Antibiotic prophylaxis for the prevention of Methicillin resistant Staphylococcus aureus (MRSA) infections and related complications in surgical patients
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
To compare the benefits and harms of all methods of antibiotic prophylaxis in the prevention of MRSA infection and related complications in patients undergoing surgery.
Background
Description of the condition
Methicillin‐resistant Staphylococcus aureus (MRSA) was first discovered in 1961 (Barber 1961; Jevons 1961; Knox 1961) and outbreaks have been reported since the 1970s (Klimek 1976; O'Toole 1970). MRSA infection is associated with significant mortality and morbidity. In the European Union member states, Norway, and Iceland, MRSA infections cause an estimated one million extra hospital stays and cost an estimated 600 million euros (ECDC 2009a). In the USA, an estimated 125,000 hospitalisations occur each year in relation to MRSA infections (Kuehnert 2005). While there has been a decrease in the incidence of MRSA in some countries such as the USA (Kallen 2010), probably because of measures to combat MRSA infections (ECDC 2009b), there has been an increase in the incidence of MRSA infections in Nordic countries (Skov 2005). Methicillin (meticillin is the International Nonproprietary Name) resistance is a marker of resistance to beta‐lactam antibiotics (Otter 2011) (penicillin and the cephalosporin group of antibiotics which are some of the most commonly used antibiotics in the community). In addition to beta‐lactam antibiotics, MRSA may be resistant to many other commonly used antibiotics such as erythromycin, clindamycin, gentamycin, ciprofloxacin, and fusidic acid (Otter 2011). So, even though methicillin is not a commonly used antibiotic itself, methicillin resistance indicates resistance to a wide range of antibiotics. There are currently concerns that farm animals may become reservoirs and a source of a major epidemic of MRSA in the community (Wulf 2008).
The incidence of MRSA infection after surgery is usually low but can be up to 33% in certain types of surgery such as pancreatic surgeries (pancreatoduodenectomies) (Sanjay 2010). Post‐operative MRSA infection can present as surgical site infections (SSI), chest infections, or blood stream infections (bacteraemia) (Fraser 2010; Reddy 2007; Sanjay 2010). Nosocomial (hospital‐acquired) MRSA transmission is believed to be due to cross‐contamination from healthcare workers whose hands become transiently colonised while performing patient care activities on patients colonized or infected with MRSA (Boyce 1994). Healthcare workers who are persistent nasal carriers of MRSA (carry MRSA without suffering from infection) may also act as the source of infection with MRSA (Boyce 1994). Air borne transmission is generally not considered to be a mode of transmission of MRSA. Large burn wounds in patients colonized or infected with MRSA may be reservoirs of MRSA (Boyce 1994).
The Centers for Disease Control and Prevention (CDC) criteria for surgical site infections, published by Horan et al (Horan 1992), provide definitions of nosocomial surgical site infections. Interested readers may refer to this document for definitions but broadly speaking, infections confined to skin and subcutaneous tissues are superficial surgical site infections; those involving the fascia and muscles are deep surgical site infections; and those involving organs or spaces other than the incision are organ space surgical site infections (Horan 1992). The incidence of MRSA surgical site infections in developed countries varies between 1% to 25% (Harbarth 2008a; Reddy 2007; Ridgeway 2005; Sanjay 2010; Shukla 2009) depending upon type of surgery and the carrier status of the individual (i.e. whether MRSA colonisation was present prior to the surgery). The role of universal MRSA screening and contact precautions in hospitalised patients is controversial. Guidelines published by the Society for Healthcare Epidemiology of America (SHEA) recommend routine screening and contact precautions (Muto 2003); others suggest that MRSA screening targeted at patients at high risk of MRSA colonisation such as those requiring intensive care, patients with chronic wounds, and nursing home residents is more cost‐effective than universal MRSA screening (Creamer 2011; Kang 2012); others suggest that the contact precautions are not necessary for decreasing MRSA infection rate provided that the patients are isolated after screening (Spence 2011); yet others suggest that MRSA screening is not effective in decreasing MRSA surgical site infections (Harbarth 2008b). The risk factors other than the type of surgery and carrier status of the individual include emergency surgery, prolonged duration of surgery, contaminated surgery, immunosuppression, and the presence of co‐morbidities such as diabetes mellitus, renal insufficiency, and ischaemic disease (Harbarth 2008a). MRSA surgical site infections are associated with increased mortality in patients undergoing cardiac surgery such as coronary artery bypass graft surgery and cardiac valve surgery (Reddy 2007). Cardiac surgical patients with MRSA surgical site infections had an in‐hospital mortality of 12.9% compared with an in‐hospital mortality of 3% in uninfected cardiac surgery patients (Reddy 2007). In patients undergoing vascular surgery such as aortic aneurysm repair, carotid endarterectomy, and vascular bypass procedures, the presence of MRSA infection resulted in a four‐fold increase in the in‐hospital mortality (Cowie 2005). Patients who developed MRSA infections also stayed longer in hospitals than those who did not develop MRSA infections (Chemaly 2010; Cowie 2005; Fraser 2010; Sanjay 2010; Shukla 2009).
The incidence of post‐operative MRSA infection can vary with the type of surgery; such infection is usually rare but chest infections can be found in up to 15% in pancreatic surgeries (Sanjay 2010) and can result in bacteraemia in up to 5% of patients in pancreatic surgeries (Sanjay 2010). MRSA bacteraemia is associated with a 30‐day mortality of about 28% to 38% (Lamagni 2011; Lewis 2011; Wang 2010) and a one‐year mortality of about 55% (Kaye 2008).
Description of the intervention
The Oxford English Dictionary defines an antibiotic substance as one of a class of substances produced by living organisms and capable of destroying or inhibiting the growth of micro‐organisms especially used for therapeutic purposes. Synthetic organic compounds having similar properties are also called antibiotics (OED 2011). Various antibiotics such as beta‐lactam (penicillin derivatives, cephalosporins),glycopeptide antibiotics (such as vancomycin, teicoplanin), clindamycin, trimethoprim‐sulfamethoxazole (TMP‐SMX), a tetracycline (doxycycline or minocycline), linezolid, daptomycin, telavancin, rifampicin, gentamycin, fluoroquinolone all work against MRSA (Liu 2011). Different antibiotics are administered in different ways with the common routes being oral, intravenous, and topical administration (Liu 2011). Antibiotics can be given as a single agent or in combinations (Liu 2011). Antibiotics can be given preoperatively, during the operation, post‐operatively, or a combination of the above. The antibiotics are usually started just before surgery and can vary between a single dose or multiple doses for a short period of time after the surgery (Saginur 2000).
How the intervention might work
The mechanisms of action vary for different types of antibiotic but in general terms they either destroy the MRSA or prevent cell division (which prevents reproduction and hence multiplication in numbers). The intervention might decrease the complications related to MRSA infection by preventing MRSA infection. As described above, complications related to MRSA infection include mortality and serious adverse events such as bacteraemia, chest infection; such outcomes are important in terms of clinical decision making (Fraser 2010; Reddy 2007; Sanjay 2010). Incidence of MRSA infection is considered as an intermediate outcome which might influence the mortality and serious adverse events and might inform clinical management.
Why it is important to do this review
One systematic review found that glycopeptide antibiotics (such as vancomycin and teicoplanin) did not influence surgical site infection rates compared with non‐glycopeptide antibiotics (Chambers 2010). This is just of one of the comparisons included in this review. There has been no systematic review comparing other antibiotics. Loeb et al compared the use of different anti‐microbial treatments in people colonized with MRSA either nasally or at extra‐nasal sites and concluded that there was insufficient evidence to support use of topical or systemic antimicrobial therapy for eradicating nasal or extra‐nasal MRSA (Loeb 2003).There has been no systematic review or Cochrane reviews comparing the various antibiotics, other than the comparison between vancomycin and teicoplanin by Chambers 2010, in the prevention of MRSA infection and subsequent complications in patients undergoing surgery. Such a review will be a useful guide for microbiologists, surgeons, and policy makers.
Objectives
To compare the benefits and harms of all methods of antibiotic prophylaxis in the prevention of MRSA infection and related complications in patients undergoing surgery.
Methods
Criteria for considering studies for this review
Types of studies
We will include randomised controlled trials (RCTs), irrespective of blinding, language, publication status, date of publication, study setting, sample size, or whether the incidence of MRSA infection was the primary outcome of the trial. We will exclude cluster RCTs. No other study designs (i.e. quasi‐randomised studies and non‐randomised studies) will be included.
Types of participants
Patients undergoing surgery, irrespective of age, type of surgery, whether surgery was elective or emergency in nature, and whether MRSA colonisation was identified by routine screening (in general, we expect that if MRSA colonisation was identified, MRSA will be eradicated before the surgery). We will exclude studies recruiting patients with established MRSA surgical site infections as these will be covered in another review (Gurusamy 2012).
Types of interventions
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Comparison of antibiotic treatment (irrespective of the antibiotic) compared with placebo (or no treatment).
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Comparison of different antibiotic treatment (and regimens).
We will include studies evaluating a combination of antibiotics in terms of the combined regimen rather than as single antibiotics.
Types of outcome measures
Primary outcomes
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All‐cause mortality at maximal follow‐up.
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Other serious adverse events (defined as any event that is life‐threatening; requires inpatient hospitalisation; results in a persistent or significant disability; or any important medical event which might have jeopardised the patient or requires intervention to prevent it (ICH‐GCP 1996) e.g., rates of bacteraemia, other MRSA complications) at maximal follow‐up due to surgery or MRSA infection or due to the use of antibiotics. Mild adverse events are unlikely to determine the clinical management if there is a significant difference in the primary outcomes or one of the secondary outcomes.
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Quality of life (at maximal follow‐up).
Secondary outcomes
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Total length of hospital stay (at maximal follow‐up due to surgery or MRSA infection).
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Use of health care resources (e.g., hospital visits at maximal follow‐up due to surgery or MRSA infection).
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Rates of surgical site infections (due to all organisms) within 30 days of surgery.
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Rates of surgical site infections due to MRSA within 30 days of surgery.
Search methods for identification of studies
Electronic searches
We will search the following electronic databases to identify reports of relevant randomised clinical trials:
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The Cochrane Wounds Group Specialised Register;
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The Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library) (Latest issue);
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Database of Abstracts of Reviews of Effects (DARE)(The Cochrane Library) (Latest issue);
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NHS Economic Evaluation Database (The Cochrane Library) (Latest issue);
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Health Technology Assessment (HTA) Database (The Cochrane Library) (Latest issue);
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Ovid MEDLINE (1948 to present);
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Ovid EMBASE (1974 to present);
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EBSCO CINAHL (1982 to present)
We will use the following search strategy in The Cochrane Central Register of Controlled Trials (CENTRAL):
#1 MeSH descriptor Methicillin Resistance explode all trees
#2 MeSH descriptor Staphylococcal Infections explode all trees
#3 MeSH descriptor Staphylococcus aureus explode all trees
#4 (#2 OR #3)
#5 (#1 AND #4)
#6 MeSH descriptor Methicillin‐Resistant Staphylococcus aureus
explode all trees
#7 (methicillin NEXT resistan*) or (meticillin NEXT resistan*) or MRSA
#8 (#5 OR #6 OR #7)
#9 MeSH descriptor Wound Infection explode all trees
#10 MeSH descriptor Sepsis explode all trees
#11 MeSH descriptor Soft Tissue Infections explode all trees
#12 MeSH descriptor Surgical Wound Dehiscence explode all trees
#13 surg* NEAR/5 infect*
#14 surg* NEAR/5 wound*
#15 surg* NEAR/5 site*
#16 surg* NEAR/5 incision*
#17 surg* NEAR/5 dehisc*
#18 wound* NEAR/5 dehisc*
#19 (deep NEXT infection*) or "deep sepsis" or (infected NEXT
collection*)
#20 (#9 OR #10 OR #11 OR #12 OR #13 OR #14 OR #15 OR #16 OR #17 OR
#18 OR #19)
#21 MeSH descriptor Anti‐Bacterial Agents explode all trees
#22 MeSH descriptor Cephalosporins explode all trees
#23 MeSH descriptor Tetracycline explode all trees
#24 MeSH descriptor Penicillins explode all trees
#25 antibiotic* or penicillin* or beta‐lactam* or cephalosporin* or
clindamycin or trimethoprim* or tetracycline* or doxycycline or minocycline or linezolid or vancomycin or daptomycin or telavancin or rifampicin or gentamycin or gentamicin or fluoroquinolone
#26 (#21 OR #22 OR #23 OR #24 OR #25)
#27 (#8 AND #20 AND #26)
We will adapt this strategy to search Ovid MEDLINE, Ovid EMBASE and EBSCO CINAHL. We will combine the Ovid MEDLINE search with the Cochrane Highly Sensitive Search Strategy for identifying randomised trials in MEDLINE: sensitivity‐ and precision‐maximising version (2008 revision) (Lefebvre 2011). We will combine the EMBASE search with the Ovid EMBASE filter developed by the UK Cochrane Centre (Lefebvre 2011). We will combine the CINAHL searches with the trial filters developed by the Scottish Intercollegiate Guidelines Network (SIGN 2011). We will not restrict studies with respect to language, date of publication or study setting.
We will search the metaRegister of Controlled Trials (mRCT) (http://www.controlled‐trials.com/mrct/) which includes the ISRCTN Register and the NIH ClinicalTrials.gov Register among others. We will also search the World Health Organizations International Clinical Trials Registry Platform (ICTRP) (http://apps.who.int/trialsearch/). The ICRTP portal includes national trial registry databases from a number of countries.
Searching other resources
We will search the references of identified trials to identify further relevant trials. We will also contact experts in MRSA infection to identify further trials.
Data collection and analysis
We will perform the systematic review following the instructions given in the Cochrane Handbook for Systematic Reviews of Intervention (Higgins 2011a).
Selection of studies
Two review authors (KG and another review author) will identify the trials for inclusion independently of each other. We will list the excluded studies with the reasons for the exclusion. Any differences will be resolved through discussion.
Data extraction and management
Both review authors will independently extract the following data.
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Year and language of publication.
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Country.
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Year in which trial was conducted.
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Inclusion and exclusion criteria.
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Sample size.
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Type of surgery.
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Details of antibiotic treatment including dose, route, frequency, and duration.
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Outcomes (described above).
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Risk of bias (described below).
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Source of funding.
We will obtain the information from all the reports if multiple reports exist for a trial. We will seek any unclear or missing information contacting the authors of the individual trials. If there is any doubt whether the trials share the same patients, completely or partially (by identifying common authors and centres), we will contact the study authors to clarify whether the trial report has been duplicated. We will resolve any differences in opinion through discussion.
Assessment of risk of bias in included studies
We will follow the instructions given in the Cochrane Handbook for Systematic Reviews of Intervention (Higgins 2011b). According to empirical evidence (Kjaergard 2001; Moher 1998; Schulz 1995; Wood 2008), the risk of bias of the trials will be assessed based on the following bias risk domains.
Sequence generation
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Low risk of bias (the methods used are either adequate (e.g., computer‐generated random numbers, table of random numbers) or unlikely to introduce confounding).
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Uncertain risk of bias ( there is insufficient information to assess whether the method used is likely to introduce confounding).
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High risk of bias (the method used (e.g., quasi‐randomised studies) is improper and likely to introduce confounding). Such studies will be excluded.
Allocation concealment
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Low risk of bias (the method used (e.g., central allocation) is unlikely to induce bias on the final observed effect).
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Uncertain risk of bias (there is insufficient information to assess whether the method used is likely to induce bias on the estimate of effect).
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High risk of bias (the method used (e.g., open random allocation schedule) is likely to induce bias on the final observed effect).
Blinding of participants, personnel
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Low risk of bias (blinding was performed adequately, or the outcome measurement is not likely to be influenced by lack of blinding).
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Uncertain risk of bias (there is insufficient information to assess whether the type of blinding used is likely to induce bias on the estimate of effect).
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High risk of bias (no blinding or incomplete blinding, and the outcome or the outcome measurement is likely to be influenced by lack of blinding).
Blinding of outcome assessors
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Low risk of bias (blinding was performed adequately, or the outcome measurement is not likely to be influenced by lack of blinding).
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Uncertain risk of bias (there is insufficient information to assess whether the type of blinding used is likely to induce bias on the estimate of effect).
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High risk of bias (no blinding or incomplete blinding, and the outcome or the outcome measurement is likely to be influenced by lack of blinding).
Incomplete outcome data
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Low risk of bias (the underlying reasons for missingness are unlikely to make treatment effects depart from plausible values, or proper methods have been employed to handle missing data).
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Uncertain risk of bias (there is insufficient information to assess whether the missing data mechanism in combination with the method used to handle missing data is likely to induce bias on the estimate of effect).
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High risk of bias (the crude estimate of effects (e.g., complete case estimate) will clearly be biased due to the underlying reasons for missingness, and the methods used to handle missing data are unsatisfactory).
Selective outcome reporting
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Low risk of bias (the trial protocol is available and all of the trial's pre‐specified outcomes that are of interest in the review have been reported or similar; if the trial protocol is not available, all the primary outcomes in this review are reported).
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Uncertain risk of bias (there is insufficient information to assess whether the magnitude and direction of the observed effect is related to selective outcome reporting).
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High risk of bias (not all of the trial's pre‐specified primary outcomes have been reported or similar).
We will consider trials that are classified as low risk of bias in all the above domains as low bias‐risk trials.
Measures of treatment effect
For dichotomous variables, we will calculate the risk ratio (RR) with 95% confidence interval (CI). For continuous variables, we will calculate the mean difference (MD) with 95% CI for outcomes such as hospital stay and standardised mean difference (SMD) with 95% CI for quality of life (where different scales might be used). For time‐to‐event outcomes such as survival at maximal follow‐up, we will calculate the hazard ratio (HR) with 95% CI.
Unit of analysis issues
The unit of analysis will be individual patients undergoing surgical procedures. We do anticipate many patients undergoing a second operation during the same admission within the trial. However, if we found any patients undergoing such second surgery and provided that they do not have MRSA infection before the second surgery, each surgery will be considered as a separate unit of analysis.
Dealing with missing data
We will perform an intention‐to‐treat analysis (Newell 1992) whenever possible. We will impute missing data for binary outcomes using various scenarios such as good outcome analysis, bad outcome analysis, best‐case scenario, and worst‐case scenario (Gurusamy 2009).
For continuous outcomes, we will use available‐case analysis. We will impute the standard deviation from P values according to the instructions given in the Cochrane Handbook for Systematic Reviews of Intervention (Higgins 2011c), and we will use the median for the meta‐analysis when the mean is not available. If it is not possible to calculate the standard deviation from the P value or the CIs, we will impute the standard deviation as the highest standard deviation in the other trials included under that outcome, fully recognising that this form of imputation will decrease the weight of the study for calculation of MD and bias the effect estimate to no effect in case of SMD (Higgins 2011c).
For time‐to‐event outcomes, if the HR and 95% CIs are not reported, we will obtain the logarithm of hazard ratios (ln(HR)) and the standard error (SE) of ln(HR) according to the methods described by Parmar 1998 using the Excel sheet provided by Tierney 2007.
Assessment of heterogeneity
We will explore heterogeneity by Chi2 test with significance set at P value 0.10, and measure the quantity of heterogeneity by I2 (Higgins 2002). We will also use overlapping of CIs on the forest plot to determine heterogeneity.
Assessment of reporting biases
We will use visual asymmetry on a funnel plot to explore reporting bias (Egger 1997; Macaskill 2001). We will perform the linear regression approach described by Egger 1997 to determine the funnel plot asymmetry. Selective reporting will also be considered as evidence of reporting bias.
Data synthesis
For the comparison of antibiotic versus placebo (or no intervention), we will perform the meta‐analysis only if there is sufficient clinical homogeneity in terms of patients included in the trials. This will be based on our clinical judgement. For the comparison of different antibiotics, we will perform the meta‐analysis only if there is sufficient clinical homogeneity in terms of patients included in the trials and in terms of antibiotics used (i.e., similar class of antibiotics). We will perform the meta‐analyses using the software package RevMan 5 (RevMan 2011) and following the recommendations of The Cochrane Collaboration (Higgins 2011a). We will use both a random‐effects model (DerSimonian 1986) and a fixed‐effect model (DeMets 1987) for the meta‐analyses. In case of discrepancy between the two models identified from the pooled estimates and their CIs, we will report both results; otherwise we will report the results of the fixed‐effect model. With regards to dichotomous outcomes, risk ratio (RR) calculations do not include trials in which no events occurred in either group in the meta‐analysis, whereas risk difference (RD) calculations do. We will report the RD if the results using this association measure are different from RR. However, RR is the measure that we will use to arrive at conclusions, since RRs perform better when there are differences in the control event rate (proportion of patients who develop the event in the control). We will use the generic inverse variance method to combine the HRs for time‐to‐event outcomes.
Subgroup analysis and investigation of heterogeneity
We will perform the following subgroup analyses.
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Different antibiotics (or class of antibiotics).
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Different doses and durations of antibiotics.
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Different types of surgery.
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Different patient characteristics (presence of systemic illness such as diabetes or other immunocompromised individual).
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Patients routinely screened and treated versus those who were not routinely screened.
We will use a P value of less than 0.05 for the Chi2 test to identify the differences between subgroups and to investigate whether heterogeneity in effect estimates are because of the differences in the above characteristics.
Sensitivity analysis
We will perform a sensitivity analysis by imputing data for binary outcomes using various scenarios such as good outcome analysis, bad outcome analysis, best‐case scenario, and worst‐case scenario (Gurusamy 2009). We will perform a sensitivity analysis by testing the effect of removing trials at unclear or high risk of bias and excluding the trials in which the mean and the standard deviation were imputed.
Presentation of results
We will present the main results of the review in summary of findings tables, which provide key information concerning the quality of evidence, the magnitude of effect of the interventions examined, and the sum of available data on the main outcomes, as recommended by the Cochrane Collaboration (Schunemann 2011a). We plan to include the following in the summary of findings tables:
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All‐cause mortality;
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Serious adverse events;
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Quality of life;
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Rates of surgical site infections due to MRSA within 30 days of surgery;
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Rates of surgical site infections due to all organisms within 30 days of surgery;
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Total length of hospital stay;
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Use of health care resources.
The summary of findings table includes an overall grading of the evidence related to each of the main outcomes, using the GRADE approach (Schunemann 2011b).
