Risk Factors for Spinal Surgical Site Infection, Houston, Texas

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1 infection control and hospital epidemiology september 2009, vol. 30, no. 9 original article Risk Factors for Spinal Surgical Site Infection, Houston, Texas Kelley M. Boston, MPH; Sarah Baraniuk, PhD; Shana O Heron, MPH; Kristy O. Murray, DVM, PhD objective. Because of an increase in the rate of surgical site infections (SSIs) following spinal procedures at the study hospital, we conducted a study to determine risk factors associated with the development of a SSI. design. Case-control study. setting. A community hospital in Houston, Texas, with more than 500 beds. patients. Fifty-five case patients who developed SSI after spinal surgery and 179 control patients who did not develop SSI after spinal surgery. methods. We examined patient- and hospital-associated risk factors for SSI by using existing data on patients who underwent spinal operations at the study hospital between December 2003 and August Multivariable analysis was conducted using logistic regression to determine significant risk factors associated with SSI. results. The presence of comorbidities (odds ratio [OR], 3.15 [95% confidence interval (CI), ]) and surgical duration greater than the population median of 100 minutes (OR, 2.48 [95% CI, ]) were identified as independent risk factors for SSI. The use of only povidone-iodine for preoperative skin antisepsis was found to be protective (OR, 0.16 [95% CI, ]). Specific operating room, hospital staff involved in the procedures, workers compensation status, method of hair removal, smoking status, or incontinence were not statistically significant. conclusions. The presence of comorbidities and increased surgical duration are risks for postoperative infection. The use of only povidone-iodine was found to decrease the risk of infection. Infect Control Hosp Epidemiol 2009; 30: Surgical site infections (SSIs) are the second most common type of hospital-acquired infections in the United States. 1 The Centers for Disease Control and Prevention (CDC) estimate that 2.7% of surgical patients will develop SSIs. 2 A 1995 study on deep infections in surgical patients revealed that spinal surgeries had the second highest rate of infection, with 4.68% of patients developing SSI. 3 Patients who develop infection following surgery have higher morbidity and mortality than those who do not develop infection. In addition, SSI frequently prolongs hospital stay and can increase the economic costs of hospitalization and medical care. 4,5 With 27 million surgeries performed each year in the United States, the question of prevention and control of nosocomially acquired SSI is a major focus of hospital infection control. 6 In January 2004, a community hospital in Houston, Texas, with more than 500 beds expanded its spine specialty unit and increased the number of orthopedic surgeries. In response, the infection control department began increased surveillance for SSI after spinal procedures. The rate of postsurgical infection after spinal procedures was significantly higher at the study hospital than national averages. Three risk-stratified analyses of the SSI incidence rates for spinal surgeries at the study hospital were conducted between January and November 2004 by using standard National Nosocomial Infections Surveillance (NNIS) system methods for data collection and risk stratification. 7 Patients were assigned a risk code on the basis of 3 variables: wound classification as defined by the physician, surgical duration, and American Society of Anesthesiologists (ASA) score. For all 3 variables, patients in the lowest risk categories had rates of infection significantly higher than rates reported by hospitals involved in the NNIS system survey. The study hospital did not see similar patterns of increased infection after other types of surgeries. A case-control study was designed to investigate further the risk factors associated with a SSI following spinal surgery. The main objectives of this study were to determine risk factors for spinal SSI in the study hospital and to determine whether any individual hospital personnel were associated with development of SSI in the patients. This study also examined patient From the University of Texas Health Science Center at Houston, School of Public Health (all authors), and Infection Prevention and Management Associates (K.M.B., S.O.), Houston, Texas. Received October 8, 2007; accepted April 26, 2009; electronically published July 30, by The Society for Healthcare Epidemiology of America. All rights reserved X/2009/ $ DOI: /605323

2 risk factors for ssis 885 characteristics that could increase the risk of infection and perioperative risk factors for infection that could be targets for hospital interventions. The results found in this study could benefit other hospitals undergoing evaluation of their hospital infection control policies and procedures. methods Definition and Identification of Case and Control Patients Case patients were defined as patients who underwent spinal surgery at the hospital between December 15, 2003, and August 15, 2005, and who developed an infection that met the criteria for infection classification. 8 Spinal surgical procedures included fusions, laminectomies, and other non NNIS system procedures. Case patients were identified during the course of infection surveillance by the hospital s infection control department. All wound sample cultures in the hospital s laboratory that were positive for a pathogen were reviewed by the infection control staff to determine whether the wound and culture met the criteria established by the CDC 9 for a SSI. Case patients included all patients with confirmed superficial incisional or deep incisional SSI. There were no organ space SSIs in the case patient group during the study period. Stitch abscesses and localized stab wounds were not included as infections, as they do not meet the CDC criteria for SSI. The infection control staff also reviewed the records of all surgical patients who were readmitted to the hospital or who returned to surgery; their purpose was to determine whether the readmission or return to surgery was the result of a SSI. In addition, the infection control staff of the hospital performed targeted surveillance for SSIs. Letters were sent out to all surgeons who performed spinal procedures within the study time frame. 10 These letters contained the definitions of a SSI and a list of that surgeon s surgical patients; this aided the infection control department in identifying case patients who may have met the SSI definition but who were not readmitted to the study hospital. If a patient had signs of infection at the time of the original surgery or if the original surgery was performed at a different hospital, that patient was excluded from the case group. Control patients were defined as patients who underwent spinal surgical procedures between December 15, 2003, and August 15, 2005, at the study hospital and did not develop a SSI. Data Collection Data for this study were collected by the infection control department at the study hospital as a part of ongoing wound surveillance and in the course of 3 spinal SSI rate reviews performed as a part of targeted surgical services surveillance. The infection control department at the study hospital uses standardized data abstraction tools for general data collection on nosocomial infections, including the CDC criteria 9 used to define infection and risk factors for SSI. This served as the source of the data used for analysis in this case-control study. The study hospital provided a coded list of patients who underwent orthopedic surgery at the study hospital between December 15, 2003, and August 15, The database used for analysis did not contain any identifying personal information. Patient records missing more than 50% of variables were excluded from the data set. Eleven (4%) of the 245 received patient records were missing more than half of the variables and were eliminated from the data set, including those of 4 of the 59 case patients (7%) and 7 of the 186 control patients (4%). Data from a total of 234 patients were included in the final analysis, representing 55 case patients and 179 control patients. Human Subject Considerations There was no direct contact with patients. All data were collected retrospectively by infection control staff at the study hospital as part of their wound surveillance program, and records containing personal identifiers were kept in locked files at the study hospital. The final database created for the purposes of this study had all personal identifiers for each patient removed and the identities of all hospital staff involved in the procedures replaced with a unique identification number; no protected health information was disclosed outside the study hospital. Since this study involved a secondary analysis of a preexisting deidentified data set, the study was approved with exempt status by the University of Texas Health Science Center at Houston Committee for the Protection of Human Subjects. Study Variables and Statistical Analysis To determine patient-associated risk factors for SSI, the following variables were included in the analysis: patient demographic characteristics (age and sex), workers compensation status, obesity (body mass index of x30), postoperative fasting blood glucose level (measured within 24 hours on the first morning following surgery), serum albumin level (as a quantitative marker for nutritional status), 11 diabetes mellitus status, nicotine use within the past year, urinary incontinence status, surgical history, and ASA score. To determine hospital-associated risk factors for SSI in patients, the following variables were included in the analysis: specific operating room, operating room personnel, surgeon, procedures performed, insertion of implants, timing of preoperative antimicrobial prophylaxis, presence of hyperglycemia after the operation, occurrence of hypothermia (intraoperative core body temperature of!36 C), preoperative hair removal, preoperative skin antisepsis, and length of stay. Descriptive statistics were prepared for all variables. The distribution of each risk factor by number of patients or median value was calculated both for case patients and for control patients. For all potential risk factors, an individual odds ratio with the associated 95% confidence interval and P value was calculated. Multivariable analysis was conducted using logistic regression to control for confounding variables. The modeling

3 886 infection control and hospital epidemiology september 2009, vol. 30, no. 9 strategy for developing a multivariable model in logistic regression presented by Hosmer and Lemeshow was used. 12 Specifically, univariate logistic regression models were analyzed, and variables found to have a P!.25 were included for consideration into the multiple-variable model, as were any variables known to have statistically significant epidemiologic or biologic effects. All risk factors addressed in the guideline for prevention of SSI 9 were included. The final model included variables with a P!.10, and a Hosmer-Lemeshow goodness-of-fit test was used to assess the final model. Analyses were performed using the statistical program packages Stata 9.0 (Statacorp) and NCSS (NCSS). results The overall SSI rate for spinal procedures during the surveillance period was 24% (55 of 234 procedures). Table 1 shows patient-associated SSI risk factors among the 234 patients (55 case patients and 179 control patients) who underwent spinal surgery at the study hospital between December 15, 2003, and August 15, Case patients and control patients were fairly evenly distributed by age and sex. Case patients were more likely than control patients to be receiving workers compensation benefits, to have previously undergone spinal surgery, to be obese, and to have comorbidities. The univariate analysis showed statistically significant differences between the 2 groups in the presence of comorbidities and an ASA score above the population median of 2. On univariate analysis, a greater body mass index, as a continuous variable, was shown to be significantly associated with being a case patient, but a diagnosis of obesity, as a dichotomous variable, was not significant. In addition to patient-associated risk factors, hospital-associated risk factors were analyzed (Table 2). Procedures and interventions performed in the hospital, as well as environmental exposures and exposures to hospital personnel, were evaluated to determine whether any of these variables had a significant impact on patient outcomes. In the univariate analysis, a number of risk factors were identified as significant. Surgeon A performing the operation was found to be significantly associated with becoming a case patient. Surgery type was also significant, with laminectomies and non NNIS system classified procedures associated with increased risk. Case patients had higher numbers of people in the operating room during the procedure than did control patients, and case patients were significantly more likely to have had a total number of people in the room above the population mean of 9. The method of skin antisepsis also had a significant effect, with use of povidone-iodine alone for skin preparation showing a protective effect. Case patients also had a significantly longer median surgical duration than control patients, and case patients had a longer length of hospital stay following surgery. Use of any specific operating room was not associated with becoming a case patient. Other findings not found to be significant include methods of hair removal and timing of antibiotic prophylaxis. On the basis of the outcomes of the univariate analysis, surgeon data were combined to create a dichotomous variable for exposure to surgeon A. A dichotomous variable was also created for hair removal; this compared patients who were shaved to all others. On the basis of the univariate analysis, the following variables were included in the logistic regression model: age, sex, workers compensation status, serum albumin level, nicotine use, incontinence, surgical history, obesity, presence of comorbidities, ASA score, length of stay between surgery and discharge, exposure to surgeon A, procedure type, number of procedures performed, surgical duration, total number of table 1. Patient-Associated Risk Factors for Case and Control Patients Who Underwent Spinal Procedures at the Study Hospital between December 15, 2003, and August 15, 2005 Variable Case patients ( n p 55) Control patients ( n p 179) Univariate OR (95% CI) P Age Median (range), years 44 (31 73) 45 (22 77) Greater than population median of 45 years 23/54 (43) 77/174 (44) 0.93 ( ).83 Female sex 34/55 (62) 109/177 (62) 1.01 ( ).98 Receipt of Worker s Compensation 42/55 (76) 114/176 (65) 1.76 ( ).11 Obesity (body mass index x30) 32/47 (68) 72/167 (43) 2.81 ( ).003 Serum albumin level!3 mg/dl 17/37 (46) 38/87 (44) 1.07 ( ).857 Diabetes mellitus 5/51 (10) 21/171 (12) 0.79 ( ).65 Nicotine use in previous year 28/53 (53) 76/174 (44) 1.44 ( ).24 Urinary incontinence 6/51 (12) 11/173 (6) 1.96 ( ).21 Previous spinal surgery 29/46 (63) 88/171 (51) 1.61 ( ).16 Presence of comorbidities 44/53 (83) 115/176 (65) 2.59 ( ).02 ASA score greater than population median of 2 17/49 (35) 38/175 (22) 1.92 ( ).065 note. Data are no. (%) of patients, unless otherwise indicated. Many records were missing data for individual variables. ASA, American Society of Anesthesiologists; CI, confidence interval; OR, odds ratio.

4 risk factors for ssis 887 table 2. Hospital-Associated Risk Factors for Case and Control Patients Who Underwent Spinal Procedures at the Study Hospital between December 15, 2003, and August 15, 2005 Variable Case patients ( n p 55) Control patients ( n p 179) Univariate OR (95% CI) P Surgeon involved Surgeon A 32/54 (59) 55/176 (31) Reference Surgeon B 13/54 (24) 30/176 (17) 0.67 ( ).32 Surgeon C 1/54 (2) 9/176 (5) 0.17 ( ).10 Surgeon D 5/54 (9) 70/176 (40) 0.11 ( )!.01 Surgeon E 1/54 (2) 9/176 (5) 0.19 ( ).13 Other 3/54 (6) 12/176 (7) 0.39 ( ).17 No. of people in operating room Median (range), no. of people 10 (4 18) 8 (5 21) Greater than population median of 9 people 24/47 (51) 50/175 (29) 2.61 ( ).004 Surgery type Fusion 34/55 (62) 88/178 (49) Reference Laminectomy 10/55 (18) 64/178 (36) 2.47 ( ).02 Other 11/55 (20) 26/178 (15) 2.71 ( ).04 No. of procedures performed Median (range), no. of procedures 4 (1 13) 4 (1 12) Greater than population median of 4 18/54 (33) 37/177 (21) 1.89 ( ).60 Surgical duration Median (range), minutes 140 (45 485) 89 (29 325) Greater than population median of 100 minutes 34/47 (72) 76/176 (43) 3.44 ( )!.01 Insertion of implants 35/50 (70) 116/177 (66) 1.23 ( ).56 Time antibiotics given prior to surgery start Median (range), minutes 75 (14 428) 74 (3 313) Greater than population median of 74 minutes 17/44 (50) 60/161 (37) 1.06 ( ).87 Fasting blood glucose level Median (range), mg/dl 103 (73 348) 98 (15 292) Greater than population median of 100 mg/dl 16/46 (35) 31/101 (31) 1.20 ( ).62 Body temperature Median (range), C 36 (34 39) 36 (34 39) Above population median of 36 C 28/50 (56) 101/170 (59) 0.87 ( ).67 Method of preoperative skin antisepsis Iodine and DuraPrep 39/48 (81) 79/171 (46) Reference Iodine only 5/48 (10) 84/171 (49) 0.12 ( )!.01 Chlorhexidine gluconate 1/48 (2) 2/171 (1) 2.02 ( ).62 Other 3/48 (6) 7/171 (4) 0.51 ( ).55 Length of stay Median (range), days 4 (0 19) 2 (0 12) Greater than population median of 2 days 41/55 (75) 71/177 (40) 4.37 ( )!.01 Length of stay before surgery Median (range), days 0 (0 15) 0 (0 7) Greater than population median of 0 days 5/55 (9) 13/177 (7) 1.26 ( ).67 Length of stay after surgery Median (range), days 4 (0 14) 2 (0 11) Above population median of 2 days 41/55 (75) 67/177 (37) 4.81 ( )!.01 note. Data are no. (%) of patients, unless otherwise indicated. Many records were missing data for individual variables. CI, confidence interval; OR, odds ratio. people in operating room, hair removal, and use of povidoneiodine. Table 3 presents the variables that remained in the final logistic regression model. In the final model, a surgical duration of greater than 100 minutes and the presence of comorbidities at the time of surgery were the only variables independently associated with increased risk of SSI. The use of povidone-iodine alone for skin preparation was shown to be protective. A Hosmer-Lemeshow goodness-of-fit test indicates that the model fits the data. discussion As seen in previous studies, the results of this study confirm that risk of SSI following spinal operations is increased by extended surgical duration and by the presence of comor-

5 888 infection control and hospital epidemiology september 2009, vol. 30, no. 9 table 3. Final Logistic Regression Model of Risk Factors for Case and Control Patients Who Underwent Spinal Procedures at the Study Hospital Variable Odds ratio (95% CI) P Surgical duration greater than population median of 100 minutes 2.48 ( ).025 Use of povidone-iodine only for skin preparation 0.16 ( )!.001 Presence of comorbidities 3.15 ( ).020 note. Hosmer-Lemeshow goodness-of-fit test, 7.01; P p CI, confidence interval. bidities. Prior studies had shown that obesity and diabetes could both be independent risk factors for infection; 9,13-17 however, they were not statistically significant in multivariable analysis in this study population. In addition, this study revealed that the use of only povidone-iodine for skin preparation was associated with decreased risk of infection compared with other antiseptic products. Case patients were more likely than control patients to have antisepsis performed with iodine combined with Dura- Prep, a 3M product containing 0.7% available iodine and 74% isopropyl alcohol. No information was available on the type of iodine preparation (scrub, paint, or gel) or the order in which the 2 products were used. This practice is not consistent with the manufacturer s instructions for use. Chlorhexidine gluconate is the current recommended skin antiseptic for orthopedic surgeries; however, this was used in only 1 case patient and 2 control patients. Further study on skin preparation and SSIs should be conducted in a setting that has a higher rate of use of chlorhexidine gluconate. Interestingly, several risk factors previously demonstrated by other studies and known to be associated with risk of SSI 9 were not shown to be statistically significant in this population, such as urinary incontinence, 18,19 nicotine use, 9,20 method of hair removal, 21 antibiotic prophylaxis, 22 or blood glucose control. 23,24 In addition, there was no association with specific hospital staff 25 or with patient workers compensation status. Many variables may have been potential confounders in this study. For example, the surgeon s preferred practices likely influenced hair removal and selection of skin antisepsic products. However, adjustment for confounding variables did not eliminate key associations or change the final model. It is likely that some important risk factors were not included in this study because either the data were not available or the risk factor was unrecognized. In addition, the large number of variables studied may have contributed to some false associations by chance rather than due to their true effect on modifying the risk of postsurgical infection. The study hospital implemented several control measures during the study period in response to the increased rate of SSI, which may have biased the results toward the null. The hospital implemented the following measures on the basis of CDC recommendations 9 for the prevention of SSI. (1) The hospital switched to the use of clippers for all preoperative hair removal. (2) Ventilation and airflow in the operating room suites were assessed to ensure compliance with Association of Peri-Operative Registered Nurses and American Institute of Architects parameters. 26 (3) All patients were asked to take showers with a chlorhexidine gluconate based antimicrobial skin cleanser the night before and the morning of surgery to reduce levels of the patient s own skin flora. (4) The appropriateness of antibiotic prophylaxis administered prior to surgery was reviewed, and current antibiotic recommendations were sent to physicians in all surgical specialties. 22 (5) A performance improvement study was conducted to determine whether the chlorhexidine gluconate shower was being implemented by patients, whether blood glucose levels were being documented on the day of surgery, and whether preoperative antimicrobial prophylaxis was being used. (6) The discharge instructions given to patients on release from the hospital were modified to place wound care at the beginning of the instructions rather than at the end of the multipage packet. Case patients were identified through several methods: laboratory culture and wound surveillance, monitoring of surgical patient readmissions within 30 days (or within 1 year if spinal implants were inserted at the time of the surgical procedure), and surgeon surveys. In addition, a comprehensive medical record review was performed for all patients who underwent spinal surgery within the study period. However, it is possible that some infections were missed, which would bias the study toward the null and make it more difficult to identify true risk factors. Unfortunately, data were unavailable for events that occurred after the patient was discharged from the hospital, and it is likely that in a subset of control patients infections became evident following discharge. This study relied on information that was available in the patients medical records. It is possible that information was recorded incorrectly or was not available in the patients charts. It is also possible that patients whose postoperative follow-up was not performed at the study hospital could be misclassified as case or control patients. However, one of the major strengths of this study is that data were available for both case and control patients on a wide variety of risk factors, which allowed this study to look at a broad cross section of potential factors that may influence infection. While most ongoing data collection by the study hospital s infection control practitioner is retrospective, the data were recorded in the patient s chart at the time of the procedure or test, thus minimizing recall bias. Another strength of this study is that cohort data on infection status were available for the study time period; therefore, it was possible to calculate incidence rates of SSI for this study period. Multiple risk-stratified studies that used NNIS system methods were performed during 2004 following the identification of the initial cluster of infections. The in-

6 risk factors for ssis 889 fection rates in the lowest risk groups were significantly higher than published NNIS system rates, suggesting that issues at the hospital level may have contributed to the increased infection rates found in this study. We found that risk of SSI following spinal procedures is increased by extended surgical duration and the presence of comorbidities, while the use of only povidone-iodine for skin preparation decreased the risk for infection. The findings from this study may be useful to other hospitals and surgical facilities in the evaluation of their infection control policies and procedures. acknowledgments We thank the study hospital staff and physicians for their assistance, as well as the staff of Infection Prevention and Management Associates. We also thank Dr Eric Boerwinkle and Dr Robert Roberts at the University of Texas Health Science Center at Houston for their input. Potential conflicts of interest. All authors report no conflicts of interest relevant to this article. Address reprint requests to Kristy Murray, DVM, PhD, University of Texas Health Science Center at Houston, Center for Infectious Diseases, School of Public Health, 1200 Herman Pressler, Room 334, Houston, TX references 1. Martone WJ, Nichols RL. Recognition, prevention, surveillance and management of surgical site infections: introduction to the problem and symposium interview. Clin Infect Dis 2001; 33(Suppl 2):S67 S National Nosocomial Infections Surveillance System. National Nosocomial Infections Surveillance System: Semiannual Report. Atlanta, GA: Centers for Disease Control and Prevention; Dhillon KS, Kok CS. The incidence of post-operative wound infection in orthopaedic surgery. Med J Malaysia 1995; 50: Roy MC, Perl TM. Basics of surgical-site infection surveillance. Infect Control Hosp Epidemiol 1997; 18: Kirkland KB, Briggs JP, Trivette SL, Wilkinson WE, Sexton DJ. 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