Literature DB >> 21601491

Surgical site infection and analytic morphometric assessment of body composition in patients undergoing midline laparotomy.

Jay S Lee1, Michael N Terjimanian, Lindsay M Tishberg, Abbas Z Alawieh, Calista M Harbaugh, Kyle H Sheetz, Sven A Holcombe, Stewart C Wang, Christopher J Sonnenday, Michael J Englesbe.   

Abstract

BACKGROUND: Obesity is a known risk factor for surgical site infection (SSI). Our hypothesis is that morphometric measures of midline subcutaneous fat will be associated with increased risk of SSI and will predict SSI better than conventional measures of obesity. STUDY
DESIGN: We identified 655 patients who underwent midline laparotomy (2006 to 2009) using the Michigan Surgical Quality Collaborative database. Using novel, semiautomated analytic morphometric techniques, the thickness of subcutaneous fat along the linea alba was measured between T12 and L4. To adjust for variations in patient size, subcutaneous fat was normalized to the distance between the vertebrae and anterior skin. Logistic regression analyses were used to identify factors independently associated with the incidence of SSI.
RESULTS: Overall, SSIs were observed in 12.5% (n = 82) of the population. Logistic regression revealed that patients with increased subcutaneous fat had significantly greater odds of developing a superficial incisional SSI (odds ratio [OR] = 1.76 per 10% increase, 95% CI 1.10 to 2.83, p = 0.019). Smoking, steroid use, American Society of Anesthesiologists (ASA) classification, and incision-to-close operative time were also significant independent risk factors for superficial incisional SSI. When comparing subcutaneous fat and body mass index (BMI) as the only model variables, subcutaneous fat significantly improved model predictions of superficial incisional SSI (area under the receiver operating characteristic curve [AUC] 0.60, p = 0.023); BMI did not (AUC 0.52, p = 0.73).
CONCLUSIONS: Abdominal subcutaneous fat is an independent predictor of superficial incisional SSI after midline laparotomy. Novel morphometric measures may improve risk stratification and help elucidate the pathophysiology of surgical complications.
Copyright © 2011 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21601491      PMCID: PMC3144280          DOI: 10.1016/j.jamcollsurg.2011.04.008

Source DB:  PubMed          Journal:  J Am Coll Surg        ISSN: 1072-7515            Impact factor:   6.113


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