An estimated 400,000 Americans, and millions more worldwide, die suddenly each year. These events are most often initiated with a sustained ventricular tachyarrhythmia, including ventricular tachycardia (monomorphic or polymorphic), ventricular flutter, or ventricular fibrillation, with a smaller percentage related to a primary bradyarrhythmia. Sudden cardiac death syndrome may be due to a wide variety of different electrical and mechanical substrates, including acute myocardial infarction, chronic coronary disease with prior myocardial infarction(s), cardiomyopathies, myocarditis, valvular heart disease, right ventricular dysplasia, the long Q-T syndrome (acquired or congenital), Wolff-Parkinson-White pre-excitation, the Brugada syndrome, drug toxicity (e.g., proarrhythmic effects of cardioactive drugs; epinephrine, cocaine, and related stimulants), and so forth. Moreover, some individuals have no demonstrable electrical or mechanical predisposition.

Data Description

Physionet has inaugurated a Sudden Cardiac Death Database to support research and to stimulate progress in this important area of electrophysiology. We initiate this database with 23 complete Holter recordings (originally collected by Scott Greenwald while he was at MIT), from which half-hour excerpts have been available to researchers since 1989 as the MIT-BIH Malignant Ventricular Arrhythmia Database. The database currently includes 18 patients with underlying sinus rhythm (4 with intermittent pacing), 1 who was continuously paced, and 4 with atrial fibrillation. All patients had a sustained ventricular tachyarrhythmia, and most had an actual cardiac arrest.

These recordings were mainly obtained in the 1980s in Boston area hospitals, and were later compiled as part of a study of ventricular arrhythmias. Because of the retrospective nature of this collection, there are important limitations. Patient information is limited, and sometimes completely unavailable, including data regarding drug regimens and drug dosages. Further, these cases may not be representative of spontaneous episodes of sudden death in what is likely a very heterogenous group of subjects. Despite these shortcomings, these unique recordings may provide important clues to the pathogenesis of sudden death syndrome.

This is a small collection of an important type of data. The task of annotating this database is particularly difficult because of the complexity of the included cardiac rhythms. We invite the community to help us make this collection larger, more representative, and more useful, and to annotate it more thoroughly and rigorously. We welcome contributions of additional data from other investigators who have access to similar records. We also invite interested researchers to review and revise the annotation files provided for these recordings; if you are interested in participating in this effort, please write for additional information. We will gratefully acknowledge all contributions.

References

• Greenwald SD, Albrecht P, Moody GB, Mark RG. Estimating confidence limits for arrhythmia detector performance. Computers in Cardiology 1985; 12:383-386.
• Greenwald SD. Development and analysis of a ventricular fibrillation detector. M.S. thesis, MIT Dept. of Electrical Engineering and Computer Science, 1986.
• Goldberger AL, Rigney DR, Mietus J, Antman EW, Greenwald S. Nonlinear dynamics in sudden cardiac death syndrome: heart rate oscillations and bifurcations. Experientia 1988; 44:983-987. [Abstract] (Analysis based on 16 subjects with underlying sinus rhythm.)
• Courtemanche M, Glass L. Rosengarten MD, Goldberger AL. Beyond pure parasystole: promises and problems in modeling complex arrhythmias. Am J Physiol 1989; 257 (Heart Circ Physiol 26):H693-H706. [Abstract] (Case 2 in this report is based on data from record 47 of this database.)
• Goldberger AL, Rigney DR. On the non-linear motions of the heart: fractals, chaos and cardiac dynamics. In: Goldbeter A, ed. Cell to Cell Signaling: From Experiments to Theoretical Models. San Diego: Academic Press, 1989, pp. 541-550. (Figure 4, showing complex periodic patterns of ventricular premature beats, is derived from a record in this database.)

ECG data and beat annotations

A list in plain text form of the names of the records in this database can be found here.

Clinical information

When using this resource, please cite the original publication:

Greenwald SD. Development and analysis of a ventricular fibrillation detector. M.S. thesis, MIT Dept. of Electrical Engineering and Computer Science, 1986.

Please include the standard citation for PhysioNet: (show more options)
Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.