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Cited by 334

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

Catabolic Illness: Strategies for Enhancing Recovery

Flier, Jeffrey S., Underhill, Lisa H., Wilmore, Douglas W.·1991·New England Journal of Medicine

Abstract

After injury, infection, extensive chemotherapy, and other critical illnesses, both protein and fat are lost from the body. Although minor alterations in body composition are probably of little clinical importance, losses of body protein of 10 percent or more contribute to morbidity and debility. This catabolic response can be modified and recovery can be accelerated by a variety of approaches. First, the inflammatory response can be reduced; second, specific nutrients can be provided to support the patient's tissue requirements during catabolic illness; and third, growth factors can be used to enhance protein synthesis and tissue repair. These approaches, whether used alone or in combination, will reduce the loss of body protein, which should accelerate recovery, shorten the length of hospitalization, and reduce convalescence.

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Crossref · 10.1056/nejm199109053251005

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Metadata

Authors
Flier, J. S., Underhill, L. H., & Wilmore, D. W.
Venue
New England Journal of Medicine
Published
1991-09-05
Volume
325
Issue
10
Pages
695-702
ISSN
  • 0028-4793 (ISSN-L)
  • 1533-4406
OpenAlex
W2038833653
Cited by
334
References
3
FWCI
27.11
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Catabolic Illness: Strategies for Enhancing Recovery. https://app.cochat.ai/papers/10.1056/nejm199109053251005
The paper
Flier, J. S., Underhill, L. H., & Wilmore, D. W. (1991). Catabolic Illness: Strategies for Enhancing Recovery. New England Journal of Medicine. https://doi.org/10.1056/nejm199109053251005

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.