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Cited by 742

The DOI matches its OpenAlex record; 3 of the 3 references it cites were found in a registry or an index.

The Nature and Course of Depression Following Myocardial Infarction

Steven J. Schleifer·1989·Archives of Internal Medicine

Abstract

Two hundred eighty-three patients admitted to cardiac care units for myocardial infarction at two urban teaching hospitals were interviewed 8 to 10 days after infarction and 171 were reinterviewed 3 to 4 months later. Initially, 45% met diagnostic criteria for minor or major depression, including 18% with major depressive syndromes. Depression was not associated with the severity of cardiac illness but was associated with the presence of noncardiac medical illnesses. Three to 4 months after infarction, 33% of patients met criteria for minor or major depression. The large majority of patients who initially met criteria for major but not minor depression showed evidence of depression at 3 months and most patients with major depression had not returned to work by 3 months. Treatment of major depressive syndromes after myocardial infarction may reduce chronicity and disability, while minor depressive syndromes may be similar to normal grief and tend to be self-limited.

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Metadata

Authors
Schleifer, S. J.
Venue
Archives of Internal Medicine
Publisher
American Medical Association
Published
1989-08-01
Volume
149
Issue
8
Pages
1785-1785
ISSN
0003-9926 (ISSN-L)
OpenAlex
W2038921909
Cited by
742
References
3
FWCI
6.65
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Nature and Course of Depression Following Myocardial Infarction. https://app.cochat.ai/papers/10.1001/archinte.149.8.1785
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Schleifer, S. J. (1989). The Nature and Course of Depression Following Myocardial Infarction. Archives of Internal Medicine. https://doi.org/10.1001/archinte.149.8.1785

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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.