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Can Sarcopenia Quantified by Computed Tomography Scan Predict Adverse Outcomes in Emergency General Surgery?
J Surg Res. 2019 03; 235:141-147.JS

Abstract

BACKGROUND

Sarcopenia (a decline of skeletal muscle mass) has been identified as a predictor of poor postoperative outcomes. The impact of sarcopenia in emergency general surgery (EGS) remains undetermined. The aim of this study was to evaluate the association between sarcopenia and outcomes after EGS.

METHODS

A 3-y (2012-15) review of all EGS patients aged ≥45 y was presented to our institution. Patients who underwent computer tomography-abdomen were included. Sarcopenia was defined as the lowest sex-specific quartile of total psoas index (computer tomography-measured psoas area normalized for body surface area). Patients were divided into sarcopenic (SA) and nonsarcopenic. Primary outcome measures were in-hospital complications, hospital-length of stay [h-LOS], intensive care unit-length of stay, adverse discharge disposition, and in-hospital mortality. Our secondary outcome measures were 30-d complications, readmissions, and mortality.

RESULTS

Four hundred fifty-two patients undergoing EGS were included. Mean age was 58 ± 8.7 y, and 60% were males. Hundred thirteen patients were categorized as SA. Compared to nonsarcopenic, SA patients had higher rates of minor complications (28% versus 17%, P = 0.01), longer hospital-length of stay (7d versus 5d, P = 0.02), and were more likely to be discharged to skilled nursing facility/Rehab (35% versus 17%, P = 0.01). There was no difference between the two groups regarding major complications, intensive care unit-length of stay, mortality, and 30-d outcomes. On regression analysis, sarcopenia was an independent predictor of minor complications (OR 1.8 [1.6-3.7]) and discharge to rehab/SNIF (OR: 1.9 [1.5-3.2]). However, there was no association with major complications, mortality, 30-d complications, readmissions, and mortality.

CONCLUSIONS

Sarcopenia is an independent predictor of minor postoperative complications, prolonged hospital-length of stay, and an adverse discharge disposition in patients undergoing EGS. Identifying SA EGS patients will improve both resource allocation and discussion about the patient's prognosis between physicians, patients, and their families.

Authors+Show Affiliations

Division of Trauma, Critical Care, Emergency Surgery, and Burns, Department of Surgery, College of Medicine, University of Arizona, Tucson, Arizona.Division of Trauma, Critical Care, Emergency Surgery, and Burns, Department of Surgery, College of Medicine, University of Arizona, Tucson, Arizona.Division of Trauma, Critical Care, Emergency Surgery, and Burns, Department of Surgery, College of Medicine, University of Arizona, Tucson, Arizona.Division of Trauma, Critical Care, Emergency Surgery, and Burns, Department of Surgery, College of Medicine, University of Arizona, Tucson, Arizona.Division of Trauma, Critical Care, Emergency Surgery, and Burns, Department of Surgery, College of Medicine, University of Arizona, Tucson, Arizona.Division of Trauma, Critical Care, Emergency Surgery, and Burns, Department of Surgery, College of Medicine, University of Arizona, Tucson, Arizona.Division of Trauma, Critical Care, Emergency Surgery, and Burns, Department of Surgery, College of Medicine, University of Arizona, Tucson, Arizona.Division of Trauma, Critical Care, Emergency Surgery, and Burns, Department of Surgery, College of Medicine, University of Arizona, Tucson, Arizona. Electronic address: bjoseph@surgery.arizona.edu.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

30691787

Citation

Hamidi, Mohammad, et al. "Can Sarcopenia Quantified By Computed Tomography Scan Predict Adverse Outcomes in Emergency General Surgery?" The Journal of Surgical Research, vol. 235, 2019, pp. 141-147.
Hamidi M, Ho C, Zeeshan M, et al. Can Sarcopenia Quantified by Computed Tomography Scan Predict Adverse Outcomes in Emergency General Surgery? J Surg Res. 2019;235:141-147.
Hamidi, M., Ho, C., Zeeshan, M., O'Keeffe, T., Hamza, A., Kulvatunyou, N., Jehan, F., & Joseph, B. (2019). Can Sarcopenia Quantified by Computed Tomography Scan Predict Adverse Outcomes in Emergency General Surgery? The Journal of Surgical Research, 235, 141-147. https://doi.org/10.1016/j.jss.2018.09.027
Hamidi M, et al. Can Sarcopenia Quantified By Computed Tomography Scan Predict Adverse Outcomes in Emergency General Surgery. J Surg Res. 2019;235:141-147. PubMed PMID: 30691787.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Can Sarcopenia Quantified by Computed Tomography Scan Predict Adverse Outcomes in Emergency General Surgery? AU - Hamidi,Mohammad, AU - Ho,Cathy, AU - Zeeshan,Muhammad, AU - O'Keeffe,Terence, AU - Hamza,Ali, AU - Kulvatunyou,Narong, AU - Jehan,Faisal, AU - Joseph,Bellal, Y1 - 2018/10/26/ PY - 2018/06/01/received PY - 2018/07/30/revised PY - 2018/09/11/accepted PY - 2019/1/30/entrez PY - 2019/1/30/pubmed PY - 2019/11/19/medline KW - CT scan KW - Complications KW - EGS KW - Sarcopenia SP - 141 EP - 147 JF - The Journal of surgical research JO - J Surg Res VL - 235 N2 - BACKGROUND: Sarcopenia (a decline of skeletal muscle mass) has been identified as a predictor of poor postoperative outcomes. The impact of sarcopenia in emergency general surgery (EGS) remains undetermined. The aim of this study was to evaluate the association between sarcopenia and outcomes after EGS. METHODS: A 3-y (2012-15) review of all EGS patients aged ≥45 y was presented to our institution. Patients who underwent computer tomography-abdomen were included. Sarcopenia was defined as the lowest sex-specific quartile of total psoas index (computer tomography-measured psoas area normalized for body surface area). Patients were divided into sarcopenic (SA) and nonsarcopenic. Primary outcome measures were in-hospital complications, hospital-length of stay [h-LOS], intensive care unit-length of stay, adverse discharge disposition, and in-hospital mortality. Our secondary outcome measures were 30-d complications, readmissions, and mortality. RESULTS: Four hundred fifty-two patients undergoing EGS were included. Mean age was 58 ± 8.7 y, and 60% were males. Hundred thirteen patients were categorized as SA. Compared to nonsarcopenic, SA patients had higher rates of minor complications (28% versus 17%, P = 0.01), longer hospital-length of stay (7d versus 5d, P = 0.02), and were more likely to be discharged to skilled nursing facility/Rehab (35% versus 17%, P = 0.01). There was no difference between the two groups regarding major complications, intensive care unit-length of stay, mortality, and 30-d outcomes. On regression analysis, sarcopenia was an independent predictor of minor complications (OR 1.8 [1.6-3.7]) and discharge to rehab/SNIF (OR: 1.9 [1.5-3.2]). However, there was no association with major complications, mortality, 30-d complications, readmissions, and mortality. CONCLUSIONS: Sarcopenia is an independent predictor of minor postoperative complications, prolonged hospital-length of stay, and an adverse discharge disposition in patients undergoing EGS. Identifying SA EGS patients will improve both resource allocation and discussion about the patient's prognosis between physicians, patients, and their families. SN - 1095-8673 UR - https://www.unboundmedicine.com/medline/citation/30691787/Can_Sarcopenia_Quantified_by_Computed_Tomography_Scan_Predict_Adverse_Outcomes_in_Emergency_General_Surgery L2 - https://linkinghub.elsevier.com/retrieve/pii/S0022-4804(18)30650-4 DB - PRIME DP - Unbound Medicine ER -