A set of training materials for professionals working in intervention epidemiology, public health microbiology and infection control and hospital hygiene.
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A Surgical Site Infection (SSI) is an infection that occurs after surgery in the part of the body where the surgery took place. Surgical site infections are superficial when the skin only is involved. Deep SSI are more serious since they involve tissues under the skin, organs, or implanted material.
2. Burden of disease.
SSIs represent 17% of all healthcare associated infections (HAIs) and are the third most common HAIs in acute care hospitals in Europe according to the ECDCs annual report from 2008. The prevalence varies according to procedure and body site and prevalence figures should be stratified accordingly. Surgical procedures can be divided into three groups in terms of the risk of developing SSI; clean surgery (i.e. cardiac, orthopaedic), clean-contaminated surgery (i.e. urogenital, cholecystectomy) and contaminated surgery (i.e. colon surgery). The estimated overall incidence of SSI is 2%-5% and figures are higher for contaminated procedures.
SSIs are associated with longer post-operative hospital stays up to 7-10 days, additional surgical procedures, prolonged antibiotic treatment and increased readmission rates. SSIs may require intensive care and often result in higher mortality. The reported crude mortality rate after major surgery is 0.5-5%.
The attributable costs of SSI vary depending on the type of operative procedure and the type of infecting pathogen. Costs of SSI are believed to account for $3.5 billion to $10 billion annually in healthcare expenditure in the US .
3. How to prevent - specific requirements.
General conditions must be met to prevent HAIs described elsewhere regarding education, surveillance and infrastructure. It has been shown that 55% of SSIs are preventable when evidence-based guidelines are followed .
Deep SSIs are caused by bacteria inoculated into the wound during surgery and originate either from the patient (endogenously) or from the operating team (exogenously). The most common pathogens in deep SSIs are skin flora (Coagulase-negative staphylococci, Staphylococcus aureus) and gut flora (Enterobacteriaceae and Enterococcus spp). The risk of SSI increases with the number of bacteria and the virulence of the bacteria inoculated in the wound and depends on the immune status of the patient. Antibiotic prophylaxis administered in the right dose and the right timing has been standard practice for any surgical procedures because evidence shows that it prevents SSI and mortality. The efficacy of prophylaxis is affected by antibiotic resistance and recent studies show that 39% to 51% of bacteria that cause infections after surgery are already resistant to standard antibiotics in the US . In a world without efficient antibiotics for prophylaxis and for treating SSI the main goal for surgeons must be to focus on optimizing the patient before surgery and infection control interventions to prevent SSI. There is a substantial evidence base for preventing SSI compiled by the WHO , and SHEA-IDSA in the United states . It is estimated that SSI are preventable by 40%–60% if adequate measures are undertaken systematically since SSI are multifactorial and several actions must be undertaken simultaneously. The outcome of SSI is dependent on surgical techniques and standardized operating procedures meaning that surgeons and intraoperative staff must be well educated, take a leading role and be the experts in the hard work of preventing SSI.
Interventions to prevent SSI can be divided into preoperative, intraoperative and postoperative. The following are the most important:
– consider medical factors influencing the immune system of the patient and eliminate known risk factors for SSI: i.e. stop smoking, optimize nutritional status, blood glucose if diabetes mellitus, optimize medication for COPD and heart failure, review medication list and exclude immunosuppressing drugs if possible, ensure a BMI<30 if possible before surgery;
– treat remote infections before surgery;
– administer antibiotic prophylaxis with optimal timing and adequate dosing according to evidence-based standards and guidelines;
– treat patient skin with soap or chlorhexidine combined with alcohol repeatedly;
– remove hair when necessary using clippers;
– wash and disinfect hands of operating team optimally;
– use the WHO checklist before start of operation .
– the operating team should wear clean air suits, gloves, masks, caps and waterproof gowns according to EN-standards;
– the surgeon should use double gloves and all persons present in the operating room should wear helmets, masks and clean air suits if clean surgery;
– ensure the discipline in the operating room by minimizing movements, door openings and persons present;
– optimal ventilation adapted for the procedure and risk of SSI. High flow ventilation and low air counts for clean surgery. Do not block the ventilation;
– ensure that all instruments and equipment are adequately cleaned, disinfected and sterilized;
– ensure the patient is normothermic with proper tissue levels of oxygen and blood-glucose throughout the operation.
– ensure optimal closure of wounds;
– use drainage with closed system and removed it <24 hours;
– leave wound dressing unchanged on as long as possible;
– adequate cleaning of the operating theatre between patients.
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Sabrina Bacci posted on 10/8/2010 11:30:52 AM:
Dear Naomi, the chapter is well done and I see that you have already have incorporated some of my comments.I would like to point out that in the future, the section on "stratified analysis" should be linked to a bigger chapter, name as " Data analysis" or something like that. Maybe it could part of the Multivariate analysis chapter which Fernando has suggested to create in a future step of the wiki project. I also think that in a future step of the project this section on stratified analysis should incorporate a specific example.
Naomi Boxall replied on 10/8/2010 11:42:24 AM:
Thanks loads for going through it, Sabrina, your suggestions were very welcome.
I totally agree with you on the chapter about Data Analysis/Multivariable analysis chapter; i felt that this was missing each time I wanted to link onto how you really (truly) deal with confounding when you have more than two variables that might be confounding, for instance.
I would like to see, in a future revision, perhaps a complete case study of an example that shows many bits and pieces: almost like the Dollis Hill case study - with a case-control part, a cohort part etc. which links into all of these problems.
Not that i'm volunteering, mind! :)
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