Literature DB >> 23945530

Predicting abdominal closure after component separation for complex ventral hernias: maximizing the use of preoperative computed tomography.

Brenton R Franklin1, Ketan M Patel, Maurice Y Nahabedian, Laura E Baldassari, Emil I Cohen, Parag Bhanot.   

Abstract

BACKGROUND: Component separation techniques (CSTs) have allowed for midline fascial reapproximation in large midline ventral hernias. In certain cases, however, fascial apposition is not feasible, resulting in a bridged repair that is suboptimal. Previous estimates on myofascial advancement are based on hernia location and do not take into account variability between patients. Examination of preoperative computed tomography (CT) may provide insight into these variabilities and may allow for prediction of abdominal closure with CST. STUDY
DESIGN: A retrospective review was conducted of patients who underwent abdominal wall reconstruction from 2007 to 2012 with CST. Preoperative CT was obtained, and specific parameters were analyzed using image analysis software. Logistic regression was used to predict ideal operative closure. Multivariate analyses were adjusted for age and sex. An a priori value was set at P < 0.05.
RESULTS: Fifty-four patients met the criteria and had preoperative CT available for analysis. Forty-eight patients had fascial reapproximation achieved, whereas 6 patients had a bridged repair. Age, sex, weight, and body mass index were similar between groups (P > 0.05). Significant differences were seen between groups in 3 variables: transverse defect size (19.8 vs 10 cm, P < 0.05), defect area (420 vs 184.2 cm, P < 0.05), and percent abdominal wall defect (18.9% vs 10.6%, P < 0.05).
CONCLUSIONS: Preoperative determination of abdominal wall defect ratios and hernia defect areas may represent a more accurate method to predict abdominal wall closure after CST. Predicting midline approximation after CST is critical because outcomes after bridged repair can result in higher recurrence rates.

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Year:  2013        PMID: 23945530     DOI: 10.1097/SAP.0b013e3182773915

Source DB:  PubMed          Journal:  Ann Plast Surg        ISSN: 0148-7043            Impact factor:   1.539


  7 in total

1.  Three-dimensional hernia analysis: the impact of size on surgical outcomes.

Authors:  Kathryn A Schlosser; Sean R Maloney; Tanushree Prasad; Paul D Colavita; Vedra A Augenstein; B Todd Heniford
Journal:  Surg Endosc       Date:  2019-06-24       Impact factor: 4.584

2.  BMI: does it predict the need for component separation?

Authors:  J R Smith; R Kyriakakis; M P Pressler; G D Fritz; A T Davis; A L Banks-Venegoni; L T Durling
Journal:  Hernia       Date:  2022-03-21       Impact factor: 4.739

3.  Validation of a simple technique of volumetric analysis of complex incisional hernias without 3D CT scan reconstruction.

Authors:  Mazen R Al-Mansour; Jacqueline Wu; Greg Gagnon; Alexander Knee; John Romanelli; Neal E Seymour
Journal:  Surg Endosc       Date:  2021-04-15       Impact factor: 4.584

4.  Linear versus volumetric CT analysis in predicting tension-free fascial closure in abdominal wall reconstruction.

Authors:  M R Al-Mansour; J Wu; G Gagnon; A Knee; J R Romanelli; N E Seymour
Journal:  Hernia       Date:  2021-01-03       Impact factor: 4.739

Review 5.  Imaging complex ventral hernias, their surgical repair, and their complications.

Authors:  Steve Halligan; Sam G Parker; Andrew A Plumb; Alastair C J Windsor
Journal:  Eur Radiol       Date:  2018-03-12       Impact factor: 5.315

6.  Computed Tomography Image Analysis in Abdominal Wall Reconstruction: A Systematic Review.

Authors:  Omar Elfanagely; Joseph A Mellia; Sammy Othman; Marten N Basta; Jaclyn T Mauch; John P Fischer
Journal:  Plast Reconstr Surg Glob Open       Date:  2020-12-16

7.  Are preoperative CT variables associated with the success or failure of subsequent ventral hernia repair: nested case-control study.

Authors:  Shankar Kumar; Nikhil Rao; Sam Parker; Andrew Plumb; Alastair Windsor; Sue Mallett; Steve Halligan
Journal:  Eur Radiol       Date:  2022-03-29       Impact factor: 7.034

  7 in total

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