HOMEPRODUCTSCOMPANYCONTACTFAQResearchDictionaryPharmaSign Up FREE or Login

Cross-sectional area of the abdomen predicts complication incidence in patients undergoing sternal reconstruction.

AbstractBACKGROUND:
Sternal reconstruction with vascularized flaps is central to the management of sternal wound infections and mediastinitis but carries a high risk of complications. There is a need to identify reliable predictors of complication risk to help inform patients and clinicians in preparation for surgery. Unfortunately, body mass index and serum albumin may not be reliable predictors of complication rates. Analytic morphomics provides a robust quantitative method to measure patients' obesity as it pertains to their risk of complications in undergoing sternal reconstruction.
METHODS:
We identified 34 patients with preoperative computed tomography scans of the abdomen from a cohort of sternal reconstructions performed between 1997 and 2010. Using semiautomated analytic morphomics, we identified the patients' skin and fascia layers between the ninth and 12th thoracic spine levels; from these landmarks, we calculated morphomic measurements of the patients' abdomens, including their total body cross sectional area and the cross sectional area of their subcutaneous fat. We obtained the incidence of complications from chart review and correlated the incidence of complications (including seroma, hematoma, recurrent wounds, mediastinitis, tracheostomy, and death) with patients' morphomic measurements.
RESULTS:
Sixty-two percent of patients (n = 21) suffered complications after their operation. Those who suffered from complications, relative to those who did not have complications, had increased visceral fat area (12,547.2 mm(2)versus 6569.9 mm(2), P = 0.0080), subcutaneous fat area (16,520.2 mm(2)versus 8020.1 mm(2), P = 0.0036), total body area (91,028.6 mm(2)versus 67,506.5 mm(2), P = 0.0022), fascia area (69,238.4 mm(2)versus 56,730.9 mm(2), P = 0.0118), total body circumference (1101.8 mm versus 950.2 mm, P = 0.0017), and fascia circumference (967.5 mm versus 868.1 mm, P = 0.0077). We also demonstrated a significant positive correlation between the previously mentioned morphomic measurements and the incidence of complications in multivariate logistic regression models, with odds ratios ranging from 1.19-3.10 (P values ranging from 0.010-0.022).
CONCLUSIONS:
Increases in abdominal morphomic measurements correlate strongly with the incidence of complications in patients undergoing sternal reconstruction. This finding may influence preoperative risk stratification and surgical decision making in this patient population.
AuthorsJeffrey H Kozlow, Jeffrey Lisiecki, Michael N Terjimanian, Jacob Rinkinen, Robert Cameron Brownley, Shailesh Agarwal, Stewart C Wang, Benjamin Levi
JournalThe Journal of surgical research (J Surg Res) Vol. 192 Issue 2 Pg. 670-7 (Dec 2014) ISSN: 1095-8673 [Electronic] United States
PMID24972736 (Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't)
CopyrightCopyright © 2014 Elsevier Inc. All rights reserved.
Topics
  • Abdomen (anatomy & histology)
  • Adult
  • Aged
  • Body Surface Area
  • Fascia (anatomy & histology)
  • Female
  • Humans
  • Incidence
  • Intra-Abdominal Fat (anatomy & histology)
  • Male
  • Middle Aged
  • Obesity (complications, epidemiology, pathology)
  • Postoperative Complications (epidemiology, etiology, pathology)
  • Predictive Value of Tests
  • Preoperative Period
  • Plastic Surgery Procedures (adverse effects, methods)
  • Risk Factors
  • Sternum (diagnostic imaging, surgery)
  • Subcutaneous Fat (anatomy & histology)
  • Tomography, X-Ray Computed
  • Treatment Outcome

Join CureHunter, for free Research Interface BASIC access!

Take advantage of free CureHunter research engine access to explore the best drug and treatment options for any disease. Find out why thousands of doctors, pharma researchers and patient activists around the world use CureHunter every day.
Realize the full power of the drug-disease research graph!


Choose Username:
Email:
Password:
Verify Password:
Enter Code Shown: