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An Alternative Scoring System to Predict Risk for Surgical Site Infection Complicating Coronary Artery Bypass Graft Surgery

Published online by Cambridge University Press:  02 January 2015

N. Deborah Friedman ,
Ann L. Bull ,
Philip L. Russo ,
Karin Leder ,
Christopher Reid ,
Baki Billah ,
Silvana Marasco ,
Emma McBryde  and
Michael J. Richards
N. Deborah Friedman*
Affiliation:
Victorian Hospital Acquired Infection Surveillance System, Melbourne, Victoria, Australia
Ann L. Bull
Affiliation:
Victorian Hospital Acquired Infection Surveillance System, Melbourne, Victoria, Australia
Philip L. Russo
Affiliation:
Victorian Hospital Acquired Infection Surveillance System, Melbourne, Victoria, Australia
Karin Leder
Affiliation:
Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
Christopher Reid
Affiliation:
Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
Baki Billah
Affiliation:
Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
Silvana Marasco
Affiliation:
Alfred Hospital, Melbourne, Victoria, Australia
Emma McBryde
Affiliation:
Victorian Hospital Acquired Infection Surveillance System, Melbourne, Victoria, Australia
Michael J. Richards
Affiliation:
Victorian Hospital Acquired Infection Surveillance System, Melbourne, Victoria, Australia
*
VICNISS Coordinating Centre, 10 Wreckyn St., North Melbourne, Vic 3605, Australia ([email protected])
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Abstract

Objective.

To analyze the risk factors for surgical site infection (SSI) complicating coronary artery bypass graft (CABG) surgery and to create an alternative SSI risk score based on the results of multivariate analysis.

Methods.

A prospective cohort study involving inpatient and laboratory-based surveillance of patients who underwent CABG surgery over a 27-month period from January 1, 2003 through March 31, 2005. Data were obtained from 6 acute care hospitals in Victoria, Australia, that contributed surveillance data for SSI complicating CABG surgery to the Victorian Hospital Acquired Infection Surveillance System Coordinating Centre and the Australasian Society of Cardiac and Thoracic Surgeons, also in Victoria.

Results.

A total of 4,633 (93%) of the 4,987 patients who underwent CABG surgery during this period were matched in the 2 systems databases. There were 286 SSIs and 62 deep or organ space sternal SSIs (deep or organ space sternal SSI rate, 1.33%). Univariate analysis revealed that diabetes mellitus, body mass index (BMI) greater than 35, and receipt of blood transfusion were risk factors for all types of SSI complicating CABG surgery. Six multivariate analysis models were created to examine either preoperative factors alone or preoperative factors combined with operative factors. All models revealed diabetes and BMI of 30 or greater as risk factors for SSI complicating CABG surgery. A new preoperative scoring system was devised to predict sternal SSI, which assigned 1 point for diabetes, 1 point for BMI of 30 or greater but less than 35, and 2 points for BMI of 35 or greater. Each point in the scoring system represented approximately a doubling of risk of SSI. The new scoring system performed better than the National Nosocomial Infections Surveillance System (NNIS) risk index at predicting SSI.

Conclusion.

A new weighted scoring system based on preoperative risk factors was created to predict sternal SSI risk following CABG surgery. The new scoring system outperformed the NNIS risk index. Future studies are needed to validate this scoring system.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 28 , Issue 10 , October 2007 , pp. 1162 - 1168
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2007 

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References

1. Rumsfeld, JS, Magid, D, O'Brien, MM, et al. Changes in health-related quality of life following coronary artery bypass graft surgery. Ann Thorac Surg 2001;72:2026–2032.Google Scholar
2. Lu, JC, Grayson, AD, Jha, P, Srinivasan, AK, Fabri, BM. Risk factors for sternal wound infection and mid-term survival following coronary artery bypass surgery. Eur J Cardiothorac Surg 2003;23:943–949.Google Scholar
3. Loop, FD, Lytle, BW, Cosgrove, DM, et al. Sternal wound complications after isolated coronary artery bypass grafting: early and late mortality, morbidity, and cost of care. Ann Thorac Surg 1990;49:179–186.Google Scholar
4. Martorell, C, Engelman, R, Corl, A, Brown, RB. Surgical site infections in cardiac surgery: an 11-year perspective. Am J Infect Control 2004;32:63–68.Google Scholar
5. Shroyer, AL, Coombs, LP, Peterson, ED, et al. The Society of Thoracic Surgeons: 30-day operative mortality and morbidity risk models. Ann Thorac Surg 2003;75:1856–1865.Google Scholar
6. Trick, WE, Scheckler, WE, Tokars, JI, et al. Modifiable risk factors associated with deep sternal site infection after coronary artery bypass grafting. J Thorac Cardiovasc Surg 2000;119:108–114.Google Scholar
7. Fowler, VG Jr, O'Brien, SM, Muhlbaier, LH, Corey, GR, Ferguson, TB, Peterson, ED. Clinical predictors of major infections after cardiac surgery. Circulation 2005;112(suppl I):I358–I365.Google Scholar
8. Eklund, AM, Lyytikainen, O, Klemets, P, et al. Mediastinitis after more than 10,000 cardiac surgical procedures. Ann Thorac Surg 2006;82:1784–1789.Google Scholar
9. Harrington, G, Russo, P, Spelman, D, et al. Surgical-site infection rates and risk factor analysis in coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2004;25:472–476.Google Scholar
10. Lucet, JC. Surgical site infection after cardiac surgery: a simplified surveillance method. Infect Control Hosp Epidemiol 2006;27:1393–1396.Google Scholar
11. Russo, PL, Spelman, DW. A new surgical-site infection risk index using risk factors identified by multivariate analysis for patients undergoing coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2002;23:372–376.Google Scholar
12. New classification of physical status. Anesthesiology 1963;24:111.Google Scholar
13. Gaynes, R, Richards, C, Edwards, J, et al.;the National Nosocomial Infections Surveillance (NNIS) System Hospitals. Feeding back surveillance data to prevent hospital-acquired infections. Emerg Infect Dis 2001;7:295–298.Google Scholar
14. Culver, DH, Horan, TC, Gaynes, RP, et al. Surgical wound infection rates by wound class, operative procedure, and patient risk index. National Nosocomial Surveillance System. Am J Med 1991;91(suppl3B):152S–157S.Google Scholar
15. Batista, R, Kaye, KS, Yokoe, DS. Admission-specific chronic disease scores as alternative predictors of surgical site infection for patients undergoing coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2006;27:802–808.Google Scholar
16. Roy, MC, Herwaldt, LA, Embrey, R, Kuhns, K, Wenzel, RP, Perl, TM. Does the Centers for Disease Control's NNIS system risk index stratify patients undergoing cardiothoracic operations by their risk of surgical-site infection? Infect Control Hosp Epidemiol 2000;21:186–190.Google Scholar
17. Gaynes, RP. Surgical-site infections and the NNIS risk index: room for improvement. Infect Control Hosp Epidemiol 2000;21:184–185.Google Scholar
18. Brandt, C, Hansen, S, Sohr, D, Daschner, F, Ruden, H, Gastmeier, P. Finding a method for optimizing risk adjustment when comparing surgical-site infection rates. Infect Control Hosp Epidemiol 2004;25:313–318.Google Scholar
19. Paul, M, Raz, A, Leibovici, L, Madar, H, Holinger, R, Rubinovitch, B. Sternal wound infection after coronary artery bypass graft surgery: validation of existing risk scores. J Thorac Cardiovasc Surg 2007;133:397–403.Google Scholar
20. Kohli, M, Yuan, L, Escobar, M, et al. A risk index for sternal surgical wound infection after cardiovascular surgery. Infect Control Hosp Epidemiol 2003;24:17–25.Google Scholar
21. Russo, P L, Bennett, N, Boardman, C, et al. The establishment of a statewide surveillance program for hospital-acquired infections in large Victorian public hospitals: a report from the VICNISS Coordinating Centre. Am J Infect Control 2006;34:430–436.Google Scholar
22. Garner, JS, Jarvis, WR, Emori, TG, Horan, TC, Hughes, JM. CDC definitions for nosocomial infections, 1988. Am J Infect Control 1988;16:128–140.Google Scholar
23. Horan, TC, Emori, TG. Definitions of key terms used in the NNIS System. Am J Infect Control 1997;25:112–116.Google Scholar
24. Hook, EB, Regal, RR. Capture-recapture methods in epidemiology: methods and limitations. Epidemiol Rev 1995;17:243–263.Google Scholar
25. Peduzzi, P, Concato, J, Kemper, E, Holford, TR, Feinstein, AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 1996;49:1373–1379.Google Scholar
26. Zacharias, A, Habib, RH. Factors predisposing to median sternotomy complications: deep vs. superficial infection. Chest 1996;110:1173–1178.Google Scholar
27. Crabtree, TD, Codd, JE, Fraser, VJ, Bailey, MS, Olsen, MA, Damiano, RJ Jr. Multivariate analysis of risk factors for deep and superficial sternal infection after coronary artery bypass grafting at a tertiary care medical center. Semin Thorac Cardiovasc Surg 2004;16:53–56.Google Scholar
28. Olsen, MA, Lock-Buckley, P, Hopkins, D, Polish, LB, Sundt, TM, Fraser, VJ. The risk factors for deep and superficial chest surgical-site infections after coronary artery bypass graft surgery are different. J Thorac Cardiovasc Surg 2002;124:136–145.Google Scholar
29. Friedman, ND, Russo, PL, Bull, AL, Richards, MJ, Kelly, H. Validation of coronary artery bypass graft surgical site infection surveillance data from a state-wide surveillance system in Australia. Infect Control Hosp Epidemiol 2007;28:812–817.Google Scholar
30. Furnary, AP, Wu, Y, Bookin, SO. Effect of hyperglycemia and continuous intravenous insulin infusions on outcomes of cardiac surgical procedures: the Portland Diabetic Project. Endocrine Practice 2004;10(suppl 2):21–33.Google Scholar
31. Kurki, TS, Jarvinen, O, Kataja, MJ, Laurikka, J, Tarkka, M. Performance of three preoperative risk indices;CABDEAL, EuroSCORE and Cleveland models in a prospective coronary bypass database. Eur J Cardiothorac Surg 2002;21:406–410.Google Scholar
32. Higgins, TL. Quantifying risk and assessing outcome in cardiac surgery. J Cardiothorac Vase Anesth 1998;12:330–340.Google Scholar
33. Hannan, EL, Kiburn, H, O'Donnell, J, et al. Adult open heart surgery in New York State: an analysis of risk factors and hospital mortality rates. JAMA 1990;264:2768–2774.Google Scholar
34. Parsonnet, V, Dean, D, Bernstein, AD. A method of uniform stratification of risk for evaluating the results of surgery in acquired adult heart disease. Circulation 1989;79(suppl 1):I3–12.Google Scholar
35. O'Connor, GT, Plume, SK, Olmstead, EM, et al. Multivariate prediction of in-hospital mortality associated with coronary artery bypass graft surgery. Circulation 1992;85:2110–2118.Google Scholar
36. Yap, CH, Reid, C, Yii, M, et al. Validation of the EuroSCORE model in Australia. Eur J Cardiothorac Surg 2006;29:441–446.Google Scholar
37. Geubbels, ELPE, Grobbee, DE, Vandenbroucke-Grauls, CMJE, Wille, JC, de Boer, AS. Improved risk adjustment for comparison of surgical site infection rates. Infect Control Hosp Epidemiol 2006;27:1330–1339.Google Scholar
38. Higgins, TL, Estafanous, FG, Loop, FD, Beck, GJ, Blum, JM, Paranandi, L. Stratification of morbidity and mortality outcome by preoperative risk factors in coronary artery bypass patients: a clinical severity score. JAMA 1992;267:2344–2348.Google Scholar
39. Lasko, TA, Bhagwat, JG, Zou, KH, Ohno-Machado, L. The use of the receiver operating characteristic curves in biomedical informatics. J Biomed Inform 2005;38:404–415.Google Scholar