the study?
Does an automated algorithm reliably measure beat-to-beat QT intervals and detect moxifloxacin-induced changes?
Does an automated algorithm reliably measure beat-to-beat QT intervals and detect moxifloxacin-induced changes?
An automated algorithm for beat-to-beat QT measurement demonstrates low variance and successfully detects drug-induced QT changes, offering a potential alternative to manual methods.
May support automated QT monitoring in early drug studies; leaves open broader validation before clinical use.
BACKGROUND: Concern for drug-induced QT prolongation has caused significant investment in QT measurement to safety-test new compounds. Manual methods are expensive and time-consuming. Reliable automatic methods would be highly desirable. METHODS: Twelve-lead Holter recordings were annotated beat-to-beat by an automatic algorithm for global QRS onset and T offset. T offset was established from the time of peak T downslope plus a rate-dependent offset, analogous to the "tangent method," wherein T offset is determined by extrapolating the T downslope to an intersection with the baseline. RESULTS AND CONCLUSIONS: Variances of the beat-to-beat QT measurements were in the range 2.5-3.4 ms over three distinct databases, including a large heart failure database. Application to a moxifloxacin/placebo control database of 29 subjects showed excellent results.
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David Mortara (2009) studied Drug-induced QT prolongation (n=29). Automatic algorithm for beat-to-beat QT measurement was evaluated on Variances of the beat-to-beat QT measurements. An automatic algorithm for beat-to-beat QT measurement yielded variances of 2.5-3.4 ms across three databases and performed well in a 29-subject moxifloxacin/placebo database.
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