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Cited by 403

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

New method for assessing cardiac parasympathetic activity using 24 hour electrocardiograms.

Open access
Ewing, D J, Neilson, J M, Travis, P·1984·Heart

Abstract

Cardiac parasympathetic activity was assessed using 24 hour electrocardiographic recordings by measuring the incidence of larger changes in successive RR intervals, which in normal subjects occur frequently but irregularly. In 25 normal subjects the mean number of times per hour in which the change in successive RR interval was greater than 50 ms was 150-250 during waking and 350-450 during sleeping. By contrast, 30 diabetics with medically denervated hearts (12 with cardiovascular reflex evidence of parasympathetic damage and 18 with additional sympathetic damage) and six cardiac transplant patients with surgically denervated hearts had extremely low counts. Additionally, of 20 diabetics with normal cardiovascular reflexes, about half had abnormally low counts, suggesting that this method is better than currently available reflex tests in detecting early cardiac parasympathetic damage. This technique provides a valid and sensitive way of monitoring cardiac parasympathetic activity over prolonged periods.

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Metadata

Authors
Ewing, D. J., Neilson, J. M., & Travis, P.
Venue
Heart
Publisher
BMJ
Published
1984-10-01
Volume
52
Issue
4
Pages
396-402
ISSN
1355-6037 (ISSN-L)
OpenAlex
W2023233510
Cited by
403
References
13
FWCI
3.92
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: New method for assessing cardiac parasympathetic activity using 24 hour electrocardiograms. https://app.cochat.ai/papers/10.1136/hrt.52.4.396
The paper
Ewing, D. J., Neilson, J. M., & Travis, P. (1984). New method for assessing cardiac parasympathetic activity using 24 hour electrocardiograms. Heart. https://doi.org/10.1136/hrt.52.4.396

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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