Association between institutional case volume and mortality following thoracic aorta replacement: a nationwide Korean cohort study View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2020-06-29

AUTHORS

Karam Nam, Eun Jin Jang, Jun Woo Jo, Jae Woong Choi, Minkyoo Lee, Ho Geol Ryu

ABSTRACT

BackgroundThe inverse relationship between case volume and postoperative mortality following high-risk surgical procedures have been reported. Thoracic aorta surgery is associated with one of the highest postoperative mortality. The relationship between institutional case volume and postoperative mortality in patients undergoing thoracic aorta replacement surgery was evaluated.MethodsAll thoracic aorta replacement surgeries performed in Korea between 2009 and 2016 in adult patients were analyzed using an administrative database. Hospitals were divided into low (< 30 cases/year), medium (30–60 cases/year), or high (> 60 cases/year) volume centers depending on the annual average number of thoracic aorta replacement surgeries performed. The impact of case volume on in-hospital mortality was assessed using the logistic regression.ResultsAcross 83 hospitals, 4867 cases of thoracic aorta replacement were performed. In-hospital mortality was 8.6% (191/2222), 10.7% (77/717), and 21.9% (422/1928) in high, medium, and low volume centers, respectively. The adjusted risk of in-hospital mortality was significantly higher in medium (odds ratio [OR], 1.56; 95% confidence interval [CI], 1.16–2.11, P = 0.004) and low volume centers (OR, 3.12; 95% CI, 2.54–3.85, P < 0.001) compared to high volume centers.ConclusionsPatients who had underwent thoracic aorta replacement surgery in lower volume centers had increased risk of in-hospital mortality after surgery compared to those in higher volume centers. Our results may provide the basis for minimum case volume requirement or regionalization in thoracic aorta replacement surgery for optimal patient outcome. More... »

PAGES

156

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13019-020-01204-0

DOI

http://dx.doi.org/10.1186/s13019-020-01204-0

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https://app.dimensions.ai/details/publication/pub.1128835922

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/32600356


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