Surgical Site Infection Surveillance Research Articles

A comparison of surgical site infections following total hip replacement and total knee replacement surgeries identified by Infection Prevention and Control and the National Surgical Quality Improvement Program in Alberta, Canada.

To understand how the different data collections methods of the Alberta Health Services Infection Prevention and Control Program (IPC) and the National Surgical Quality Improvement Program (NSQIP) are affecting reported rates of surgical site infections (SSIs) following total hip replacements (THRs) and total knee replacements (TKRs). Retrospective cohort study. Four hospitals in Alberta, Canada. Those with THR or TKR surgeries between September 1, 2015, and March 31, 2018. Demographic information, complex SSIs reported by IPC and NSQIP were compared and then IPC and NSQIP data were matched with percent agreement and Cohen's κ calculated. Statistical analysis was performed for age, gender and complex SSIs. A P value <.05 was considered significant. In total, 7,549 IPC and 2,037 NSQIP patients were compared. The complex SSI rate for NSQIP was higher compared to IPC (THR: 1.19 vs 0.68 [P = .147]; TKR: 0.92 vs 0.80 [P = .682]). After matching, 7 SSIs were identified by both IPC and NSQIP; 3 were identified only by IPC, and 12 were identified only by NSQIP (positive agreement, 0.48; negative agreement, 1.0; κ = 0.48). Different approaches to monitor SSIs may lead to different results and trending patterns. NSQIP reports total SSI rates that are consistently higher than IPC. If systems are compared at any point in time, confidence on the data may be eroded. Stakeholders need to be aware of these variations and education provided to facilitate an understanding of differences and a consistent approach to SSI surveillance monitoring over time.

Surveillance of surgical site infections: methodical comparison of the IQTIG and KISS strategies.

Aim: In 2017, the Institute for Quality Assurance and Transparency in Healthcare (IQTIG) introduced a quality assurance system for the surveillance of surgical site infections (SSI) on behalf the Federal Joint Committee. The establishment of the new system was made in parallel to existing methods, such as the “Krankenhaus-Infektions-Surveillance-System” (KISS). The aim of this work was to perform a comparative analysis.Methods: All 2,233 cases at the University Medical Center Goettingen requiring an assessment of the presence of SSI as part of the IQTIG procedure in 2018 and 2019 were evaluated retrospectively according to the KISS protocol.Results: In total, 2,050 patients were included in the comparative evaluation. Overall, 1,779 (79.7%) had a surgical anamnesis (surgery during the stay or in the past), and 1,716 (83.7%) showed identical results for both surveillance strategies. Different results were found for 334 patients (16.3%), with 160 of these (7.8%) positive for SSI according to IQTIG and 174 (8.5%) positive for KISS. Risk factors were identified for a discordant assessment between the methods. Conclusion: The congruence of the two strategies was consistently high over the study period. There is evidence that the efficiency of the documentation algorithm can be increased without the loss of documentation of SSI, while preserving the precision of the documentation through training.

Improving surgical site infection prevention in Asia-Pacific through appropriate surveillance programs: Challenges and recommendation.

Surgical site infections (SSIs) represent a substantial clinical and economic burden on patients and the healthcare system. The prevention of SSIs entails surveillance activities which lead to effective mitigation strategies, which are lacking across Asia Pacific (APAC). This manuscript aims to document gaps and challenges across APAC that affect the undertaking of a successful SSI surveillance activities and to provide recommendations on overcoming such challenges. A targeted literature review with relevance to APAC identified a series of salient points pertaining to SSI prevention guidelines, implementation, surveillance and outcomes, which was discussed in July 2019at the APAC Surgical Site Infection Prevention Symposium. An expert panel, comprising eight multidisciplinary experts from APAC and the USA, subsequently amalgamated the key discussion points from the Symposium and their clinical experiences in developing this article. The barriers to implementing a successful and effective APAC SSI surveillance program were identified as: (a) lack of standardized definitions, reporting methodology and accountability, (b) lack of fiscal resources, (c) reporting variability and under-reporting, and (d) lack of safety culture. Implementing an effective surveillance program in APAC will require countries to develop a well-designed and robust surveillance plan and ensure adequate training for staffs involved. To improve SSI prevention in the region, it is imperative to encourage implementation of national programs with standardized methodologies and accountabilities. An ongoing APAC information exchange, including data and methodologies, will enable continuous learning within the APAC region.

Risk factors for surgical site infection associated with clean surgical procedures in dogs

Surgical site infection (SSI) is associated with increased morbidity, cost and mortality in human medicine and with increased morbidity and cost in veterinary medicine. The aim of this study was to evaluate risk factors for SSI development after clean surgical procedures in dogs, treated at both first opinion clinics as well as referral hospitals.1550 dogs scored 1 or 2 according to the American Society of Anesthesiologists (ASA), that underwent clean surgical procedures at 103 clinics located in Northern and Central Europe were included in the study. Data regarding the surgical procedure, surgery time use of perioperative antimicrobial prophylaxis (AMP), surgery type, intraoperative hypothermia, and the use of surgical implants were recorded according to predefined protocols. Active 30-day SSI surveillance was performed. A random effects logistic regression model was used to evaluate the association between the perioperative variables and SSI development.SSI was detected in 85/1550 dogs (5.5%); 25 occurred in the 500 orthopedic/neurosurgery procedures (5.0%), and 60 in the 1050 soft tissue procedures (5.7%). A total of 1524 dogs were included in the final multivariable model. Increased surgery time was the only variable associated with an increased risk of SSI. No association between the other risk factors evaluated in the study and SSI occurrence was detected. Efforts must therefore be made to keep the surgery time as short as possible. Orthopedic and neurosurgical procedures including those where an implant is placed should not automatically be regarded as high-risk procedures benefiting from perioperative AMP.

What gets measured gets noticed. Tracking surgical site infection post caesarean section through community surveillance: A post intervention study protocol.

This study aims to evaluate the effectiveness of HealthTracker, a surgical site infection surveillance system that aims to improve the notification of surgical site infection for women after giving birth by caesarean section. This protocol is an intervention study to evaluate the effectiveness of the surveillance system called "HealthTracker" in monitoring surgical site infections post caesarean section. This study will use a mobile web application to automatically send a text message inviting all women who give birth to a live baby by caesarean section over six months during 2020-2021, at an Australian tertiary referral hospital. The text message invites women to complete a web-based validated Wound Healing Questionnaire. The estimated number of eligible women in six months is 700 (caesarean section rate: 34% of 4,000 births annually). the proposed "HealthTracker" surveillance system facilitates active patient-reported surgical site infection identification through an automated mobile text message linking women to an individualized online Wound Healing Questionnaire. This project aims to provide a consistent, reliable and cost effective surgical site infection surveillance tool to improve post caesarean section surgical site infection reporting, can be scaled for broader utilization and will provide valuable information to decision makers regarding surgical site infection prevention. Study findings will provide insights into whether HealthTracker is an efficient and cost effective platform for a systematic and consistent approach to surgical site infection surveillance that can be adopted more broadly, across the local health organization, the State and across other surgical specialty areas. This information will equip hospitals and clinicians with knowledge to better identify patient outcomes related to SSI post discharge from hospital and inform decision making related to preventative strategies, providing the necessary momentum to introduce practice change initiatives aimed at reducing surgical site infection rates. ACTRN12620001233910.

Wound infection in colorectal cancer resections through a laparoscopic approach: a single-center prospective observational study of over 3000 cases

ObjectivesThis prospective observational study aimed to clarify the incidence and independent risk factors of wound infection after laparoscopic surgery for primary colonic and rectal cancer.MethodsA prospective surveillance of surgical site infection (SSI) was conducted in consecutive patients with primary colorectal cancer, who underwent elective laparoscopic surgery in a single comprehensive cancer center between 2005 and 2014. The outcomes of interest were the incidence and risk factors of wound infection.ResultsIn total, 3170 patients were enrolled in the study. The overall incidence of wound infection was 3.0%. The incidence of wound infection was significantly higher in rectal surgery than in colonic surgery (4.7 vs. 2.1%, p < 0.001). In rectal surgery, independent risk factors for developing wound infection included abdominoperineal resection (p < 0.001, odds ratio [OR] = 11.4, 95% confidence interval [CI]: 5.04–24.8), body mass index (BMI) ≥ 25 kg/m2 (p = 0.041, OR = 1.97, 95% CI, 1.03–3.76), and chemoradiotherapy (p = 0.032, OR = 2.18, 95% CI, 1.07–4.45). In laparoscopic colonic surgery, no significant risk factors were identified.ConclusionsLaparoscopic rectal surgery has a higher risk of wound infection than colonic surgery. Laparoscopic rectal surgery involving abdominoperineal resection, patients with higher BMI, and chemoradiotherapy requires careful observation in wound care and countermeasures against wound infection.

Urgency of surgery as an indicator for the occurrence of surgical site infections: data from over 100,000 surgical procedures

The risk for surgical site infections (SSIs) is influenced by patient- and procedure-related factors. Urgent surgery represents a challenge in operative medicine and is frequently linked to a variety of complications, including SSIs. We aimed to investigate whether urgency was significantly associated with SSI occurrence, and determine whether collection of this variable provided useful information for SSI surveillance. We performed a retrospective data analysis of caesarean sections (C-sections) and colon surgeries conducted between 2017 and 2019 within the German national SSI surveillance network. A multivariable logistic regression model was utilized to determine the influence of urgency on SSI occurrence. For this purpose, data on procedures and SSIs were associated with available department- and patient-related parameters. A total of 115,648 procedures were included in the analysis: 78,288 C-sections and 37,360 colon surgeries. For C-sections, the SSI rate per 100 procedures was 0.98 (95% confidence interval: 0.85-1.11) for urgent and 0.46 (0.40-0.53) for elective procedures (P<0.001). For open colon surgeries, SSI rates were 9.66 (8.89-10.49) for urgent and 8.60 (8.13-9.11) for elective procedures (P<0.001). For laparoscopic colon surgeries, SSI rates did not differ significantly. Multivariable analysis revealed that urgency significantly increased the likelihood of SSI occurrence only for C-sections. Urgency significantly increased the SSI risk of C-sections, but not colon surgeries. Hence, collection of this variable is useful for SSI surveillance of C-sections, but may be dispensable for other procedures. Future analyses on the matter should therefore focus on other procedure types.

POST-DISHCARGE SURVEILLANCE IN SURGICAL SITE INFECTION: VALIDATION OF AN INSTRUMENT

ABSTRACT Objective: to create and validate an instrument for detecting potential cases of surgical site infection through post-discharge telephone surveillance. Method: a methodological study using psychometric analyzes to develop and validate an instrument for conducting post-discharge surveillance of surgical site infection. Results: the instrument had a total content validity coefficient equal to 0.87. It was applied to a sample of 100 patients and compared to a medical and nursing physical examination to detect surgical site infection, resulting in satisfactory Cohen’s kappa (0.83), Cronbach’s alpha (0.87) and Comparative Fit Index (0.998). The difference between the time spent on telephone calls for patients positive for surgical site infection was statistically greater than the time spent on calls for patients negative for surgical site infection (p &lt;0.001). Sensitivity was 76.4%, with specificity of 100%, negative predictive values of 92.5%, positive values of 100% and accuracy of 94%. Conclusion: the instrument was validated in content, criteria and constructo stages.

Usefulness of a multidisciplinary surgical site infection team in colorectal surgery.

Background : Surgical site infection (SSI) is an adverse event that places a major burden on patients and staff. In this study, we examined the occurrence of SSI and the characteristics of patients referred to the SSI team after colorectal surgery. Methods : In total, 955 patients underwent colorectal surgery at our hospital from 2014 to 2019. Of these 955 patients, 516 received therapeutic support by the SSI team from 2017 to 2019. All patients were evaluated using an SSI surveillance sheet, and we checked for reports of SSI once a month. Each attending physician performed SSI prophylaxis (use of new instruments before wound irrigation and closure). Results : SSI occurred in 80 (8.4%) patients. The incidence of SSI and the incidence of surface SSI were higher in the patients who did not receive intervention by the SSI team than in the patients who did. Organ / space SSI occurred in 18 patients. Among patients with surface SSI, Enterococcus was the most commonly detected bacteria. Among the 18 patients with organ / space SSI, 5 developed anastomotic leakage and 4 developed intra-abdominal abscesses. Conclusions : An SSI team for prevention and treatment of infection may contribute to reduction of SSI. J. Med. Invest. 68 : 256-259, August, 2021.

897. Prediction of Surgical Site Infections in Colon Surgery in Belo Horizonte Hospitals

BackgroundIn Belo Horizonte (a 3,000,000 inhabitants city) a survey was carried out in five hospitals, between July 2016 and June 2018, about surgical site infection (SSI) in patients undergoing colon surgery procedures. The general objective is to statistically evaluate such incidences and enable an analysis of the SSI predictive power, through MLP (Multilayer Perceptron) pattern recognition algorithms.MethodsThrough the Hospital Infection Control Committees (CCIH) of the hospitals a data collection on SSI was carried out. Such data was used in the analysis during your routine SSI surveillance procedures. So, three procedures were performed: a treatment of the collected database for use of intact samples; a statistical analysis on the profile of the collected hospitals and; an assessment of the predictive power of five types of MLPs (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay and Quick Propagation) for SSI prediction. The MLPs were tested with 3, 5, 7 and 10 neurons in the hidden layer and with a division of the database for the resampling process (65% or 75% for testing, 35% or 25% for validation). They were compared by measuring the AUC (Area Under the Curve - ranging from 0 to 1) presented for each of the configurations.ResultsFrom 2126 records, 638 were complete for analysis. It was found: the average age is 55 years (from 1 to 94 years); the surgeries had an average time of approximately 197 minutes; the average hospital stay is 8 days, the death rate reached 5.625% and the SSI rate reached 6%. Regarding the predictive power, a maximum predictive power of 0.8316 was found.ConclusionThere was a loss of 70% of the database samples due to the presence of noise. However, it was possible to have a relevant sample to assess the profile of these five hospitals. The predictive process presented some configurations with results that reached 0.8316, which promises the use of the structure for the monitoring of automated SSI for patients undergoing colon surgeries. To optimize data collection, enable other hospitals to use the prediction tool and minimize noise from the database, two mobile application were developed: one for monitoring the patient in the hospital and the other for monitoring after hospital discharge. The SSI prediction analysis tool is available at www.nois.org.br.Disclosures All Authors: No reported disclosures

895. Prediction of Occurrence for Surgical Site Infection in Infected Surgeries

BackgroundA survey was carried out in five hospitals, between July 2016 and June 2018, on surgical site infection (SSI) in patients undergoing infected surgery procedures, in the city of Belo Horizonte (3,000,000 inhabitants). The general objective is to statistically evaluate such incidences and enable an analysis of the SSI predictive power, through MLP (Multilayer Perceptron) pattern recognition algorithms.MethodsThrough the Hospital Infection Control Committees (CCIH) of the hospitals, a data collection on SSI was carried out. Such data is used in the analysis during your routine SSI surveillance procedures. So, three procedures were performed: a treatment of the collected database for use of intact samples; a statistical analysis on the profile of the collected hospitals and; an assessment of the predictive power of five types of MLPs (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay and Quick Propagation) for SSI prediction. The MLPs were tested with 3, 5, 7 and 10 neurons in the hidden layer and with a division of the database for the resampling process (65% or 75% for testing, 35% or 25% for validation). They were compared by measuring the AUC (Area Under the Curve - ranging from 0 to 1) presented for each of the configurations.ResultsFrom 1770 records, 810 were intact for analysis. It was found that: the average age is 53 years old (from 0 to 98 years old); the surgeries had an average time of approximately 140 minutes; the average hospital stay is 19 days, the death rate reached 10.86% and the SSI rate was 6.04%. A maximum prediction power of 0.729 was found.ConclusionThere was a loss of 54% of the database samples due to the presence of noise. However, it was possible to have a relevant sample to assess the profile of these five hospitals. The predictive process, presented some configurations with results that reached 0.729, which promises the use of the structure for the monitoring of automated SSI for patients submitted to infected surgeries. To optimize data collection, enable other hospitals to use the prediction tool and minimize noise from the database, two mobile application were developed: one for monitoring the patient in the hospital and another for monitoring after hospital discharge. The SSI prediction analysis tool is available at www.nois.org.br.Disclosures All Authors: No reported disclosures

901. Risk Prediction for Surgical Site Infection in Patients Subject to Knee Arthroplasty Surgery

BackgroundThis research represents an experiment on surgical site infection (SSI) in patients undergoing knee arthroplasty surgery procedures in hospitals in Belo Horizonte, between July 2016 and June 2018. The objective is to statistically evaluate such incidences and enable a study of the prediction power of SSI of pattern recognition algorithms, in this case the Multilayer Perceptron (MLP).MethodsData were collected on SSI in five hospitals. The Hospital Infection Control Committees (CCIH) of the hospitals involved collected all data used in the analysis during their routine SSI surveillance procedures and sent the information to the Nosocomial Infection Study Project (NOIS). Three procedures were performed: a treatment of the database collected for use of intact samples; a statistical analysis on the profile of the hospitals collected and; an assessment of the predictive power of five types of MLP (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay, and Quick Propagation) for SSI prediction. MLPs were tested with 3, 5, 7, and 10 hidden layer neurons and a database split for the resampling process (65% and 75% for testing, 35% and 25% for validation). They were compared by measuring AUC (Area Under the Curve - ranging from 0 to 1) presented for each of the configurations.ResultsFrom the 1438 data collected, 390 records were usable and it was verified: the average age of the patients who underwent this surgical procedure was 70 (ranging from 29 to 92), average surgery time was 171 minutes (between 50 and 480), 47% presented a hospital contamination, 1% SSI and no deaths. During the MLP experiments, due to the low number of SSI cases, the prediction rate for this specific surgery was 0.5.ConclusionDespite the large noise index of the database, it was possible to have a relevant sampling to evaluate the profile of hospitals in Belo Horizonte. However, for the predictive process, despite some results equal to 0.5, the database demands more samples of SSI cases, as only 1% of positive samples generated an unbalance of the database. To optimize data collection and enable other hospitals to use the SSI prediction tool (available in www.sacihweb.com), two mobile application were developed: one for monitoring the patient in the hospital and the other for monitoring after hospital discharge.Disclosures All Authors: No reported disclosures

880. Artificial Neural Networks to Predict Surgical Site Infection in Aorta Artery Aneurysm Correction

BackgroundA survey was conducted in three hospitals, between July 2016 and June 2018, about surgical site infection (SSI) in patients undergoing surgeries to correct aortic artery aneurysms in the city of Belo Horizonte, with more than 3,000,000 of inhabitants. The general objective is to statistically evaluate such incidences and enable an analysis of the predictive power of SSI, through MLP (Multilayer Perceptron) pattern recognition algorithms.MethodsThrough the Hospital Infection Control Committees (CCIH) of the hospitals involved in the research, data collection on SSI was carried out. Such data is used in the analysis during your routine SSI surveillance procedures. Thus, three procedures were performed: a treatment of the database collected for use of intact samples; a statistical analysis on the profile of the collected hospitals and; an assessment of the predictive power of five types of MLPs (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay and Quick Propagation) for SSI prediction. The MLPs were tested with 3, 5, 7 and 10 neurons in the hidden layer and with a division of the database for the resampling process (65% or 75% for testing, 35% or 25% for validation). They were compared by measuring the AUC (Area Under the Curve - ranging from 0 to 1) for each of the configurations.ResultsFrom 600 records, 575 were complete for analysis. It was found that: the average age is 68 years (from 24 to 98 years); the average hospital stay is 9 days (with a maximum of 127 days), the death rate reached 6.43% and the SSI rate 2.78%. A maximum prediction power of 0.75 was found.ConclusionThere was a loss of 4% of the database samples due to the presence of noise. It was possible to evaluate the profile of the three hospitals. The predictive process presented configurations with results that reached 0.75, which promises the use of the structure for the monitoring of automated SSI for patients undergoing surgery to correct aortic artery aneurysms. To optimize data collection, enable other hospitals to use the prediction tool and minimize noise from the database, two mobile application were developed: one for monitoring the patient in the hospital and another for monitoring after hospital discharge. The SSI prediction analysis tool is available at www.nois.org.br.Disclosures All Authors: No reported disclosures

879. Artificial Neural Networks to Predict Infection in the Surgical Site in Patients over 70 Years Old

BackgroundBetween July 2016 and June 2018, a survey was carried out in five hospitals on surgical site infection (SSI) in patients over 70 years old, who underwent surgery procedures, in the city of Belo Horizonte, a city with more of 3,000,000 inhabitants. The general objective is to statistically evaluate such incidences and enable an analysis of the predictive power of SSI, through MLP (Multilayer Perceptron) pattern recognition algorithms.MethodsThrough the Hospital Infection Control Committees (CCIH) of the hospitals involved in the research, data collection on SSI was carried out. Such data is used in the analysis during your routine SSI surveillance procedures. Thus, three procedures were performed: a treatment of the database collected for use of intact samples; a statistical analysis on the profile of the collected hospitals and; an evaluation of the predictive power of five types of MLPs (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay and Quick Propagation) for SSI prediction. The MLPs were tested with 3, 5, 7 and 10 neurons in the hidden layer and with a division of the database for the resampling process (65% or 75% for testing, 35% or 25% for validation). They were compared by measuring the AUC (Area Under the Curve - ranging from 0 to 1) for each of the configurations.ResultsFrom 11277 records, 3350 were complete for analysis. It was found that: the average age is 79 years (from 74 to 84 years); the average surgery time is 123 minutes; the average hospital stay is 58 days (with a maximum of 114 days), the death rate reached 7.1% and that of SSI 2.59%. A maximum prediction power of 0.642 was found.ConclusionThere was a loss of almost 70% of the database samples due to the presence of noise, however it was possible to evaluate the hospitals profile. The predictive process, presented configurations with results that reached 0.642, what promises the use of the structure for the monitoring of automated SSI for patients over 70 years submitted to surgeries. To optimize data collection, enable other hospitals to use the prediction tool and minimize noise from the database, two mobile application were developed: one for monitoring the patient in the hospital and another for monitoring after hospital discharge. The SSI prediction analysis tool is available at www.nois.org.br.Disclosures All Authors: No reported disclosures

877. Use of Statistical Process Control Charts for Early Detection of Healthcare Facility-Associated Nontuberculous Mycobacterial Outbreaks

BackgroundNontuberculous mycobacteria (NTM) are increasingly implicated in healthcare facility-associated (HCFA) outbreaks. However, systematic methods for NTM surveillance and outbreak detection are lacking and represent an emerging need. We examined how statistical process control (SPC) might perform in NTM outbreak detection.MethodsSPC charts were optimized for surgical site infection surveillance and adapted to analyze 3 NTM outbreaks that occurred from 2013-2016 at a single hospital. The first 2 outbreaks occurred contemporaneously and consisted of pulmonary Mycobacterium abscessus complex (MABC) acquisition and cardiac surgery-associated extrapulmonary MABC infection, respectively. The third outbreak was a pseudo-outbreak of Mycobacterium avium complex (MAC) at a bronchoscopy suite.We retrospectively analyzed monthly rates of unique patients who had: 1) positive respiratory cultures for MABC obtained on hospital day 3 or later; 2) positive non-respiratory cultures for MABC; and 3) positive bronchoalveolar lavage (BAL) cultures for MAC collected at the bronchoscopy suite. For each outbreak, we used these rates to construct a standardized moving average (MA) SPC chart with MA span of 3 months. Rolling baselines were estimated from average rates for months 7 through 12 prior to each monthly data point. SPC detection was indicated by the first data point above the upper control limit (UCL) of 3 standard deviations. Traditional surveillance detection was defined as the time of outbreak detection by routine infection control procedures.ResultsSPC detection occurred 5, 4, and 9 months prior to traditional surveillance outbreak detection for the three outbreaks, respectively (Figures 1 and 2). Prospective NTM surveillance using the MA chart potentially would have prevented an estimated 19 cases of pulmonary MABC, 9 cases of extrapulmonary MABC, and 80 cases of BAL MAC isolation (Table). No data points exceeded the UCL during 95 cumulative months of post-outbreak surveillance, suggesting low burden of false positive SPC signals.Figure 1. Use of a moving average statistical process control (SPC) chart for early detection of hospital-associated outbreaks of pulmonary Mycobacterium abscessus complex (MABC) and cardiac surgery-associated extrapulmonary MABC infection. The pulmonary chart analyzes cases of hospital-onset respiratory isolation of MABC. The extrapulmonary chart analyzes cases of positive non-respiratory cultures for MABC. CL, center line; LCL, lower control limit; UCL, upper control limit. Figure 2. Use of a moving average statistical process control (SPC) chart for early detection of a pseudo-outbreak of Mycobacterium avium complex (MAC) that occurred at a bronchoscopy suite. The chart analyzes cases of MAC isolated from bronchoalveolar lavage cultures. CL, center line; LCL, lower control limit; UCL, upper control limit. Table. Estimated cases of hospital-associated nontuberculous mycobacteria that would have been prevented by prospective surveillance with a moving average statistical process control (SPC) chart. ConclusionA single MA SPC chart detected 3 HCFA NTM outbreaks an average of 6 months earlier than traditional surveillance. SPC has potential to improve NTM surveillance, promoting early cluster detection and prevention of HCFA NTM.Disclosures All Authors: No reported disclosures

A midwifery-led prevalence programme for caesarean section surgical site infections

Caesarean section (CS) is a common procedure accounting for 29% of all deliveries. Surgical site infections (SSI) are a risk with any surgical procedure. A CS SSI prevalence programme led by a midwife, who is also an infection prevention and control matron, was implemented to determine the rate of CS SSI within the trust. The initial CS SSI rate was 26% over a 3-month period (June-August 2012). Targeted interventions were put in place to reduce the CS SSI rate, and by 2019, it had decreased to 8%. Hospitals should consider implementing CS SSI surveillance and prevention programmes. Real benefits can be realized with minimal resources.

Changes in the accuracy of administrative data for the detection of surgical site infections

We performed a retrospective analysis of the changes in accuracy of International Classification of Diseases, Clinical Modification (ICD-CM) diagnosis codes for colectomy and hysterectomy surgical site infection surveillance. After the transition from ICD-CM ninth edition to tenth edition codes, there was no significant change in the accuracy of these codes for SSI surveillance.

Pediatric research priorities in healthcare-associated infections and antimicrobial stewardship.

To develop a pediatric research agenda focused on pediatric healthcare-associated infections and antimicrobial stewardship topics that will yield the highest impact on child health. The study included 26 geographically diverse adult and pediatric infectious diseases clinicians with expertise in healthcare-associated infection prevention and/or antimicrobial stewardship (topic identification and ranking of priorities), as well as members of the Division of Healthcare Quality and Promotion at the Centers for Disease Control and Prevention (topic identification). Using a modified Delphi approach, expert recommendations were generated through an iterative process for identifying pediatric research priorities in healthcare associated infection prevention and antimicrobial stewardship. The multistep, 7-month process included a literature review, interactive teleconferences, web-based surveys, and 2 in-person meetings. A final list of 12 high-priority research topics were generated in the 2 domains. High-priority healthcare-associated infection topics included judicious testing for Clostridioides difficile infection, chlorhexidine (CHG) bathing, measuring and preventing hospital-onset bloodstream infection rates, surgical site infection prevention, surveillance and prevention of multidrug resistant gram-negative rod infections. Antimicrobial stewardship topics included β-lactam allergy de-labeling, judicious use of perioperative antibiotics, intravenous to oral conversion of antimicrobial therapy, developing a patient-level "harm index" for antibiotic exposure, and benchmarking and or peer comparison of antibiotic use for common inpatient conditions. We identified 6 healthcare-associated infection topics and 6 antimicrobial stewardship topics as potentially high-impact targets for pediatric research.

Antimicrobial resistance in hospitalized surgical patients: a silently emerging public health concern in Benin

BackgroundSurgical site infections are related to high morbidity, mortality and healthcare costs. Because the emergence of multidrug-resistant bacteria in hospitals is becoming a worldwide challenge for surgeons who treat healthcare-associated infections, we wished to identify the causative agents involved in these infections and the rate of multidrug-resistant bacteria in six public hospitals in Benin.MethodsUsing standard microbiological procedures, we processed pus specimens collected from obstetrics and gastrointestinal surgery wards. Mass spectrometry (MALDI-TOF) was used for confirmation. For the antibiotic susceptibility test, we first used the Kirby-Bauer disk diffusion method. The secondary test (by microdilution) used the Beckton Dickinson Phoenix automated system (Becton Dickinson Diagnostic, USA).ResultsWe included 304 patients, whose median length of stay was 9 days. A total of 259 wound swabs (85.2%) had positive aerobic bacterial growth. In obstetrics, S. aureus (28.5%, n = 42) was the most common isolate. In contrast, Gram-negative bacteria (GNB) were predominant in gastrointestinal surgery, the most dominant being E.coli (38.4%, n = 31). Overall, 90.8% (n = 208) of aerobic bacteria were multidrug resistant. Two-thirds of S. aureus (65.3%, n = 32) were methicillin-resistant Staphylococcus aureus (MRSA), three of which carried both MRSA and induced clindamycin resistance (ICR). GNB showed high resistance to ceftazidime, ceftriaxone and cefepime. Extended-spectrum beta-lactamases were presented by 69.4% of E.coli (n = 43/62) and 83.3% of K. pneumoniae (n = 25/30). Overall, twelve Gram-negative bacteria (5.24%) showed resistance to at least one carbapenem. No isolates showed a wild-type susceptible phenotype.ConclusionThis study shows the alarming prevalence of multidrug-resistant organisms from surgical site infections in Benin hospitals. To reduce the spread of such bacteria in Benin, periodic surveillance of surgical site infections and strict adherence to good hand-hygiene practice are essential.

Prevalence and antimicrobial resistance patterns of nosocomial pathogens causing Surgical Site Infections in an Egyptian University hospital.

Background: Surgical site infections (SSI) are a common type of health care associated infections. The emergence of multidrug resistant nosocomial pathogens represents a major heath burden. This study was conducted to determine the frequency of isolation and patterns of antimicrobial resistance of nosocomial pathogens causing SSI in Zagazig University Hospitals. Methodology: Samples obtained from the infected surgical wounds were subjected to microbiological identification and antibiotic susceptibility testing. The role of extended spectrum beta lactamase (ESBL) and carbapenmases in bacterial resistance to some antibiotic were evaluated. Results: The most frequently isolated species were S. aureus (31%) followed by Klebseilla pneumoniae (22%), E. coli (15%), P. aeruginosa (11%), Coagulase negative staphylococci ( CoNs) (8%) , Proteus spp (7%) and Acinetobacter spp (6%). Methecillin resistance was detected in 38 (97 %) and 8 (80 %) S. aurues and CoNs isolates, respectively. Among Gram negative organisms, 65.8% of isolates were ESBL producers, of which 60% were Carbapenem resistant. Metallo-β-lactamase was detected in 30% of Gram negative isolates. Multi-drug resistance (MDR) was observed in 50 isolates (68.5%) where extensively drug resistance (XDR) occurred in 23 (31.5%) of Gram negative isolates. Conclusion: Most of Gram-negative isolates were MDR or XDR. Antibiotic therapy of SSI must be guided by microbiological culture and antibiotic sensitivity testing. Infection prevention and control practices need more improvement. Rationalisation of antibiotic prescription must be carried out. Post discharge surveillance of SSI needs to be considered.