Predictors of complications in gynaecological oncological surgery: a prospective multicentre study (UKGOSOC—UK gynaecological oncology surgical outcomes and complications)

Autor: Andrew J. Nordin, R Desai, Adeola Olaitan, R Gornall, Ranjit Manchanda, S Varkey, S Shanbhag, D Meechan, K. Hillaby, K. Reynolds, Usha Menon, A Thackeray, B Rufford, R Iyer, A Gentry-Maharaj, A Beardmore-Gray, S Leeson, Alberto Lopes, N. Das, Matthew Burnell, J Nevin, Andy Ryan, Robert Liston, Tim Mould, Nicholas J Wood, A Linder
Jazyk: angličtina
Rok vydání: 2014
Předmět:
Zdroj: British Journal of Cancer
ISSN: 1532-1827
0007-0920
Popis: Background: There are limited data on surgical outcomes in gynaecological oncology. We report on predictors of complications in a multicentre prospective study. Methods: Data on surgical procedures and resulting complications were contemporaneously recorded on consented patients in 10 participating UK gynaecological cancer centres. Patients were sent follow-up letters to capture any further complications. Post-operative (Post-op) complications were graded (I–V) in increasing severity using the Clavien-Dindo system. Grade I complications were excluded from the analysis. Univariable and multivariable regression was used to identify predictors of complications using all surgery for intra-operative (Intra-op) and only those with both hospital and patient-reported data for Post-op complications. Results: Prospective data were available on 2948 major operations undertaken between April 2010 and February 2012. Median age was 62 years, with 35% obese and 20.4% ASA grade ⩾3. Consultant gynaecological oncologists performed 74.3% of operations. Intra-op complications were reported in 139 of 2948 and Grade II–V Post-op complications in 379 of 1462 surgeries. The predictors of risk were different for Intra-op and Post-op complications. For Intra-op complications, previous abdominal surgery, metabolic/endocrine disorders (excluding diabetes), surgical complexity and final diagnosis were significant in univariable and multivariable regression (P
Databáze: OpenAIRE