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Association of Volume With Outcome of Coronary Artery Bypass Graft Surgery: Scheduled vs Nonscheduled Operations

Showstack, Jonathan A.·1987·JAMA

Abstract

Empirical evidence suggests that mortality rates for coronary artery bypass graft (CABG) surgery are lower in hospitals that perform a higher volume of the procedure. In recent years, the criteria for CABG surgery have been expanded to include patients with a wide variety of co-morbidities. To address the question of whether the volume-outcome relationship continues to exist for this new group of patients, discharge abstracts for 18,986 CABG operations at 77 hospitals in California in 1983 were analyzed using multiple-regression techniques. Higher-volume hospitals had lower in-hospital mortality (adjusted for case mix); this effect was greatest in patients who might be characterized as having "non-scheduled" CABG surgery. Higher-volume hospitals also had shorter average postoperative lengths of stay and fewer patients with extremely long stays. The results of this study suggest that the greatest improvement in average outcomes for CABG surgery would result from the closure of low-volume surgery units.

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Crossref · 10.1001/jama.1987.03390060075027

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Metadata

Authors
Showstack, J. A.
Venue
JAMA
Published
1987-02-13
Volume
257
Issue
6
Pages
785
ISSN
  • 0002-9955 (ISSN-L)
  • 0098-7484
OpenAlex
W2090142454
Cited by
272
References
0
FWCI
12.80
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Association of Volume With Outcome of Coronary Artery Bypass Graft Surgery: Scheduled vs Nonscheduled Operations. https://app.cochat.ai/papers/10.1001/jama.1987.03390060075027
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Showstack, J. A. (1987). Association of Volume With Outcome of Coronary Artery Bypass Graft Surgery: Scheduled vs Nonscheduled Operations. JAMA. https://doi.org/10.1001/jama.1987.03390060075027

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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.