Geoffrey M Bove1, Susan L Chapelle1,2, Eleanor Boyle3,4, David J Mokler1, Jan Hartvigsen3,5. 1. a Department of Biomedical Sciences , University of New England College of Osteopathic Medicine , Biddeford , ME , USA. 2. b Squamish Integrated Health , Squamish , BC , Canada. 3. c Department of Sports Science and Clinical Biomechanics , University of Southern Denmark , Odense , Denmark. 4. d University of Toronto , Dalla Lana School of Public Health , Toronto , ON , Canada. 5. e Nordic Institute of Chiropractic and Clinical Biomechanics, University of Southern Denmark , Odense M , Denmark.
Abstract
Purpose/Aim: Postoperative adhesions remain an undesirable and commonly symptomatic side effect of abdominopelvic surgeries. Animal models of postoperative adhesions typically yield heterogeneous adhesions throughout the abdominal cavity and are not easily quantified. Here we present a novel method of postoperative adhesion assessment and report its reliability and measurement error. MATERIALS AND METHODS: A model of cecal abrasion with partial sidewall attachment was performed on female rats. After 1, 2, 4, or 7 days of recovery, the rats were euthanized and their abdominopelvic cavities were systematically evaluated for postoperative adhesions. The necropsy was recorded through the surgical microscope. Four raters were trained to use a ballot to capture key factors of the adhesions as they viewed the recordings. Their ratings were compared for measurement error and reliability (using Bland-Altman plots and intraclass correlation coefficients, respectively) and for the ability to discriminate differences in experimental groups. A subset of the data was analyzed to determine practical utility. RESULTS: The rating system was shown to have low measurement error and high inter-rater reliability for all parameters measured. Applied practically, the system was able to discriminate groups in a manner that was expected. CONCLUSIONS: We have developed and validated a rating system for postoperative adhesions and shown that it can detect group differences. This method can be used to quantify postoperative adhesions in rodent models.
Purpose/Aim: Postoperative adhesions remain an undesirable and commonly symptomatic side effect of abdominopelvic surgeries. Animal models of postoperative adhesions typically yield heterogeneous adhesions throughout the abdominal cavity and are not easily quantified. Here we present a novel method of postoperative adhesion assessment and report its reliability and measurement error. MATERIALS AND METHODS: A model of cecal abrasion with partial sidewall attachment was performed on female rats. After 1, 2, 4, or 7 days of recovery, the rats were euthanized and their abdominopelvic cavities were systematically evaluated for postoperative adhesions. The necropsy was recorded through the surgical microscope. Four raters were trained to use a ballot to capture key factors of the adhesions as they viewed the recordings. Their ratings were compared for measurement error and reliability (using Bland-Altman plots and intraclass correlation coefficients, respectively) and for the ability to discriminate differences in experimental groups. A subset of the data was analyzed to determine practical utility. RESULTS: The rating system was shown to have low measurement error and high inter-rater reliability for all parameters measured. Applied practically, the system was able to discriminate groups in a manner that was expected. CONCLUSIONS: We have developed and validated a rating system for postoperative adhesions and shown that it can detect group differences. This method can be used to quantify postoperative adhesions in rodent models.
Authors: Susan H Whang; J Andres Astudillo; Emanuel Sporn; Sharon L Bachman; Brent W Miedema; Wade Davis; Klaus Thaler Journal: J Surg Res Date: 2009-07-15 Impact factor: 2.192
Authors: Karen L Reed; A Brent Fruin; Kelly K Bishop-Bartolomei; Adam C Gower; Michael Nicolaou; Arthur F Stucchi; Susan E Leeman; James M Becker Journal: J Surg Res Date: 2002-11 Impact factor: 2.192
Authors: Geoffrey M Bove; Susan L Chapelle; Katherine E Hanlon; Michael P Diamond; David J Mokler Journal: PLoS One Date: 2017-06-02 Impact factor: 3.240