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Ann Surg. 2012 Nov;256(5):697-704; discussion 704-5. doi: 10.1097/SLA.0b013e31827241d5.

Incidence and risks of liver resection: an all-inclusive French nationwide study.

Author information

1
Department of Hepatobiliopancreatic Surgery and Liver Transplantation, Hôpital Beaujon, AP-HP, Université Paris 7, 100 bld du General Leclerc, Clichy, France. olivier.farges@bjn.aphp.fr

Abstract

OBJECTIVE:

To evaluate at a national level the incidence of liver resection, postoperative mortality, and variables that predict this outcome.

BACKGROUND:

Data on indications of and results of liver resection are mainly derived from high-volume centers. Nationwide data are lacking.

METHODS:

French health care databases were screened to identify all patients who had undergone elective hepatectomy between 2007 and 2010. The patients' age, address, associated conditions, indication and extent of hepatic (or extrahepatic) surgery and the hospital type, location, and hepatectomy caseload were retrieved. Logistic regression was used to measure the influence of these parameters on in-hospital and 90-day mortality rates. The model, created using patients operated on in 2007 and 2009, was tested in those operated on in 2008 and 2010.

RESULTS:

Overall, 28,708 hepatectomies were performed. The annual incidence (13.2 per 10 adult inhabitants) varied between regions, but the extremal quotient was limited to 2.2 because 15% of the operations took place outside the patients' home region. Hospitals performed a median of 4 resections per year but 53% of all resections were performed in institutions with a volume of more than 50 per year. Treatment for primary tumors and major resections correlated with hepatectomy caseload. In-hospital and 90-day mortality were 3.4% and 5.8%, respectively. The area under the receiver operating characteristic curve of the prognostic model was 0.78/0.77 in the training and validation sample.

CONCLUSIONS:

There were significant disparities in practice. In-hospital mortality underestimated true, postoperative mortality by more than 50%. The model created may be useful for more efficient regionalization of care and patient counseling.

PMID:
23095612
DOI:
10.1097/SLA.0b013e31827241d5
[Indexed for MEDLINE]

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