Holter bin Analysis

by FAbio BAdilini, PhD

June 25, 2010

Holter bin is a method used to quantify changes of electrocardiographic metrics from continuous recordings. This technique was introduced to characterize repolarization patterns in healthy subjects (1) and it has been applied to study several pathological conditions (2,3) and for the assessment of drug-induced ECG changes (4), particularly in the presence of heart rate changes (5).
Holter bin is based on the concept of selective beat averaging. An exploring time window is initially defined; within this time window all the cardiac beats characterized by the same preceding heart-rate (or RR interval) are pooled and averaged to form a representative waveform for that specific RR interval (or RR bin). When the variable of interest is the QT interval, the rule of selection can be tailored to meet further conditions, as for example to take into account (or to compensate for) the effect of hysteresis: for example excluding all the cardiac beats not preceded by stable heart rate or, alternatively, using the hysteresis-corrected RR interval by a mathematical model as the bin-inclusion parameter.
Holter bin requires adequate signal processing; for example the precise position of each cardiac beat should be properly verified and automatically adjusted (trigger jitter correction); at need, the individual cardiac complexes may need to be re-interpolated to improve the respective alignment before averaging. The exploring window should be rigorously controlled: for example, diurnal and nocturnal periods and, more in general, regions with known modified autonomic tone (for example exercise periods) should not be mixed in the same Holter bin session. The ideal length of the exploring window depends on the specific experiment. In the case of pharmaceutical trials, a 2 to 4-hours window centered at peak concentration has been typically used (4).
Holter bin is particularly suited to inspect metrics that need to be compared in conditions or maneuvers that modify the hart rate, for examples when comparing the effect of repolarization on drugs that change the baseline RR interval (5). Rather than enforcing the application of one or more QT/RR models models, the approach assesses changes by comparing the study parameters (e.g. QT interval) belonging to the same RR-bin, i.e. enforcing a comparison at identical heart-rate, thus avoiding the application of correction formulae.The typical output of an Holter-bin analysis session is typically a set of comparisons associated with each of the RR bin inspected: for example (in the context of a QT study) the averaged and the maximum QT difference across all the RR bins could be reported. Within-bin variability is important and can be assessed by several indicators such as the bin "density" (i.e. number of cardiac beats pooled inside each bin) or the variability of some parameters the individual beats included into the bin (for example SD of the beat-to-beat QT intervals).


    1. No need to implement correction models
    2. Good to assess changes associated with moderate (up to 10 bpm) heart rate changes, where the degree of RR overlap between baseline or placebo and on-drug is significant.
    3. QT hysteresis can be easily controlled.


    1. Within the exploring window cardiac beats are pooled according to the preceding heart rate and the time-scale is lost.
    2. Requires sophisticated beat-to-beat processing including appropriate quality control of automated ECG analyses.

[1] Badilini F, Maison-Blanche P, Childers R, Coumel P. QT Interval Analysis on Ambulatory Recordings: a Selective Beat Averaging Approach, Med & Bio Eng & Comp, 1999;37:71-79.
[2] Neyroud N, Maison-Blanche P, Denjoy I, Chevret S, Donger C, Dausse E, Fayn J, Badilini F, Menhabi N, Schwartz K, Guicheney P, Coumel P. Diagnostic Performance of QT Interval Variables from 24-hour Electrocardiography in the Long QT SyndromeEur Heart J, 1998; 19: 158-165.
[3] Milliez P, Leenhardt A, MaisonBlanche, P, Vicaut E, Badilini F, Siliste C, Benchetrit C, Coumel P. Usefulness of Ventricular Repolarization Dynamicity in Predicting Arrhythmic Deaths in Patients with Ischemic Cardiomyopathy  (From the European Myocardial Infarct Amiodarone Trial), Am J Cardiol, 2005; 95:821-826.
[4] Extramiana F, Maison-Blanche P, Cabanis MJ, Ortemann-Renon C, Beaufils P, Leenhardt A. Clinical assessment of drug-induced QT prolongation when associated with heart rate changes. Clinical Pharmacology & Therapeutics, 2005; 77(4): 247-258.
[5] Extramiana F, Maison-Blanche P, Haggui A, Badilini F, Beaufils P, Leenhardt A. Control of Rapid Heart Rate Changes for Electrocardiographic Analysis: Implications for Thorough QT Studies. Clin Cardiol, 2006; 29: 534-539.