Patients with diabetes were at a significantly higher risk of developing SSI (P = 0.028). Of note, surgeries that resulted in an SSI and were performed on patients with diabetes were always of closed fracture type involving the lower extremities. The unadjusted OR of SSI among patients with diabetes was 2.85 (95% CI, 1.08–7.54; P = 0.035); when adjusted for age, the odds for developing SSI remained relatively high but was not statistically significant (OR [95% CI], 2.76 [0.99–7.69]; P = 0.052). Those with lower extremity injuries were at a significantly higher risk of developing SSI, (P = 0.0038) (Figure 4). The presence of SSI was significantly associated with a positive bone/tissue culture (P < 0.0001). Among those with SSI, rates of elevated C-reactive protein level, erythrocyte sedimentation rate, and white blood cell count were 15%, 56%, and 48%, respectively.
Patients in need of bone graft—ie, fractures with marked comminution, segmental bone loss, or nonunion following closed fracture treatment—had a higher incidence of SSI; this difference, however, was not statistically significant (P = 0.085). Similarly, patients who were uninsured or had Medicaid/Medicare had a much higher rate of SSI compared with privately insured patients (8.6% and 9.4% vs. 2.8%, respectively); however, this was not statistically significant (P = 0.055). When private patients were exclusively compared with Medicaid/Medicare and uninsured patients, there was a significantly lower rate of SSI seen in the private group (2.8% vs. 9.0%; P = 0.021). Polytrauma patients, including those with spine, intracranial, intra-abdominal, urological, and intrathoracic injuries, did not have a significantly higher incidence of SSI. The sample studied had 37/400 (9.3%) polytrauma patients, and of those, only 1/27 (3.7%) developed an orthopaedic procedure-related SSI.
Among patients who met the selection criteria (400 of 956), the median number of index surgeries performed on a daily basis was two (range, 1–9). The average daily rate of SSI among index procedures was 0.18, with most SSIs occurring on days when multiple procedures were performed.
The SWC was designed as a component of the NNIS risk index to risk-stratify wounds based on a crude assessment of the degree of contamination. It is used along with the procedure duration and ASA score and could provide prognostic information on likelihood for SSI. However, the current data did not show an association (ie, direct relationship) of subsequent SSI and SWC grades (I–IV). This finding is in accordance with the poor concordance already seen in the general surgery literature evaluating the utility of the SWC. Ortega et al7 showed significantly lower rates of SSIs in the contaminated and dirty groups (classes III and IV, respectively) compared with the historically reported rates. A recent multicenter study of 11 participating institutions reviewed 2,034 cases and showed a classification discordance of 44% across the participating institutions.8
The implementation of the SWC was part of a national effort to reduce SSI rates and to standardize reporting of these complications for quality improvement across institutions. Although the SWC is one of the three parameters, ASA and procedure duration being the other two, in the proposed risk model, it is the least objective and the one with wide interobserver variability. Moreover, if found efficacious with some modifications provided by the results seen in this study (insurance status, lower extremity injuries, and history of diabetes mellitus), it has the potential to influence treatment strategies and perioperative protocols, inform surveillance protocols, and manage expectations—ultimately improving patient outcomes.
We suggest that the initiative for quality improvement, SSI risk surveillance, and promoting standardized institutional reporting of such events is important. The current study provides some objective insights that may be useful for future modifications of the current SWC and how it may apply to the orthopaedic patient. Some strengths of the current study are as follows: a retrospective design reviewing a single center and use of case logs of a single surgeon, which enabled consistent reporting of the SWC, thus avoiding the interobserver variability seen in previous SWC studies.9 Despite previously published results on the SWC, there are still hospital systems remaining that rely on the aforementioned risk model to risk-stratify patients and may imply prognostic utility for subsequent SSIs, perhaps not its original intended use. Consequently, newer and more robust SSI risk models are being developed, that is, the NHSN procedure-specific risk index models.8,10 These newer models are yet to be adopted widely among hospital systems and may improve nationwide reporting, standardize the analysis of SSI and at-risk patients, improve infection control initiatives, and promote the development of novel strategies to reduce SSI risk.
The patients evaluated in the study belonged exclusively to the adult population (age, ≥18 years) and largely included patients with orthopaedic trauma injuries. This represents a different demographic from the pediatric and general surgery literature studied by Levy et al.9 The results of this study can be particularly relevant to the general orthopaedic surgeon, orthopaedic traumatologist, hospital systems, and third-party payers, including Medicare/Medicaid, who value the SWC as part of their quality improvement initiative. The current study includes a wide spectrum of orthopaedic procedures involving all four extremities (long bones, shoulders, knees, ankles, and wrists) and the pelvis.
A possible explanation as to why the current results did not show an association (direct or indirect) between the SSI rate/incidence and SWC grade might be due to current operating room standards, surgical techniques, perioperative wound protocols, improved efficacy of antibiotics, and active surveillance of high-risk patients (ie, open injuries). However, the variables that demonstrated significance or were positive prognostic indicators for postoperative SSI, diabetes mellitus, lower extremity injury, and payer-source may strengthen future models.
Historically, diabetes mellitus is known to be associated with a higher risk of SSI and was found to be a significant risk factor for SSI in the current study. A univariate analysis following spine procedures by Olsen et al14 demonstrated that serum glucose levels preoperatively and within 5 days following surgery were significantly higher in patients in whom SSI developed than in uninfected patients. Specifically, patients with a preoperative serum glucose >125 mg/dL or a postoperative serum glucose of >200 mg/dL had an OR of 3.4 for developing a subsequent SSI.14 This is consistent with our finding of an OR of 2.85 for patients with diabetes. Similarly, a study looking at postoperative infection rates in foot and ankle surgery among patients with and without diabetes showed that the presence of “complicated” diabetes increases the risk of postoperative infection by 10 and 6-fold compared with uncomplicated diabetes.15
The Lower Extremity Assessment Project (LEAP) study, a large prospective series evaluating lower extremity injuries, demonstrated that patients with lower extremity trauma are confronted with higher rates of wound infections and osteomyelitis compared with the pelvic/sacrum or upper extremities.16 Our data endorse this trend as lower extremity injuries accounted for a significantly larger proportion of resultant SSIs: 10.2% infection rate among lower extremity surgical procedures, and 1.9% among upper extremity procedures. Among all SSI cases, 74.1% were from the lower extremity.
Another interesting finding was that the payer-source proved to be a significant prognostic factor for SSIs when Medicaid/Medicare and uninsured patients were compared with privately insured patients (9.0% vs. 2.8%; P = 0.021). In addition, our findings are consistent with those from a separate study looking at patients who had undergone primary hip or knee arthroplasty: variables compared were complications, costs, and length of hospital stay for patients with Medicaid versus patients with non-Medicaid insurance.17 The patients with Medicaid were found to have a higher prevalence of postoperative SSI than those with non-Medicaid insurance (OR = 1.7; 95% CI = 1.3–2.1).17 Reasons for this are likely multifactorial and may necessitate further investigation to better understand any differences that predispose or protect against SSI.
Limitations to this study include a relatively small sample size (400 cases) eligible for further analyses. A larger sample size might have been possible with a multicenter approach, but such a study design did not allow for control of potential interobserver variability, which has been described by previous reports. All wounds were appraised by a single trauma/general orthopaedic surgeon and a circulating nurse, and a consensus was reached 100% of the time.
Another limitation is that the study cohort does contain polytrauma patients with both orthopaedic and nonorthopaedic injuries. In these patients, confounding variables such as systemic inflammatory response syndrome, septicemia, and secondary procedures performed by other surgical services can influence the risk of SSI. Other variables not controlled for are as follows: type of implants used and miscellaneous host-dependent variables—postoperative patient compliance, wound surveillance, and acute rehab versus home care. Similarly, these variables may influence one's risk of SSI.18
Unlike the Gustilo and Anderson wound classification system, in which open fractures are classified and further subdivided (type I, type II, types IIIA, IIIB, and IIIC) with respect to the severity of soft tissue injury, the SWC fails to account for such intrinsic risk factors associated with SSI, that is, poor soft-tissue coverage, need for soft-tissue flap, or vascular repair. In addition, the former classification shows a positive correlation with postoperative wound complications (wound infection, osteomyelitis, and amputation) and a higher classification grade.19
In conclusion, the CDC SWC system did not show an association with the rate of SSI. As used by some facilities, it was not an effective prognostic indicator for SSIs in the orthopaedic patient. Certain variables were found to be positive prognostic indicators for future SSI and may be worthy of inclusion in future risk-stratifying models. These variables include but are not limited to diabetes mellitus and lower extremity injuries.
References printed in bold type are those published within the past 5 years.
1. Lee J, Singletary R, Schmader K, Anderson DJ, Bolognesi M, Kaye KS: Surgical site infection in the elderly following orthopaedic surgery. Risk factors and outcomes. J Bone Joint Surg Am 2006;88:1705–1712.
2. Whitehouse JD, Friedman ND, Kirkland KB, Richardson WJ, Sexton DJ: The impact of surgical-site infections following orthopedic surgery at a community hospital and a university hospital: Adverse quality of life, excess length of stay, and extra cost. Infect Control Hosp Epidemiol 2002;23:183–189.
3. Thakore RV, Greenberg SE, Shi H, et al: Surgical site infection in orthopedic trauma: A case-control study evaluating risk factors and costs. J Clin Orthop Trauma 2015;6:220–226.
4. Graf K, Ott E, Vonberg RP, et al: Surgical site infections—economic consequences for the health care system. Langerbecks Arch Surg 2011;396:453–459.
5. Greene LR: Guide to the elimination of orthopedic surgery surgical site infections: An executive summary of the Association for Professionals in Infection Control and Epidemiology elimination guide. Am J Infect Control 2012;40:384–386.
7. Ortega G, Rhee DS, Papandria DJ, et al: An evaluation of surgical site infections by wound classification system using the ACS-NSQIP. J Surg Res 2012;174:33–38.
9. Levy SM, Lally KP, Blakely ML, et al: Surgical wound misclassification: A multicenter evaluation. J Am Coll Surg 2015;220:323–329.
10. Mu L, Edwards J, Horan T, Berrios-Torres S, Fridkin S: Improving risk- adjusted measures of surgical site infection for the National Healthcare Safety Network. Infect Control Hosp Epidemiol 2011;32:970–986.
11. Garner JS: CDC guideline for prevention of surgical wound infections, 1985. Supersedes guideline for prevention of surgical wound infections published in 1982. (Originally published in November 1985). Revised. Infect Control 1986;7:193–200.
12. Simmons BP: Guideline for prevention of surgical wound infections. Infect Control 1982;3:185–196.
13. Chapman MW: Role of bone stability in open fractures. Instr Course Lect 1982;31:75–87.
14. Olsen MA, Nepple JJ, Riew D, et al: Risk factors for surgical site infection following orthopaedic spinal operations. J Bone Joint Surg Am 2008;90:62–69.
15. Wukich DK, Lowery NJ, McMillen RL, Frykberg RB: Postoperative infection rates in foot and ankle surgery: A comparison of patients with and without diabetes mellitus. J Bone Joint Surg Am 2010;92:287–295.
16. Harris AM, Althausen PL, Kellam J, Bosse MJ, Castillo R; Lower Extremity Assessment Project (LEAP) Study Group: Complications following limb-threatening lower extremity trauma. J Orthop Trauma 2009;23:1–6.
17. Browne J, Novicoff W, D'Apuzzo M: Medicaid payer status is associated with in-hospital morbidity and resource utilization following primary total joint arthroplasty. J Bone Joint Surg Am 2014;96:e180.
18. Bowen TR, Widmaier JC: Host classification predicts infection after open fracture. Clin Orthop Relat Res 2005;433:205–211.
Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Orthopaedic Surgeons
19. Gustilo RB, Mendoza RM, Williams DN: Problems in the management of type III (severe) open fractures: A new classification of type III open fractures. J Trauma 1984;24:742–746.