Predictive value of sarcopenia and visceral obesity for postoperative pancreatic fistula after pancreaticoduodenectomy analyzed on clinically acquired CT and MRI View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-05

AUTHORS

Minji Jang, Hyung Woo Park, Jimi Huh, Jong Hwa Lee, Yoong Ki Jeong, Yang Won Nah, Jisuk Park, Kyung Won Kim

ABSTRACT

OBJECTIVE: To evaluate predictive values of sarcopenia and visceral obesity measured from preoperative CT/MRIs for postoperative pancreatic fistula (POPF) after pancreaticoduodenectomy in patients with periampullary malignancies. METHODS: From the prospectively constructed surgical registry, we included adult patients treated with pancreaticoduodenectomy. Based on CT/MRIs, body morphometric analysis was performed to evaluate the visceral obesity and sarcopenia, based on the areas of visceral fat and skeletal muscle measured at the L3 vertebrae level. We retrieved various perioperative factors from registry. As outcomes of postoperative complications, we evaluated POPF and major complications based on the Clavien-Dindo classification. Multivariate logistic regression analyses were performed. RESULTS: From a total of 284 patients (163 males, 121 females) who met the inclusion/exclusion criteria, POPF, major complications, and 60-day mortality occurred in 52 (18.3%), 34 (12.0%), and 6 (2.1%), respectively. Sarcopenia and visceral obesity were noted in 123 (75.5%) and 66 (40.5%) of men and 68 (56.2%) and 53 (43.8%) of women, respectively. Combination of sarcopenia and obesity (sarcopenic obesity) was noted in 31.9% (52/163) of men and in 26.4% (32/121) of women. In multivariate logistic regression analyses, sarcopenic obesity was the only independent predictor for POPF (OR 2.65, 95% CI 1.43-4.93), and the vascular resection during pancreaticoduodenectomy was the only independent predictor for severe complications (OR 3.75, 95% CI 1.61-8.70). CONCLUSION: Sarcopenic obesity might be highly predictive for POPF. Body morphometric analysis in preoperative CT/MRI combined with assessment of perioperative clinical features may help to identify high-risk patients and determine perioperative management strategies. KEY POINTS: • Sarcopenic obesity might be predictive for postoperative pancreatic fistula after pancreaticoduodenectomy. • The vascular resection during pancreaticoduodenectomy might be predictive of major complications. • Body morphometric analysis might be helpful for identifying high-risk patients. More... »

PAGES

2417-2425

References to SciGraph publications

  • 2009-09. Adipose Tissue: The New Endocrine Organ? A Review Article in DIGESTIVE DISEASES AND SCIENCES
  • 2012-08. Impact of Sarcopenia on Outcomes Following Resection of Pancreatic Adenocarcinoma in JOURNAL OF GASTROINTESTINAL SURGERY
  • 2010-03. Is an estimation of physiologic ability and surgical stress able to predict operative morbidity after pancreaticoduodenectomy? in JOURNAL OF HEPATO-BILIARY-PANCREATIC SCIENCES
  • 2019-02. Association of paraspinal muscle water–fat MRI-based measurements with isometric strength measurements in EUROPEAN RADIOLOGY
  • 2016-09. Preoperative Sarcopenia Strongly Influences the Risk of Postoperative Pancreatic Fistula Formation After Pancreaticoduodenectomy in JOURNAL OF GASTROINTESTINAL SURGERY
  • 2014-05. Assessment of sarcopenia and changes in body composition after neoadjuvant chemotherapy and associations with clinical outcomes in oesophageal cancer in EUROPEAN RADIOLOGY
  • 2006-10. Adipocytokines: mediators linking adipose tissue, inflammation and immunity in NATURE REVIEWS IMMUNOLOGY
  • 2010-11. Redefining Mortality After Pancreatic Cancer Resection in JOURNAL OF GASTROINTESTINAL SURGERY
  • 2016-05. Markers of sarcopenia quantified by computed tomography predict adverse long-term outcome in patients with resected oesophageal or gastro-oesophageal junction cancer in EUROPEAN RADIOLOGY
  • 2012-05. Limitations of Patient-Associated Co-Morbidity Model in Predicting Postoperative Morbidity and Mortality in Pancreatic Operations in JOURNAL OF GASTROINTESTINAL SURGERY
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    URI

    http://scigraph.springernature.com/pub.10.1007/s00330-018-5790-7

    DOI

    http://dx.doi.org/10.1007/s00330-018-5790-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1109759801

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30406311


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