Radiographic Sarcopenia and Self-reported Exhaustion Independently Predict NSQIP Serious Complications After Pancreaticoduodenectomy in Older Adults
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Sarcopenia is linked to poor outcomes after abdominal surgery. We hypothesized that radiographic sarcopenia metrics enhance prediction of complications after pancreaticoduodenectomy (PD) when combined with clinical and frailty data.
Preoperative geriatric assessments and CT scans of patients undergoing PD were reviewed. Sarcopenia was assessed at L3 using total psoas area index (TPAI) and weighted average Hounsfield units (HU), i.e., estimates of psoas muscle volume and density. Outcomes included 30-day American College of Surgeons National Surgical Quality Improvement Program (NSQIP) serious complications, Clavien–Dindo complications, unplanned intensive care unit (ICU) admission, hospital length of stay (LOS), non-home facility (NHF) discharge, and readmission rates.
Low HU score correlated with NSQIP serious complications (r = −0.31, p = 0.0098), Clavien–Dindo complication grade (r = −0.29, p = 0.0183), unplanned ICU admission (r = −0.28, p = 0.0239), and NHF discharge (r = −0.25, p = 0.0426). Controlling for a “base model” of age, body mass index, American Society of Anesthesiologists score, and comorbidity burden, Fried’s exhaustion (odds ratio [OR] 4.72 [1.23–17.71], p = 0.021), and HU (OR 0.88 [0.79–0.98], p = 0.024) predicted NSQIP serious complications. Area under the receiver-operator characteristic (AUC) curves demonstrated that the combination of the base model, exhaustion, and HU trended towards improving the prediction of NSQIP serious complications compared with the base model alone (AUC = 0.81 vs. 0.70; p = 0.09). Additionally, when controlling for the base model, TPAI (β-coefficient = 0.55 [0.10–1.01], p = 0.018) and exhaustion (β-coefficient = 2.47 [0.75–4.20], p = 0.005) predicted LOS and exhaustion (OR 4.14 [1.48–11.6], p = 0.007) predicted readmissions.
When combined with clinical and frailty assessments, radiographic sarcopenia metrics enhance prediction of post-PD outcomes.
KeywordsHounsfield Unit Geriatric Assessment Short Physical Performance Battery Short Physical Performance Battery Score Unplanned Intensive Care Unit Admission
The authors gratefully acknowledge Mitchell C. Posner, M.D., Jeffrey B. Matthews, M.D., Eugene A. Choi, M.D., and Alaine Kamm, N.P., who recruited and cared for study patients and collected data; Aparna Palakodeti, Ph.D., who participated in study design and CT analysis; Teresa G. Barry and Randi Rothman, who performed GA and collected data; and Nneka Chukwueke, who collected data. Finally, we dedicate this work to the memory of our beloved friend and colleague, Joshua A. Hemmerich, Ph.D.
This study was funded by Carole and Gordon Segal, the Michael Rolfe Pancreatic Cancer Foundation, and the Ben D. Kissel Fund for Pancreatic Cancer Research. The authors maintained full independence in the conduct of this research and have no commercial interests in the subject of this study.
- 7.Walston J, Hadley EC, Ferrucci L, et al. Research agenda for frailty in older adults: toward a better understanding of physiology and etiology: summary from the American Geriatrics Society/National Institute on Aging Research Conference on Frailty in Older Adults. J Am Geriatr Soc. 2006;54(6):991–1001.Google Scholar
- 10.Hewitt J, Moug SJ, Middleton M, et al. Prevalence of frailty and its association with mortality in general surgery. Am J Surg. 2014;209:254–9.Google Scholar
- 11.Arya S, Kim SI, Duwayri Y, et al. Frailty increases the risk of 30-day mortality, morbidity, and failure to rescue after elective abdominal aortic aneurysm repair independent of age and comorbidities. J Vasc Surg. 2014;61:324–31.Google Scholar
- 21.Age adjusted Charlson Comorbidity Index. http://farmacologiaclinica.info/scales/Charlson_Comorbidity. Accessed 1 Nov 2014.
- 27.ACS NSQIP Surgical Risk Calculator. About the ACS Risk Calculator. http://www.riskcalculator.facs.org/Home/About/ Accessed 1 Nov 2014.
- 28.Bilimoria KY, Liu Y, Paruch JL, et al. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons. J Am Coll Surg. 2013;217(5):833–42; e1–3.Google Scholar
- 30.Cohen J CP, West SG, Aiken LS. Applied multiple regression/correlation analysis for the behavioral sciences. 3rd edn. Mahwah, NJ: Lawrence Earlbaum Associates; 2003.Google Scholar
- 40.Cooper AB, Slack R, Fogelman D, et al. Characterization of anthropometric changes that occur during neoadjuvant therapy for potentially resectable pancreatic cancer. Ann Surg Oncol. 2014;22:2416–23.Google Scholar