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Shock/Sepsis/Trauma/Critical Care| Volume 209, P60-69, March 2017

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Postoperative sepsis prediction in patients undergoing major cancer surgery

  • Author Footnotes
    1 The authors contributed equally to this work.
    Akshay Sood
    Correspondence
    Corresponding author. VCORE—Vattikuti Urology Institute, Henry Ford Hospital, 2799 W. Grand Boulevard, Detroit, MI 48202. Tel.: +1 443 691 3193; fax: +1 313 916 4352.
    Footnotes
    1 The authors contributed equally to this work.
    Affiliations
    Center for Outcomes Research, Analytics and Evaluation, Vattikuti Urology Institute, Henry Ford Health System, Detroit, Michigan

    Division of Urologic Surgery and Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts

    Department of Surgery, Henry Ford Health System, Detroit, Michigan
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  • Author Footnotes
    1 The authors contributed equally to this work.
    Firas Abdollah
    Footnotes
    1 The authors contributed equally to this work.
    Affiliations
    Center for Outcomes Research, Analytics and Evaluation, Vattikuti Urology Institute, Henry Ford Health System, Detroit, Michigan
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  • Jesse D. Sammon
    Affiliations
    Center for Outcomes Research, Analytics and Evaluation, Vattikuti Urology Institute, Henry Ford Health System, Detroit, Michigan

    Division of Urologic Surgery and Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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  • Nivedita Arora
    Affiliations
    Department of Surgery, University of Minnesota, Minneapolis, Minnesota
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  • Matthew Weeks
    Affiliations
    Center for Outcomes Research, Analytics and Evaluation, Vattikuti Urology Institute, Henry Ford Health System, Detroit, Michigan
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  • James O. Peabody
    Affiliations
    Center for Outcomes Research, Analytics and Evaluation, Vattikuti Urology Institute, Henry Ford Health System, Detroit, Michigan
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  • Mani Menon
    Affiliations
    Center for Outcomes Research, Analytics and Evaluation, Vattikuti Urology Institute, Henry Ford Health System, Detroit, Michigan
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  • Quoc-Dien Trinh
    Affiliations
    Division of Urologic Surgery and Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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  • Author Footnotes
    1 The authors contributed equally to this work.
Published:October 06, 2016DOI:https://doi.org/10.1016/j.jss.2016.09.059

      Abstract

      Background

      Cancer patients are at increased risk for postoperative sepsis. However, studies addressing the issue are lacking. We sought to identify preoperative and intraoperative predictors of 30-d sepsis after major cancer surgery (MCS) and derive a postoperative sepsis risk stratification tool.

      Methods

      Patients undergoing one of nine MCSs (gastrointestinal, urological, gynecologic, or pulmonary) were identified within the American College of Surgeons National Surgical Quality Improvement Program (2005-2011, n = 69,169). Multivariable adjusted analyses (MVA) were performed to identify the predictors of postoperative sepsis. A composite sepsis risk score (CSRS) was constructed using the regression coefficients of predictors significant on MVA. The score was stratified into low, intermediate, and high risk, and its predictive accuracy for sepsis, septic shock, and mortality was assessed using the area under the curve analysis.

      Results

      Overall, 4.3% (n = 2954) of patients developed postoperative sepsis. In MVA, Black race (odds ratio [OR] = 1.30, P = 0.002), preoperative hematocrit <30 (OR = 1.40, P = 0.022), cardiopulmonary and cerebrovascular comorbidities (P < 0.010), American Society of Anesthesiologists score >3 (P < 0.05), operative time (OR = 1.002, P < 0.001), surgical approach (OR = 1.81, P < 0.001), and procedure type (P < 0.001) were significant predictors of postoperative sepsis. CSRS demonstrated favorable accuracy in predicting postoperative sepsis, septic shock, and mortality (area under the curve 0.72, 0.75, and 0.74, respectively). Furthermore, CSRS risk stratification demonstrated high concordance with sepsis rates, 1.3% in low-risk patients versus 9.7% in high-risk patients. Similarly, 30-d mortality rate varied from 0.5% to 5.5% (10-fold difference) in low-risk patients versus high-risk patients.

      Conclusions

      Our study identifies the major risk factors for 30-d sepsis after MCS. These risk factors have been converted into a simple, accurate bedside sepsis risk score. This tool might facilitate improved patient–physician interaction regarding the risk of postoperative sepsis and septic shock.

      Keywords

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