title: What predicts serious complications in colorectal cancer resection?
abstract: Virtually all volume-outcome studies use mortality as their outcome measure, yet most general surgical procedures have low in-patient death rates. We examined whether hospital surgical volume impacts other colorectal cancer resection outcomes and complications. Colorectal cancer (CRC) resections from 1996 to 2000 were identified using the California hospital discharge database. Comorbidity was graded using a modified Charlson index. Hospital CRC resection volume was calculated. Serious medical complications were defined as life-threatening cardiac or respiratory events, renal failure, or shock. Serious surgical complications were defined as vascular events, need for reoperation, or bleeding. Multivariate logistic regression analyses were performed to estimate the impact of predictors on complications. We identified 56,621 resections. Median age was 70 to 74 years. Eighty-one per cent of patients were white. Most had localized (57%) versus distant (22%) disease. Serious medical (17.5%) and surgical (9.8%) complications were not infrequent. In multivariate analyses, greater annual CRC surgical volume predicted lower odds of serious complication, but patient characteristics (age, comorbidity, and acuity of surgery) were more important. Although patients receiving CRC resection at lower-volume hospitals have greater odds of complication than patients treated at higher-volume institutions, patient factors remain the most important determinants of complication.
authors: David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
authors: David
authors: D
authors: Zingmond
authors: Melinda
authors: M
authors: Maggard
authors: Jessica
authors: J
authors: O'Connell
authors: Jerome
authors: J
authors: Liu
authors: David
authors: D
authors: Etzioni
authors: Clifford
authors: C
authors: Ko
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002140:California; D015179:Colorectal Neoplasms / Q000601:surgery*; D005260:Female; D006761:Hospitals / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011183:Postoperative Complications; D012307:Risk Factors