Abstract
Background
Antibiotic-resistant infections have high rates of morbidity and mortality and exposure to antibiotics is the crucial risk factor for development of antibiotic resistance. If surgical antibiotic prophylaxis (SAP) increases risk for antibiotic-resistant infections, prophylaxis may cause net harm even if it decreases overall infection rates.
Study Design
This retrospective cohort study included adults who underwent elective surgical procedures and developed infections within 30 post-operative days. Surgeries from multiple disciplines were included if SAP was considered discretionary by current guidelines. Postoperative antibiotic-resistant infections were defined as positive culture results from any site within 30 post-operative days showing intermediate or non-susceptibility across one or more antibiotic classes. SAP included use of antibiotics within any class and at any dose from one hour before first incision until the end of the operation.
Results
Among 689 adults with post-operative infections, 338 (49%) had post-operative resistant infections. Use of SAP was not associated with post-operative antibiotic-resistant infections (OR 0.99, 95% CI 0.67–1.46). This result remained robust when the SAP definition was extended to antibiotics given within 4 hours before first incision (OR 0.94, 95% CI 0.63–1.40) and when the follow-up window was narrowed to 14 days (OR 0.82, 95% CI 0.50–1.34). Prior antibiotic-resistant infections were associated with risk for post-operative antibiotic-resistant infections (OR 1.81, 95% CI 1.16–2.83).
Conclusion
Use of SAP was not associated with risk for post-operative antibiotic resistant infections in a large cohort of patients with post-operative infections. This provides important reassurance regarding use of surgical antibiotic prophylaxis.
INTRODUCTION
Surgical site infections (SSIs) are responsible for up to 20% of healthcare-acquired infections outside of the intensive care unit and are the most common cause of healthcare-acquired infections amongst surgical patients.(1) Surgical antibiotic prophylaxis (SAP) has been shown to decrease the risk of post-operative infections for a number of procedures across surgical disciplines.(2–4) For many procedures, however, the benefit of SAP is uncertain and the decision to use prophylaxis is at the discretion of the operating surgeon with a large degree of inter-operator variability.
Surgical antibiotic prophylaxis may lower overall infection rates but there is concern that it has the potential to cause harm. A single dose of SAP can increase antibiotic resistance within colonizing bacteria, and consequently SAP could contribute towards antibiotic-resistant infections.(5–7) In the United States, roughly 2 million people develop antibiotic-resistant infections each year. These infections are difficult to treat and have higher morbidity and mortality compared to non-resistant infections.(8, 9) Simultaneously, rates of post-operative infections for select procedures are low and have been getting progressively lower.(10–12)
If surgical antibiotic prophylaxis increases the risk for antibiotic-resistant infections, the potential harm of SAP may outweigh a modest overall reduction in rates of post-operative infections, particularly in procedures with traditionally low rates of post-operative infections. This study was performed to assess the relationship between use of SAP and development of post-operative antibiotic-resistant infections.
METHODS
Population
This was a retrospective cohort study. Adults 18 years old or more evaluated at an urban tertiary care hospital in New York were considered for the study if they had one of a specific list of elective surgical procedures between January 1, 2008 and December 31, 2016. We selected 2008 for the start of the study because it was the earliest date on which complete electronic data was available. For patients with multiple surgeries during the study period, only the first surgery was analyzed. We sought to include a broad list of different surgeries that encompassed as many surgical disciplines as possible and for which surgical antibiotic prophylaxis is considered discretionary according to current multi-society or specialty guidelines.(2, 5, 13–17) Surgical procedures were first identified by relevant coding (Supplementary Table 1), and then filtered using intelligent keyword searches to exclude situations in which multiple codes were used to describe various stages of a single operation (e.g., exploratory laparoscopy and partial pancreatectomy). The select surgical procedures were also reviewed by a group of subject experts for accuracy and concordance with clinical practice behaviors.
Patients were included in the study if they had one of the pre-selected procedures and subsequently developed a post-operative infection within 30 days. Post-operative infection was defined as a post-operative culture from any site or fluid showing bacterial growth and speciation. Surveillance testing for colonization was not included in this definition. The cut-off of 30 days was chosen to balance the duration of the observed effect of single-dose antibiotics (up to 12 months)(18–20) with the assumption that any effect of antibiotics on bacterial resistance patterns would be likely to wane with the passage of time. To focus on incident rather than prevalent infections, patients who developed culture-positive infection within 24 postoperative hours were excluded. To ensure a minimum of follow-up time, patients were also excluded who died within 24 post-operative hours. This study protocol was approved by the institutional review board of Columbia University Medical Center.
Post-operative antibiotic-resistant infections
Post-operative antibiotic-resistant infections were defined as positive bacterial culture results from any site or fluid within 30 post-operative days showing intermediate susceptibility or non-susceptibility across one or more antibiotic classes using the clinical breakpoints from the . Clinical and Laboratory Standards Institute that were in effect at the time when the culture result was performed.(21, 22) Specialized cultures such as cultures performed from stool or vaginal samples were not included. In addition, the results of surveillance swabs or non-culture microbiological data (e.g., PCR or EIA results) were not included. All cultures were performed by a single clinical laboratory using standard techniques.
Primary exposure
The primary exposure was surgical antibiotic prophylaxis, defined as use of antibiotics within any class and at any dose given from 1 hour before first incision until the end of the operation. SAP was ascertained electronically from the provider order entry system; we captured antibiotics given in the pre-operative area as well as antibiotics given in the operating room. The cut-off of 1 hour was chosen based on current guidelines concerning the optimal timing for SAP and was further explored in sensitivity analyses.(5, 23, 24)
Covariates
Automated queries were used to retrieve demographic information, comorbidities using claims data (to compute the Charlson Comorbidity Index),(25, 26) and prior exposure to antibiotics and immunosuppressants (within 90 days of surgery). Immunosuppressants included steroids at a minimum dose of 5 mg of prednisone or equivalent, calcineurin inhibitors, antimetabolites, anti-tumor necrosis factor agents, and mycophenolate. Microbiological data from 90 days before each procedure was gathered including the originating site or fluid (e.g., urine), the organism, and the organism’s resistance pattern. Operative characteristics were captured including pre- and post-operative hospital admission and operative time. Hospital admission immediately before/after the index surgery was classified categorically based on whether there was an admission for ≥24 hours before the surgery or for ≥24 hours afterwards; we also examined whether there was an inpatient hospitalization prior to the index surgery. Operative time was defined as the time from first incision until the time the patient left the room and was classified into approximate tertiles.
Statistical approach
Continuous variables were examined graphically so that appropriate cut-offs could be selected. Categorical variables were compared using the chi-squared test or Fisher’s exact test when 5 or fewer events were expected in any category. The primary outcome was determined using logistic regression modeling to test risk for resistant versus non-resistant infections. We decided a priori that the multivariable model would include variables representing past exposure to antibiotics and representing operative time, because these variables are key potential confounders for the relationship between surgical antibiotic prophylaxis and post-operative antibiotic-resistant infections. To construct the final multivariable model, additional variables were tested stepwise and included if they had a significant independent relationship with the outcome of interest or if they altered the β-coefficient representing SAP by ≥10%. All analyses were performed using STATA statistical software version 14 (StataCorp, College Station, TX) at the α = .05 level of significance.
Sensitivity analyses
The optimal dosing for surgical antibiotic prophylaxis is controversial.(23, 27) To test the robustness of our findings, we repeated the final model after extending the definition of SAP to include antibiotics given from 4 hours before first incision until the end of the procedure. Alternative follow-up timeframes and alternative definitions for antibiotic resistance have been used (22, 28, 29) so, as further tests of robustness, we repeated the final model with the follow-up window narrowed to 14 days and with post-operative antibiotic resistance re-defined as resistance in 3 or more antibiotic classes. To evaluate for the development of post-operative antibiotic resistance in a class-specific manner, we tested the 3 most commonly used prophylactic antibiotics for within-class post-operative resistance (e.g., use of cephalosporins and subsequent cephalosporin resistance). To further explore risk factors for post-operative urinary tract infections, we retrieved data related to the placement of indwelling urinary catheters intra-operatively or during the post-operative period. Selected stratified analyses and alternative cutoffs for continuous variables were also considered within the final model.
RESULTS
Population
There were 22,138 unique adults who had surgeries within the pre-selected categories between 2008 and 2016 and who met other inclusion criteria. Of these, 689 (3.1%) developed infections within 30 post-operative days and were analyzed.
Baseline and operative characteristics
Median time to infection was 10 days (IQR 5–19). Among those with post-operative infections, 550 (80%) subjects received surgical antibiotic prophylaxis. The most common classes of antibiotics used were cephalosporins, followed by piperacillin-tazobactam and gentamicin (Supplementary Table 2). Subjects who developed resistant compared to nonresistant infections were more likely to have prior culture-proven infections (Table 1). The most common operations were cystoscopy, lymph node biopsy, and uncomplicated laparoscopic cholecystectomy (Table 2 and Supplemental Table 3). Most subjects did not require pre-operative hospital admission and most spent <24 post-operative hours in the hospital. Procedures were relatively brief with 56% of patients leaving the operating room within 2 hours after entering it.
Table 1.
Baseline Characteristics, Stratified by Resistant vs NonResistant Postoperative Infection
| Characteristic | All | Resistant infection | Non-resistant infection | p Value | ||
|---|---|---|---|---|---|---|
| n | % | n | % | |||
| Sex | .91 | |||||
| Male | 286 | 141 | 49 | 145 | 51 | |
| Female | 403 | 197 | 49 | 206 | 51 | |
| Age | .22 | |||||
| 18 to 42 y | 111 | 54 | 49 | 57 | 51 | |
| 43 to 60 y | 170 | 74 | 44 | 96 | 56 | |
| >60 y | 408 | 210 | 51 | 198 | 49 | |
| Race/ethnicity | .71 | |||||
| White | 263 | 122 | 46 | 141 | 54 | |
| Black | 49 | 24 | 49 | 25 | 51 | |
| Hispanic | 170 | 88 | 52 | 82 | 48 | |
| Other/unclassified | 207 | 104 | 50 | 103 | 50 | |
| Charlson Comorbidity Index | .44 | |||||
| 0 | 337 | 167 | 50 | 170 | 50 | |
| 1 | 127 | 56 | 44 | 71 | 56 | |
| ≥2 | 225 | 115 | 51 | 110 | 49 | |
| Prior exposure to antibiotics* | .99 | |||||
| No | 526 | 258 | 49 | 268 | 51 | |
| Yes | 163 | 80 | 49 | 83 | 51 | |
| Prior exposure to immunosuppressants* | .37 | |||||
| No | 613 | 297 | 48 | 316 | 52 | |
| Yes | 76 | 41 | 54 | 35 | 36 | |
| Inpatient hospitalization prior to the index surgery* | .35 | |||||
| No | 664 | 328 | 49 | 336 | 51 | |
| Yes | 25 | 10 | 40 | 15 | 60 | |
| Prior VRE colonization* | 0.11 | |||||
| No | 683 | 333 | 49 | 350 | 51 | |
| Yes | 6 | 5 | 83 | 1 | 17 | |
| Prior MRSA colonization* | 0.44 | |||||
| No | 683 | 334 | 49 | 349 | 51 | |
| Yes | 6 | 4 | 67 | 2 | 33 | |
| Prior culture-proven infection* | .04 | |||||
| None | 487 | 231 | 47 | 256 | 53 | |
| Sensitive | 94 | 42 | 45 | 52 | 55 | |
| Resistant ≥1 antibiotic class | 108 | 65 | 60 | 43 | 40 | |
Within the 90 days preceding surgery.
VRE, vancomycin-resistant Enterococcus faecium
Table 2.
Operative Characteristics, Stratified by Resistant versus NonResistant Postoperative Infection
| Characteristic | All | Resistant infection | Non-resistant infection | p Value | ||
|---|---|---|---|---|---|---|
| n | % | n | % | |||
| Preoperative admission for the index surgery | .41 | |||||
| No | 503 | 242 | 48 | 261 | 52 | |
| Yes | 186 | 96 | 52 | 90 | 48 | |
| Procedure type | .12 | |||||
| Endocrine surgery | 27 | 14 | 52 | 13 | 48 | |
| General surgery | 3 | 83 | 51 | 81 | 49 | |
| Gynecology | 164 | 30 | 36 | 53 | 64 | |
| Hand surgery | 83 | 2 | 40 | 3 | 60 | |
| Lymph node biopsy | 5 | 77 | 47 | 88 | 53 | |
| Orthopedic | 165 | 15 | 58 | 11 | 42 | |
| Otolaryngology | 26 | 3 | 100 | 0 | 0 | |
| Urology | 216 | 114 | 53 | 102 | 47 | |
| Operative time * | .40 | |||||
| <60 minutes | 172 | 79 | 46 | 93 | 54 | |
| 60 to100 minutes | 79 | 79 | 47 | 89 | 53 | |
| >100 minutes | 180 | 180 | 52 | 169 | 48 | |
| Postoperative admission immediately after the index surgery | .38 | |||||
| No | 344 | 163 | 47 | 181 | 53 | |
| Yes | 345 | 175 | 51 | 170 | 49 | |
Defined as the time from first incision to when the patient left the room.
Post-operative antibiotic-resistant infections
Urine was the most common culture source, accounting for 63% of all cultures (Table 3). The most commonly cultured organisms were Escherichia coli, Enterococcus, and Klebsiella pneumoniae. Among antibiotic classes, resistance was most often observed for penicillins, cephalosporins, and fluoroquinolones. Among organisms, high rates of resistance were seen within Enterococcus (72% of cultures showing resistance within ≥1 antibiotic class), Proteus mirabilis (70%), and E. coli (67%) (Supplementary Table 4).
Table 3.
Postoperative Culture Results
| Characteristic | Total | |
|---|---|---|
| n | % | |
| Source | ||
| Blood | 75 | 11 |
| Respiratory | 30 | 4 |
| Urine | 432 | 63 |
| Wound | 67 | 10 |
| Tissue/other fluid | 85 | 12 |
| Organism | ||
| Acinetobacter | 8 | 1 |
| Escherichia coli | 172 | 25 |
| Enterobacter | 38 | 6 |
| Enterococcus | 128 | 19 |
| Klebsiella pneumoniae | 72 | 10 |
| Proteus mirabilis | 27 | 4 |
| Pseudomonas aeruginosa | 37 | 5 |
| Staphylococcus Aureus | 52 | 8 |
| Staphylococcus Epidermidis | 21 | 3 |
| Staphylococcus (coagulase negative) | 71 | 10 |
| Stenotrophomonas | 2 | 0 |
| Streptococcus Pneumoniae | 38 | 6 |
| Streptococcus (Group B) | 37 | 5 |
| Resistance pattern | ||
| Amikacin | 4 | 1 |
| Aminoglycosides | 42 | 6 |
| Carbapenems | 6 | 1 |
| Cephalosporins (1st or 2nd generation) | 95 | 14 |
| Cephalopsporins (3rd or 4th generation) | 47 | 7 |
| Glycopeptides | 15 | 2 |
| Fluoroquinolones | 109 | 16 |
| Lincosamides | 17 | 2 |
| Macrolides | 40 | 6 |
| Monobactams | 30 | 4 |
| Nitroimidazoles | 32 | 5 |
| Penicillins | 160 | 23 |
| Penicillins/β-lactamase inhibitors | 99 | 14 |
| Polymixin | 2 | 0 |
| Sulfa-based | 91 | 13 |
| Rifamycins | 2 | 0 |
| Tetracyclines | 71 | 10 |
Multivariable analysis
There was no difference in the rates of antibiotic resistance when we compared those who did versus those who did not receive surgical antibiotic prophylaxis (49% vs 47% respectively, p=0.68). In the final multivariable model, there was also no difference based on SAP after adjusting for potential confounders (OR 0.99, 95% CI 0.67–1.46, Table 4). The occurrence of a prior antibiotic resistant infection was the key predictor of a post-operative antibiotic resistant infection (OR 1.81, 95% CI 1.16–2.83).
Table 4.
Multivariable Model for Risk for Postoperative Antibiotic-Resistant Compared to Antibiotic-Sensitive Infection
| Characteristic | Subjects with resistant infections/total exposed | Odds ratio (95% CI) | |
|---|---|---|---|
| n | % | ||
| Surgical antibiotic prophylaxis | |||
| No, N=139 | 66 | 47 | Reference |
| Yes, N=550 | 272 | 49 | 0.99 (0.67–1.46) |
| Prior exposure to antibiotics * | |||
| No, N=526 | 258 | 49 | Reference |
| Yes, N=163 | 80 | 49 | 0.90 (0.62–1.31) |
| Prior culture-proven infection* | |||
| None, N=487 | 231 | 47 | Reference |
| Sensitive, N=94 | 42 | 45 | 0.95 (0.60–1.50) |
| Resistant ≥1 antibiotic class, N=108 | 65 | 60 | 1.81 (1.16–2.83) |
| Operative time† | |||
| <60 minutes, N=172 | 79 | 46 | Reference |
| 60 to 100 minutes, N=168 | 79 | 47 | 1.05 (0.68–1.62) |
| >100 minutes, N=349 | 180 | 52 | 1.31 (0.89–1.93) |
Within the 90 days preceding surgery
Defined as the time from first incision to when the patient left the room.
Sensitivity analyses
We performed several tests to explore the robustness of our results. There was no change in the main result when the definition of surgical antibiotic prophylaxis was extended to include antibiotics received within 4 hours before first incision or during the operation (OR 0.94, 95% CI 0.63–1.40). There was also no change when the follow-up window was narrowed to 14 days (OR 0.82, 95% CI 0.50–1.34) or when the definition of resistant infections was narrowed to include only infections with resistance in ≥3 antibiotic classes (OR 1.53, 95% CI 0.90–2.60). There was no evidence of class-specific antibiotic resistance within the most-used antibiotic classes including cephalosporins (p=0.15), piperacillin-tazobactam (p=0.85), and vancomycin p=0.50). The relationship between SAP and resistant infections was unchanged when duration of prior hospitalization was organized into tertiles and included in the final model (OR 0.99, 95% CI 0.67–1.47). There was no change in the relationship of interest after excluding general surgical procedures (OR 1.07, 95% CI 0.67–1.69), or after excluding urological procedures (OR 0.98, 95% CI 0.61–1.56), or within the stratum of only urological or gynecological procedures (1.30, 95% CI 0.72–2.35). There was also no change after excluding cultures growing coagulase-negative Staphylococcus (OR 1.05, 95% CI 0.70–1.59). Finally, because many of the infections were urinary, we examined data related to the placement of indwelling urinary catheters. Again, no changes in the SAP-resistant infection relationship were seen when the presence or absence of an indwelling urinary catheter was included in the final model (OR 1.01, 95% CI 0.68–1.49).
DISCUSSION
In this large retrospective cohort study, use of surgical antibiotic prophylaxis was not associated with increased risk for post-operative antibiotic-resistant infection. This null finding was robust when SAP was operationalized differently, and also when the primary outcome was redefined to capture multi-drug resistant infections. There was no change in the relationship between SAP and post-operative antibiotic-resistant infection when results were stratified by type of surgical procedure, or after adjusting for known risk factors for infection such as the presence of an indwelling urinary catheter. The presence of prior antibiotic-resistant infection was the main predictor of post-operative antibiotic-resistant infection.
Previous studies have found that antibiotic use is associated with subsequent development of antibiotic resistance.(30–32) This finding is concerning because antibiotic-resistant infections are associated with increased morbidity and mortality, as well as longer and more expensive hospital stays.(9, 33) SAP is commonly used for procedures with relatively low risks for post-operative infection. If SAP is associated with even a slight increase in risk for post-operative antibiotic-resistant infections, this observation would become a significant factor in the risk-benefit equation for use of SAP. The lack of an association seen in this study provides important reassurance to surgeons who choose to use SAP for select procedures and also useful guidance for antibiotic stewardship programs seeking to minimize potentially harmful antibiotic use.
Single dose or short course antibiotics appear to have a lasting impact on the composition of the human gastrointestinal microbiome and on the development of colonization by antibiotic-resistant organisms.(34) Short course antibiotics decrease bacterial taxonomic richness and diversity within the distal gut for up to 12 months.(18, 19, 35, 36) Even single dose antibiotics seem to lead to increased rates of colonization with resistant organisms(7, 37) although there is some inconsistency between studies.(38) Notably, these studies have focused on changes in colonizing organisms rather than on the development of clinical infections with resistant pathogens. It is possible that although single dose antibiotics impact colonization with antibiotic-resistant organisms, this colonization does not develop into overt infection unless selective pressure from antibiotics is more prolonged.
The presence of a prior antibiotic-resistant infection was associated with increased risk for post-operative antibiotic-resistant infection. This is consistent with previous studies that support the utility of prior individual culture data in predicting subsequent antibiotic susceptibility patterns in both medical and Surg Infect (Larchmt).(39–41) Knowledge of an individual’s past culture data and related risk for antibiotic-resistant infection is a crucial part of appropriate antibiotic selection for a given patient.(40, 42, 43) A combined approach to SAP based on procedure-specific risks in conjunction with a patient’s own prior culture data could potentially serve to improve clinical outcomes.
Notably, the current study was restricted to patients who had culture-proven infections in the post-operative period (i.e., rates of SAP were compared in patients with antibiotic-resistant versus non-resistant infections rather than comparing rates in patients with antibiotic-resistant infections versus no infections). We believe that this approach minimizes the potential for confounding due to baseline patient differences because it eliminates loss to follow-up and ensures relative homogeneity within the population (in all patients, there was some kind of postoperative infection). Additionally, our analysis accounted for the major factors likely to influence the risk of post-operative antibiotic-resistant infection and was performed within a large cohort.
Adherence rates to guidelines for SAP are 53% to 83% depending on which aspect of guidelines are being interrogated.(44, 45) Many surgeons use SAP when it is not indicated(46, 47) and many also fail to give antibiotics when they are indicated.(45) This study focused on procedures where use of SAP is considered discretionary according to current guidelines and on procedures with low baseline rates of post-operative infections; the results should not be generalized to types of procedures that were not included in the analysis. There are other limitations to the study. Although the study was large, we cannot completely exclude the possibility that use of SAP is associated with a modest increase in post-operative antibiotic-resistant infections. We took into account a broad variety of potential confounders but we were unable to assess the potential effects of socioeconomic status or post-operative adherence to follow up recommendations. This was a single center study, and it is possible that results could differ in a different patient population or hospital environment. Finally, our approach assumes that positive culture results in post-operative patients represent clinically relevant infections. This approach was chosen to address the underlying mechanistic question: is a single dose of SAP sufficient to cause antibiotic resistance? Alternative approaches should be considered in future studies.
CONCLUSIONS
Use of surgical antibiotic prophylaxis for low-risk procedures was not associated with risk for post-operative antibiotic-resistant infection in this large retrospective cohort of patients with post-operative infections. There was no association between SAP and antibiotic-resistant infection risk in multiple sensitivity analyses. A history of prior antibiotic-resistant infection was the main predictor of post-operative antibiotic-resistant infection risk. When SAP is used in patients with this history, antibiotics should be selected based on prior culture results. Such patients may also merit closer post-operative monitoring for infection. Fear of antibiotic resistance should not drive the decision whether or not to use SAP.
Supplementary Material
Footnotes
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