Risk Factors for Sternal and Leg Surgical Site Infections after Cardiac Surgery in Taiwan

Chih-Hung Ku1, Shu-Lin Ku2, Jeo-Chen Yin3 and An-Jen Lee4

1 School of Public Health, National Defense Medical Center, National Defense University, Taipei, Taiwan
2 Cardiovascular Intensive Care Unit, Taipei Veterans General Hospital, Taipei, Taiwan
3 Nursing Department, Taipei Veterans General Hospital, Taipei, Taiwan
4 Deputy Director, Taipei Veterans General Hospital, Taipei, Taiwan

Reprint requests to Dr. Chih-Hung Ku, School of Public Health, National Defense Medical Center, National Defense University, P.O. Box 90048-509, Taipei, Taiwan 114 (e-mail: cku{at}mail.ndmctsgh.edu.tw).

Received for publication December 8, 2003. Accepted for publication November 19, 2004.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
To account for time factors related to hospitalization, the authors calculated incidence rates of surgical site infection (SSI) instead of cumulative incidence and assessed risk factors for SSI after cardiac surgery. From July 1999 to August 2000, all cardiac surgery patients in the Taipei Veterans General Hospital (Taipei, Taiwan) were invited to join the study. Data were collected by chart review, including information on patient characteristics and potential risk factors at the preoperative, intraoperative, and postoperative stages. The authors employed multiple logistic regression analyses using a generalized logit model to assess associations of interest. SSI incidence rates were 2.5 episodes per 1,000 person-days for the sternum and 3.6 episodes per 1,000 person-days for the leg. After adjustment for covariates, age (in years), gender (female vs. male), New York Heart Association classification (moderate/severe vs. normal/mild), creatinine concentration (mg/dl), and duration of surgery (in minutes) were significantly associated with sternal SSI, while age, peripheral arterial occlusive disease, and length of stay in the intensive care unit (in hours) were significantly associated with leg SSI. In addition to patients' characteristics and health situations, the significant findings for duration of surgery and length of intensive care unit stay indicate that the incidence rate is more appropriate than cumulative incidence for studying risk factors for SSI.

arterial occlusive diseases; cohort studies; cross infection; incidence; logistic models; surgical wound infection; Taiwan; thoracic surgery


Abbreviations: CI, confidence interval; ICU, intensive care unit; NYHA, New York Heart Association; OR, odds ratio; SSI, surgical site infection


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
The site of surgery is the most common site of nosocomial infection (37 percent) (1Go). Surgical site infection (SSI) is a nosocomial infection and a complication of cardiac surgery that generates increased costs and longer hospital stays in comparison with patients without complications. The documented incidence of SSI in terms of cumulative incidence varies from 0.6 percent to 3 percent (2Go, 3Go). Many risk factors have been identified as contributing to the development of SSI: age (4Go, 5Go), gender (6Go–8Go), body mass index (6Go), diabetes mellitus (5Go–13Go), chronic obstructive pulmonary disease (6Go, 14Go, 15Go), obesity (9Go, 10Go, 12Go, 15Go, 16Go), previous cardiac surgery (10Go, 17Go), use of antibiotics (11Go, 15Go, 18Go) or steroids (13Go) after admission to the hospital, preoperative renal failure (19Go), urgency of surgery (19Go), a bilateral internal thoracic artery procedure (5Go–13Go), technical errors of sternal incision (20Go), internal mammary artery grafts (12Go), blood transfusions (12Go), reexploration (5Go, 19Go, 21Go), inotropic support (16Go), prolonged intubation (20Go), use of an aortic balloon (15Go, 20Go), duration of cardiopulmonary bypass (5Go–13Go), and postoperative dialysis (8Go). However, the risk factors for SSI after sternotomy remain unclear.

The aim of this study was to assess rates of and risk factors for SSI, including sternal and leg SSI, after cardiac surgery at the Taipei Veterans General Hospital, Taipei, Taiwan. Most of the cardiac surgery procedures performed in this hospital include coronary artery bypass grafting and valve repairs or replacements. Both valve replacement and coronary artery bypass grafting entail making an incision down the front of the chest through the sternum. However, in addition to the chest incision, there is one more chance of incurring an SSI for bypass patients, because of the harvesting of the saphenous vein from the leg. We made the assumption that SSIs, including sternal SSI and leg SSI, were related to patient and surgical characteristics (especially the time factor in each process) and characteristics of medical care personnel at the pre-, intra-, and postoperative stages.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Study design
We conducted a prospective open-cohort study to assess the rate of sternal SSI after cardiac surgery at Taipei Veterans General Hospital from July 1999 to August 2000. Within this cohort, patients were classified into four groups—1) sternal SSI, 2) leg SSI, 3) double SSI (both sternum and leg), and 4) no SSI (controls)—for evaluation of SSI risk factors. This study was supported by the Institutional Review Board Human Subjects Committee of Taipei Veterans General Hospital.

Study population
Patients who had undergone cardiac surgery were invited to enroll in the study during the study period. Patients undergoing cardiac surgery were usually admitted a few days before the surgical procedure for completion of physical and laboratory examinations to determine whether cardiac surgery was needed. A total of 471 cardiac surgery patients were included in the study. No participant withdrew from the study.

Case criteria
After the study participant had been admitted to one of the two cardiovascular surgery units prior to cardiac surgery, a researcher (S.-L. K.) started to collect data on his or her risk factors. The researcher continued to collect data throughout the subject's hospitalization period.

Sternal SSI was defined according to the SSI criteria of the US Centers for Disease Control and Prevention (22Go, 23Go). Infection occurs within 30 days after surgery and can include the following types: 1) superficial incisional (infection above the sternum with no bony involvement); 2) deep incisional (infection involving the sternum); and 3) organ/space (site-specific infection, such as mediastinitis). Leg SSI was defined as redness, swelling, increased pain, excessive bleeding, or discharge at the incision site among the patients who had undergone coronary artery bypass grafting. All SSI cases were diagnosed by attending physicians and confirmed by the nosocomial infection control committee. Patients who did not have any SSI formed the control group.

Risk factors
Potential risk factors for sternal SSI were classified into three groups according to stage (preoperative, intraoperative, and postoperative). Preoperative potential risk factors included demographic factors (age, gender, weight, height, body mass index, and smoking) (table 1) and factors pertaining to medical history (diabetes, hypertension, use of antibiotics, chronic obstructive pulmonary disease, peripheral arterial occlusive disease, previous cardiac surgery, and obesity (body mass index ≥27)). Posthospitalization parameters included admission to the intensive care unit (ICU) before surgery and length of stay in the ICU, use of steroids, New York Heart Association (NYHA) classification, lung function, left-side ejection fraction, right-side ejection fraction, albumin concentration, and creatinine concentration (table 2). Intraoperative potential risk factors included urgency of surgery, operating room, surgical team, surgical procedure, duration of surgery, use of an intraaortic balloon pump, intraaortic balloon pump time, use of an internal mammary artery, total bypass time, aortic clamp time, blood loss, use of left ventricular assist devices, blood transfusion, blood transfusion materials, homeostasis (good = blood loss <1,000 ml; poor = blood loss ≥1,000 ml), cardiac massage, inotropic support, and complications (table 3). Postoperative potential risk factors included duration of intermittent positive pressure ventilation and length of stay in the ICU after cardiac surgery (table 4).


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TABLE 1. Potential preoperative risk factors for cardiac surgical infection—demographic factors and medical history, Taipei Veterans General Hospital, Taipei, Taiwan, 1999–2000*

 

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TABLE 2. Potential preoperative risk factors for cardiac surgical infection—parameters measured during hospitalization, Taipei Veterans General Hospital, Taipei, Taiwan, 1999–2000*

 

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TABLE 3. Potential intraoperative risk factors for cardiac surgical site infection, Taipei Veterans General Hospital, Taipei, Taiwan, 1999–2000*

 

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TABLE 4. Potential postoperative risk factors for cardiac surgical site infection, Taipei Veterans General Hospital, Taipei, Taiwan, 1999–2000

 
Data analysis
We used cumulative incidence to account for infection. However, we also considered that the hospital environment might be a potential risk factor for either sternal SSI or leg SSI and that different lengths of hospital stay imply different durations of environmental exposure. Thus, we used person-days to calculate the incidence rate in order to account for the time factor (different lengths of stay) for each subject.

To assess risk factors for sternal and leg SSI, we used one-way analysis of variance for univariate continuous variables and the chi-square test for categorical variables. In addition, we conducted Fisher's exact test whenever the chi-square expected value of at least one cell was less than 5 (24Go).

Since there were 42 potential risk factors (see tables 1–4), to avoid multicollinearity among the explanatory variables we performed collinearity diagnostic analysis to select variables from the models step by step, with the following criteria: tolerance greater than 0.4 (25Go) or variance inflation less than 2.5 (25Go), condition number less than 10 (26Go, 27Go), and a variance of two or more variables no greater than 0.5 (26Go, 27Go). Since there were only four study subjects with double SSI, they were dropped during the analysis because of the small sample size. The dependent variable was a nominal response in three categories: 1) persons with sternal SSI, 2) persons with leg SSI, and 3) controls. We performed multiple logistic regression analyses with a generalized logit link function and stepwise selection, using a significance value of p < 0.25 for entering the models and a value of p < 0.05 for staying in the models, to evaluate risk factors for SSI and to adjust for potential confounders. The adjusted odds ratio from the model indicated the association of interest. SAS software, version 8.2 (SAS Institute, Inc., Cary, North Carolina), was used for all models.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Cumulative incidence and incidence rate
All of the 471 cardiac surgery patients were enrolled during the study period. Within this cohort, 323 patients underwent coronary artery bypass grafting. Twenty-four of the 471 patients had sternal SSI, including six with superficial incisional infection, 11 with deep incisional infection, and seven with mediastinitis; 23 of the 323 bypass patients had leg SSI; and four of the 471 patients had both sternal and leg infections.

The cumulative incidences of sternal SSI, leg SSI, and both types of infection were 5.1 percent, 7.1 percent, and 0.8 percent, respectively. However, since patients were neither admitted to the hospital nor discharged from the hospital at the same time, the study subjects were "dynamic" (28Go–30Go) during the study period. We considered the possibility that the hospital environment might be a risk factor for this open cohort (28Go–30Go). In addition, each patient's length of stay was different. We thus applied the incidence rate to account for the time factor in terms of "person-days" in the denominator (28Go–30Go). The total lengths of stay in terms of person-days among the 471 study subjects and 323 bypass patients in this cohort were 9,459 person-days and 6,371 person-days, respectively. The infection incidence rates per 1,000 person-days following cardiac surgery were 2.5 episodes for sternal SSI (24/9,459 person-days) and 3.6 episodes for leg SSI (23/6,371 person-days).

Preoperative risk factors
Univariate analysis indicated that there was a significant difference in age, chronic obstructive pulmonary disease, and peripheral arterial occlusive disease among the sternal SSI patients, the leg SSI patients, and the controls, respectively (table 1). The average ages of study subjects in order of seniority were 72.3 years for leg SSI patients, 69.0 years for sternal SSI patients, and 65.4 years for controls. The percentages of subjects with chronic obstructive pulmonary disease were 26.1 for leg SSI patients, 12.5 for sternal SSI patients, and 9.8 for controls. The percentages of subjects with peripheral arterial occlusive disease were 30.4 for leg SSI, 8.6 for controls, and 4.2 for sternal SSI. However, there were no significant differences in weight, height, body mass index, gender, smoking status, or medical history, including histories of diabetes, hypertension, and previous cardiac surgery (table 1).

Physical parameters measured after hospital admission included whether the patient stayed in the ICU before surgery, length of stay in the ICU, NYHA classification, results of lung function testing, use of steroids, use of antibiotics, left-side ejection fraction, right-side ejection fraction, albumin concentration, and creatinine concentration (table 2). There were significant differences for NYHA classification (p = 0.0104) and right-side ejection fraction (p = 0.0109), and there was marginal significance for the lung function test (p = 0.0515) among sternal SSI patients, leg SSI patients, and controls. However, there were no significant differences in the other parameters (table 2).

Intraoperative risk factors
Among the 18 potential intraoperative risk factors, univariate tests indicated that surgical procedure (p = 0.0155), duration of surgery (p = 0.0005), use of an intraaortic balloon pump (p = 0.0039), blood loss (p = 0.0118), homeostasis (p = 0.0145), cardiac massage (p = 0.0348), inotropic support (p = 0.0159), and complications (p = 0.0057) showed significant differences among the sternal SSI patients, leg SSI patients, and controls (table 3). However, there were no significant differences in the following univariate variables: urgency of surgery, operating room, surgical team, intraaortic balloon pump time, use of an internal mammary artery, total bypass time, aortic clamp time, use of left ventricular assist devices, blood transfusion, and blood transfusion materials (table 3).

Postoperative risk factors
All of the postoperative risk factors showed significant differences among sternal SSI patients, leg SSI patients, and controls (table 4). The average durations of intermittent positive pressure ventilation, in descending order, were 254.5 hours for patients with sternal SSI, 178.7 hours for patients with leg SSI, and 83.2 hours for controls (p = 0.0154). The average durations of ICU stay after surgery, in descending order, were 79.1 hours for leg SSI patients, 78.3 hours for sternal SSI patients, and 53.9 hours for controls (p = 0.0005).

Multicollinearity
To consider the possibility that there might be factors at the preoperative stage that were collinear or confounding or that modified the effect of assessed risk factors from the other stages, we put together 42 potential risk factors to evaluate multicollinearity. After the collinearity diagnostic analysis, weight, height, body mass index, admission to the ICU before surgery, total bypass time, aortic clamp time, use of an intraaortic balloon pump, and use of left ventricular assist devices were dropped because of multicollinearity. The final model in collinearity diagnostic analysis matched the criteria. The other 34 variables were retained in the analysis for the generalized logit model.

Generalized logit model
After adjustment for patient characteristics (obesity, smoking, hypertension, diabetes, chronic obstructive pulmonary disease, previous cardiac surgery, lung function, use of steroids, use of antibiotics, left- and right-side ejection fractions, and albumin concentration) and intraoperative or postoperative covariates (urgency of surgery, operating room, surgical team, surgical procedure, intraaortic balloon pump time, use of an internal mammary artery, blood loss, blood transfusion, blood transfusion materials, homeostasis, cardiac massage, inotropic support, complications, and duration of intermittent positive pressure ventilation), we found that age (odds ratio (OR) = 1.14, 95 percent confidence interval (CI): 1.05, 1.23), gender (OR = 8.14, 95 percent CI: 2.04, 32.51), NYHA classification (OR = 4.72, 95 percent CI: 1.39, 16.07), creatinine concentration (OR = 2.05, 95 percent CI: 1.19, 3.54), and duration of surgery (OR = 1.01, 95 percent CI: 1.01, 1.02) were risk factors for sternal SSI, while age (OR = 1.09, 95 percent CI: 1.01, 1.17), peripheral arterial occlusive disease (OR = 7.17, 95 percent CI: 2.05, 25.09), and length of stay in the ICU after cardiac surgery (OR = 1.02, 95 percent CI: 1.01, 1.03) were risk factors for leg SSI (table 5; adjusted r2 = 0.35). With a 1-year increase in patient age, the risks of sternal SSI and leg SSI would be increased 14 percent and 9 percent, respectively. Compared with patients with an NYHA classification of mild or normal, patients who had an NYHA classification of moderate or severe had 4.7 times the risk of sternal SSI. With an increase in creatinine level of 1 mg/dl, the risk of sternal SSI was increased twofold. In addition, with a 1-minute increase in the duration of surgery, the risk of sternal SSI for all patients was increased by 1 percent. For leg SSI patients, in addition to age, patients with peripheral arterial occlusive disease had 7.2 times the risk of leg SSI as patients without peripheral arterial occlusive disease. With a 1-hour increase in ICU stay, the risk of leg SSI was increased by 2 percent.


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TABLE 5. Risk factors for sternal and leg wound infections after cardiac surgery, Taipei Veterans General Hospital, Taipei, Taiwan, 1999–2000

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Cumulative incidence vs. incidence rate
We calculated infection rates in terms of cumulative incidence (5.1 percent and 7.1 percent for sternal SSI and leg SSI, respectively) and incidence rate (2.5 episodes and 3.6 episodes per 1,000 person-days for sternal and leg SSI, respectively). Generally, we used cumulative incidence to express the rate of SSI in the study, such as five sternal SSI cases and seven leg SSI cases per 100 patients. However, to investigate risk factors for SSI after cardiac surgery, we preferred to use the incidence rate (2.5 episodes and 3.6 episodes per 1,000 person-days) instead of cumulative incidence, for the following reasons: 1) study subjects formed a "dynamic" population (28Go–30Go) and an "open" cohort (28Go–30Go) during the study period; 2) each patient's exposure in terms of length of stay after admission was different, and time was an important factor in accounting for the risk of SSI; and 3) the incidence rate accounted for time in terms of "person-time" but cumulative incidence did not.

In this study, we considered the patients' characteristics and their health conditions as well as multicollinearity to assess risk factors for two different types of SSI at one time, using the controls as the reference group in the models. The results from the generalized logit model indicated that, in addition to the patients' demographic characteristics (age and gender) and health status (peripheral arterial occlusive disease, NYHA classification, and creatinine level), duration of surgery and length of ICU stay after surgery were risk factors for SSI (table 5); this supports our consideration that time is an important factor in the investigation of SSI.

Collinearity, confounding, effect modification, and generalized logit model
We considered that factors might exist at the preoperative stage that were either collinear or confounding or that modified the effect of assessed risk factors from the other stages; we put the potential risk factors together to account for the multicollinearity. After the collinearity diagnostic analysis, we conducted multiple logistic regression with the generalized logit link function to assess associations of interest, as well as to adjust for potential confounders. This method was generally applied whenever the response level was nominal (no natural ordering) (31Go). Since, in our study, the dependent variable was nominal (sternal SSI patients, leg SSI patients, and controls), we thought that multiple logistic regression analyses with a generalized logit link function were appropriate for assessment of the associations of interest. Moreover, to evaluate effect modification due to age or gender, we likewise checked the interaction terms among age, gender, and other variables of interest (e.g., creatinine level, peripheral arterial occlusive disease, NYHA classification, and duration of surgery). However, no effect modification was detected.

Risk factors for SSI
We constructed the models from 34 risk factors after collinearity diagnostic analysis by using multiple logistic regression with a generalized logit link function for the nominal dependent variable and stepwise selection, with a significance value of p < 0.25 for entering the models and a value of p < 0.05 for staying in the models. After adjustment for the covariates, four parameters related to patient characteristics or health (age, gender, NYHA classification, and creatinine level) and duration of surgery were risk factors for sternal SSI, while two patient parameters (age and peripheral arterial occlusive disease) and length of stay in the ICU after surgery were risk factors for leg SSI (table 5).

The results of this study support findings from previous reports that age is a risk factor for sternal SSI (5Go), that gender is a predictor of sternal SSI in cardiac surgery patients (7Go), being especially dominant in females (8Go), and that creatinine level is a risk factor for sternal SSI (32Go–37Go). However, in this study, the significance of gender (female vs. male) might have resulted from our having fewer female patients than males (female:male ratio = 1:4.4). Seven percent of females (6 of 83) had sternal SSI, as opposed to 5 percent of males (18 of 361) (table 1).

NYHA classification has been reported to be a risk factor for leg SSI (38Go). According to this classification, patients in class III or IV have worse heart function than those in class I or II in carrying out physical activities. NYHA classification was a risk factor for sternal SSI in this study. Since, in this study, we used the generalized logit model to assess the associations of interest for sternal SSI and leg SSI in the same model after performing diagnostic analysis for multicollinearity, controlling for confounders, and taking into consideration effect modification, we deem this report more appropriate than the previous report (38Go). In addition, peripheral arterial occlusive disease was defined as the obstruction or narrowing of the lumen of the peripheral arteries, resulting in an interruption of blood flow. Peripheral arterial occlusive disease has been reported to be one of the risk factors for mortality in patients undergoing coronary artery bypass grafting at this same hospital (39Go); however, to our knowledge, this study is the first to have found peripheral arterial occlusive disease to be a risk factor for leg SSI.

In addition to patient characteristics, several reports have shown that obesity (9Go, 10Go, 12Go, 15Go, 16Go), diabetes (5Go–13Go), chronic obstructive pulmonary disease (6Go, 14Go, 15Go), previous cardiac surgery (10Go, 17Go), use of antibiotics (11Go, 15Go, 18Go) or steroids (13Go), and preoperative renal failure (19Go) are preoperative risk factors. Jakob et al. (9Go) reported that 38 (10 percent) of 376 adult cardiac surgery patients had developed a sternal SSI and proved that obesity, diabetes, and nasal carriage of Staphylococcus aureus were independent risk factors. Spelman et al. (10Go) reported that diabetes and obesity were independent predictors of sternal SSI following coronary artery bypass grafting. Slaughter et al. (13Go) reported that use of steroids and diabetes were independent risk factors for SSI in bypass patients; however, these variables were not significant in the generalized logit model. This might be due to the homogeneity of our study subjects; all were older veterans who had lived similar military lifestyles for many years prior to retirement.

Previous cardiac surgery has been reported to be an independent predictor of the development of sternal SSI (10Go, 17Go). However, after adjustment for the other significant factors, previous cardiac surgery was not a predictor in our study.

Use of antibiotics was an important factor in the risk of sternal SSI. Trick et al. (11Go) reported that the timing of use of cefuroxime was an independent risk factor for sternal SSI. Patients who took cefuroxime 2 or more hours before their incision had 5 times the risk of developing a sternal SSI as those who took none (11Go). Nooyen et al. (18Go) reported that a single dose of cefuroxime was as effective as a 3-day course in the prevention of SSI in bypass patients. Likewise, Sisto et al. (17Go) reported that single-dose ceftriaxone prophylaxis was as effective as cefuroxime given for 48 hours postoperatively in patients undergoing coronary bypass surgery. In the current observational study, prophylactic antibiotics (either cefuroxime/tobramycin or vancomycin/teicoplanin) were administered starting 1 hour prior to surgery and continuing through the postoperative period. This was routine for all cardiac surgery patients. Univariate and multiple logistic regression analyses indicated that there was no significant difference between the groups. However, of the 158 patients who had been given cefuroxime/tobramycin, seven sternal SSI patients (4.4 percent) and eight leg SSI patients (5.1 percent) still had an SSI; and of the 309 patients (table 2) who had received vancomycin/teicoplanin, 17 sternal SSI patients (5.5 percent) and 15 leg SSI patients (4.9 percent) still had an SSI. Antibiotic resistance might be a problem at this hospital, and we suggest focusing on this issue in a future study.

Use of an intraaortic balloon pump has been reported to be one of the risk factors for infection (15Go, 21Go, 40Go–42Go). The intraaortic balloon pump is a circulatory support device. Patients who need an intraaortic balloon pump are those suspected of having poor circulation, and these devices are especially used for perioperative support of surgical patients with severe left ventricular dysfunction. In our study, 31 of 467 patients used an intraaortic balloon pump, and there was a significant difference in the univariate analysis (p = 0.0039); however, after collinearity diagnostic analysis, use of an intraaortic balloon pump was deleted, and inclusion of balloon pump time in the model did not show a significant difference.

Duration of surgery was found to be a risk factor for sternal SSI. Factors related to duration of surgery included patient disease classification, urgency of surgery, surgical procedure, surgical team, operating room, etc. We adjusted for these factors in the analysis; however, except for age, gender, NYHA classification, and creatinine concentration, none of these factors, which were related to the duration of surgery, were associated with infection. The longer the duration of surgery the more environmental exposure there was, and therefore a higher infection rate was expected. The findings suggest that the operating room environment (e.g., temperature, relative humidity, airflow rate, airflow direction, and aerosols from ventilation outlets) should be examined for other risk factors for sternal SSI in future studies.

Intermittent positive pressure ventilation is always used at this hospital to help patients with their respiratory status postoperatively. In this study, the average times of intermittent positive pressure ventilation among sternal SSI patients, leg SSI patients, and controls were significantly different (254.5 hours, 178.7 hours, and 88 hours, respectively) (p < 0.0154; table 4); however, this significance did not appear after we adjusted for the other risk factors in the generalized logit model (table 5). In addition, length of stay in the ICU after surgery showed significant differences among sternal SSI patients, leg SSI patients, and controls in the univariate comparison (78.3 hours, 79.1 hours, and 53.9 hours, respectively) (p = 0.0005; table 4), and after adjustment for covariates, the length of ICU stay after surgery was likewise one of the risk factors for leg SSI (table 5). The longer the stay in the ICU the higher was the risk of leg SSI. Since duration of surgery was a risk factor for sternal SSI and the ICU was next to both the operating room and the recovery room, we suggested remodeling the building to create operating, recovery, and ICU areas specific to cardiovascular surgery in order to prevent contamination from room to room or between patients in different surgical departments.

This study had several limitations. First, there were only six superficial incisional, 14 deep incisional, and eight mediastinitis SSI cases out of the 471 cardiac surgery patients during the 14-month "observational" study period. However, three of the 14 patients with deep incisional infection and one of the eight mediastinitis patients had double infections at the sternal and leg sites. We dropped the four patients with double infections, leaving the other 24 sternal SSI patients and the 23 leg SSI patients, to compare the risk factors for SSI with 420 controls. These results were helpful to the nosocomial infection control committee in this hospital. Second, although the Centers for Disease Control and Prevention has defined guidelines for tracking SSIs for up to 30 days, we did not trace the patients after their discharges. However, Delgado-Rodriguez et al. (43Go) have shown that most predictors of in-hospital SSI are not predictors of postdischarge SSI. Likewise, Sands et al. (44Go) reported that information routinely collected in health care systems can be the basis for an efficient, largely passive surveillance system for postdischarge SSIs. Platt et al. (45Go) demonstrated that automated claims and pharmacy data from different health plans can be used together to conduct inexpensive, routine monitoring for indicators of postoperative infection. Additional study using health insurance data in Taiwan may prove helpful for the study of postdischarge SSI.

In conclusion, we studied infection rates and risk factors for sternal and leg SSI at a Taiwan veterans' hospital. We have demonstrated that, for comparison of infection rates among hospitals, considering the different lengths of stay in the hospital environment for cardiac surgery patients, the use of incidence rates accounts for the time factor in each related procedure, such as type of surgery, use of an intraaortic balloon pump, use of an aortic clamp, intermittent positive pressure ventilation, and length of ICU stay. After adjustment for patient and surgical characteristics, as well as medical care personnel, the final model indicated that age, gender, peripheral arterial occlusive disease, NYHA classification, creatinine level, duration of surgery, and length of stay in the ICU after surgery were risk factors for SSI. The last two significant factors confirmed our concern that time is an important parameter in studying risk factors for SSI.

We suggest that in addition to factors related to patient and surgical characteristics, operating suite, and medical faculty, other important factors that might contribute to infection include those related to antibiotic resistance and the hospital environment, such as temperature, relative humidity, and ventilation. Further study might focus on the relation between infectious agents cultured from wounds (including antibiotic resistance) and air sample monitoring from hospital environments.


    ACKNOWLEDGMENTS
 
This work was supported by a grant (VGH-TPE-89-120) from the Taipei Veterans General Hospital, Taipei, Taiwan.

The authors gratefully acknowledge the work of the study coordinators, Dr. Shin Ling Tasi and Dr. Shiau Ting Lai; the registered nurses in the cardiovascular intensive care unit, Mei Ling Lin, Ruo Ing Ku, and Feng Chin Huang; and registered nurse Chih-Hau Chang of the infection control committee. They also thank their colleagues in the cardiovascular surgery general wards for participating in the study.


    References
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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