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Early detection of silent ischaemic heart disease by 24-hour electrocardiographic monitoring of active subjects.

Open access
Stern, S, Tzivoni, D·1974·Heart

Abstract

Continuous 24-hour recordings of the electrocardiogram during everyday activities were obtained in 8o subjects with praecordial symptoms, who had normal 12-lead resting electrocardiograms and negative Master two-step tests.The ages of the subjects varied between 4I and 76 years (average 54-7).Forty-three were men and 37 were women, with similar age distribution in each of the sexes.In 37 patients ischaemic ST-T changes were observed during various phases of the day, the incidence being higher among men (55_5%), than women (37.8%).Follow-up examinations 6 to I2 months later in these 37 patients revealed that i patient had had a myocardial infarction, 7 others had developed pathological changes in the resting electrocardiogram, and in I6 patients the praecordial symptoms had become worse.In the 43 subjects in whom the 24-hour monitoring was negative, none developed ischaemic attacks, deterioration in clinical symptomatology, or changes in the resting electrocardiogram during the 6 to I2 month folloup period.We conclude that 24-hour monitoring of the electrocardiogram under normal everyday activity is a reliable and convenient method for detecting ischaemnic changes at an early stage.

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Metadata

Authors
Stern, S., & Tzivoni, D.
Venue
Heart
Publisher
BMJ
Published
1974-05-01
Volume
36
Issue
5
Pages
481-486
ISSN
1355-6037 (ISSN-L)
OpenAlex
W2069356652
Cited by
366
References
0
FWCI
5.83
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Early detection of silent ischaemic heart disease by 24-hour electrocardiographic monitoring of active subjects. https://app.cochat.ai/papers/10.1136/hrt.36.5.481
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Stern, S., & Tzivoni, D. (1974). Early detection of silent ischaemic heart disease by 24-hour electrocardiographic monitoring of active subjects. Heart. https://doi.org/10.1136/hrt.36.5.481

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.