Surgical Site Infection Surveillance Research Articles

Surveillance of surgical site infections using artificial intelligence

Abstract Background Surgical site infection (SSI) is a major health problem associated with high morbidity and mortality, the consequences of which can be very serious for the patient and costly for the organisation. Surveillance systems provide insight into the incidence of SSI, the analysis of which enables improvement plans to be established to reduce it. Traditionally, surveillance systems have been based on manual medical record review for evidence of the presence of surgical infection. Objectives To create and validate a global SSI diagnostic algorithm and to optimise the SSI workload of Preventive Medicine services. Methods The study population included patients undergoing surgical procedures of rectal surgery, colon surgery, knee replacement surgery, hip replacement surgery, coronary bypass and valve surgery, at the Hospital Universitario Vinalopó in Elche (n = 1240). Data mining was used to collect clinical, microbiological and postoperative follow-up values from the electronic medical record. Machine Learning techniques were used to train (n = 1054) and validate the model (n = 186). Time spent on SSI surveillance of the preventive medicine service was measured. Results Model performance after validation was: sensitivity of 0.83 specificity of 0.87, accuracy of 0.87, an F1 score of 0.45, and an area under the curve of 0.87. The time spent by preventive medicine staff in identifying patients with surgical site infection decreased from 168 person-hours per procedure per quarter to 34 person-hours, a 77% reduction in the workload allocated to this task. Conclusions This project not only improves surveillance efficiency, but also optimises the workload in Preventive Medicine services very significantly. Key messages • This project improves the efficiency of surgical site infection surveillance and significantly optimises the workload in preventive medicine departments. • It makes it possible to extend surveillance to new surgical procedures and to work more intensively on preventive measures.

Evaluating XGBoost’s predictive accuracy on surgical site Infections in cardiac surgery

Abstract Background Surgical site infections (SSIs) pose a significant threat in cardiac surgery (CS), profoundly impacting patient prognosis. SSI incidence varies widely, reported between 3.5% and 26.8%. The study used a decade-long dataset from SSI surveillance in a specialized hospital in Italy, applying machine learning (ML) techniques to predict the SSI incidence among CS patients. Methods Data collected from 2013-2023 through the surveillance system of SSI in patients undergoing CS were used to train a predictive ML algorithm (XGBoost). Data included information on demographics, risk factors, surgery variables (incision site, prophylaxis, etc.), and the infection outcome derived from follow-up interviews at 30 days post-surgery, or 90 days for patients with prosthetic materials, according to the ECDC case definition of SSI. We used the R libraries “caret”, “smotefamily” and “xgboost” to train the algorithm. A train-test split of 70-30 was applied. Both downsampling of the majority class (no SSI) and oversampling of SSI cases with SMOTE were used in the training set to address class imbalance. Results A total of 10,534 subjects (65.9% males, mean age 68.3 years) who underwent CS (64.3% with prosthetic materials) were included, among which 533 SSIs were identified (mean incidence of 5.06%), with 430 cases (80.7%) occurring after discharge (38.7% deep SSI) and 103 (19.3%) before discharge (55.5% deep SSI). The trained XGBoost algorithm achieved an AUC of 0.62, sensitivity of 69%, and specificity of 50% in the prediction of SSI on the test dataset. Conclusions These findings suggest that while the XGBoost model provides a fair predictive capability, there is significant room for improvement in sensitivity and specificity. The use of artificial intelligence offers a promising opportunity to identify patients at risk of SSI. However, further research and comprehensive data are needed to refine the predictive model and effectively improve prevention measures. Key messages • Predominantly occurring post-discharge, SSIs in cardiac surgery necessitate enhanced prevention strategies, highlighting the critical phase after hospital discharge where surveillance is paramount. • Artificial intelligence may enhance post-discharge SSI surveillance, promising to identify patients at increased risk. Further research is needed to refine these AI tools for optimal sensitivity.

A study on pathogenic aerobic bacteria of surgical site infection and their antimicrobial susceptibility pattern in patients attending a hospital in Bhubaneswar, Odisha

Abstract: Introduction: Identification of bacterial pathogens and their antibiotic susceptibility testing are vital for the effective treatment of surgical site infection (SSI). Objective: The objective of the study was to study the bacterial pathogens in patients with SSI and their antibiotic susceptibility pattern. Methods: Pus samples were collected using sterilized swab stick, and then, the samples were cultured in MacConkey and Blood agar and incubated for 24 h in bacterial incubator. The identification was done by using colony morphology, Gram staining technique, and biochemical tests. After identification, the antibiogram of organisms was done using Mueller–Hinton agar. Results: A total of 76 pus samples were collected from different specialties from SSIs. Out of which 53 samples were culture positive. The number of male patients who had SSI was higher than females. Maximum SSIs were observed in the orthopedics department followed by the surgery department and gynecology department. SSIs in surgery and orthopedics department were commonly seen in the age group 41–60 years. In the obstetrics and gynecology department, SSIs were seen mostly in the age group 21–40 years. In the surgery and orthopedics department, Staphylococcus aureus was the predominant organism and Klebsiella spp was the most common Gram-negative isolate. In the gynecology department, S. aureus was the predominant organism followed by Acinetobacter spp. Maximum sensitivity to Vancomycin and Linezolid was seen as the only Gram-positive isolate in all specialties. Gram-negative isolates from the Enterobacteriaceae family of all specialties were sensitive to tigecycline followed by imipenem and meropenem. Nonfermenters were mostly sensitive to polymyxin b/colistin, imipenem, and meropenem. Conclusion: The study gives an insight into aerobic bacterial pathogens and their antibiotic-sensitivity patterns isolated from SSI and there should be surveillance of SSI which helps to reduce the rate of SSI as well as appropriate use of antibiotics.

Perception and Role of Indirect and Post-Discharge Surveillance in Predicting Surgical Site Infection in Surgical Patients: An Institutional Experience

Abstract Background: Surgical site infection (SSI) surveillance is a process of observing and reporting of infections following surgery. SSI surveillance studies are few in our country. Objectives: Present study was conducted to know the perception and role of SSI surveillance. Incidence of surgical site infection, identification of risk factors and bacterial spectrum of surgical wounds during surveillance were also studied. Methods: Patients who underwent a surgical procedure between July 2022 and June 2023 at our hospital were included. A prospective incidence surveillance for SSI was done to look for any signs of infection and record them in the surveillance form. Wound swabs or pus aspirates were sent for microbiological culture. Results: A total of 2312 patients underwent surgery during the study period, of whom 61 patients were diagnosed with SSI. The incidence of SSI was 2.6%. SSI was encountered more in female patients (57.3%). Age distribution had a significant association with SSI (P = 0.025). Most operative wounds were clean-contaminated (45.9%). Most SSIs were superficial (91.8%), followed by deep (8.2%). Most patients who developed SSI had a National Nosocomial Infection Surveillance (NNIS) patient risk index of 2 (45.9%). Bacterial growth was observed in 45.9% of cases. Multidrug resistance (MDR) among these isolates was 42.6%. Conclusion: This study helped to determine predictors of SSI like duration of surgery, type of wound, duration of hospital stays, and NNIS risk index. MDR isolates are now contributing to SSI. The perception of healthcare workers about SSI surveillance was that it was feasible to use and practice. Surveillance helped clinicians to strengthen the existing infection prevention and control practices for the future.

Surgical site infection surveillance in knee and hip arthroplasty: optimizing an algorithm to detect high-risk patients based on electronic health records

BackgroundSurgical site infection (SSI) is an important cause of disease burden and healthcare costs. Fully manual surveillance is time-consuming and prone to subjectivity and inter-individual variability, which can be partly overcome by semi-automated surveillance. Algorithms used in orthopaedic SSI semi-automated surveillance have reported high sensitivity and important workload reduction. This study aimed to design and validate different algorithms to identify patients at high risk of SSI after hip or knee arthroplasty.MethodsRetrospective data from manual SSI surveillance between May 2015 and December 2017 were used as gold standard for validation. Knee and hip arthroplasty were included, patients were followed up for 90 days and European Centre for Disease Prevention and Control SSI classification was applied. Electronic health records data was used to generate different algorithms, considering combinations of the following variables: ≥1 positive culture, ≥ 3 microbiological requests, antimicrobial therapy ≥ 7 days, length of hospital stay ≥ 14 days, orthopaedics readmission, orthopaedics surgery and emergency department attendance. Sensitivity, specificity, negative and predictive value, and workload reduction were calculated.ResultsIn total 1631 surgical procedures were included, of which 67.5% (n = 1101) in women; patients’ median age was 69 years (IQR 62 to 77) and median Charlson index 2 (IQR 1 to 3). Most surgeries were elective (92.5%; n = 1508) and half were hip arthroplasty (52.8%; n = 861). SSI incidence was 3.8% (n = 62), of which 64.5% were deep or organ/space infections. Positive culture was the single variable with highest sensitivity (64.5%), followed by orthopaedic reintervention (59.7%). Twenty-four algorithms presented 90.3% sensitivity for all SSI types and 100% for deep and organ/space SSI. Workload reduction ranged from 59.7 to 67.7%. The algorithm including ≥ 3 microbiological requests, length of hospital stay ≥ 14 days and emergency department attendance, was one of the best options in terms of sensitivity, workload reduction and feasibility for implementation.ConclusionsDifferent algorithms with high sensitivity to detect all types of SSI can be used in real life, tailored to clinical practice and data availability. Emergency department attendance can be an important variable to identify superficial SSI in semi-automated surveillance.

Post Caesarean Surgical Site Infection: Incidence, Prevalence, Risk Factors and Microbiological Profile of Tertiary Care Hospital, Jaipur

Background: In the past few decades, the prevalence of cesarean sections (CS) has continuously increased worldwide making it one of the most frequent surgical procedures. CS can often save a patient's life, but there are chances of postoperative consequences such as surgical site infections (SSI). During this study we have determine the occurrence and risk factors associated surgical site infections in women undergoing CS. Methodology: This is a prospective study conducted in a tertiary care hospital. Total 280 women were selected whose undergoes elective or emergency CS during May 2023 – July 2023. Each woman was properly examined and followed for 7 days to developed SSI. Bacterial profile and antibiotics pattern were examined to relate other factors associated with SSI. Results: Among 280 candidate 59 candidate suspected for SSI which are 4.74%. after microbiological analysis 5 samples were failed to produce culture, 54 (5.18%) samples were identified as SSI. Among 54 samples 77. 78% (n=42) observed as Single bacterial infection and 22.22 (n=12) observed as Mixed bacterial infection. Among all Coagulase negative staphylococci spp (CoNS) showed the highest infection 22.23% followed by Staphylococcus aureus 16.95% highest infection was observed in higher age candidate (>30) 37.04%, rural candidate 59.26%, obese candidate 31.48% and Lower-class candidate 53.70%. Conclusion: This study showed the high incidence of SSI after CS which highlighted the urgent need of prevent and surveillance of SSI. Considering patients demographic and medical history incidences of SSI can be reduced.

Duration of surgical antibiotic prophylaxis and surgical site infection in orthopaedic surgery: A prospective cohort study.

The optimal duration for surgical antibiotic prophylaxis (SAP) for preventing surgical site infection (SSI) in orthopaedic surgeries remains poorly supported by high-level evidence. This study aimed to assess the association between SAP duration and the occurrence of SSI within one year postoperatively. This prospective cohort study was based on the database from Surgical Site Infection Surveillance and Improvement Project (SISIP) of a tertiary orthopaedic university hospital from October 2014 to December 2020. The main outcome was SSI, defined according to the CDC/NHSN criteria, determined by review of index hospitalization medical records, microbiology laboratory reports, and readmission records for SSI treatment within one-year after discharge. Adjusted Generalized additive models (GAMs) were performed to assess the relationships between SAP duration and SSI, determined the cut-off point of SAP duration, and estimate the relative contribution of each included variable, across the overall cohort and the three subgroups (open fracture, closed fracture, and non-traumatic group). Multivariable logistic regression models were used to estimate the association between prolonging SAP duration based on the cut-off point and SSI. There were 37,046 patients (55.1% male) included, with the overall SSI incidence of 2.35% (871/37,046). In adjusted GAMs, no statistically significant relationships were observed in overall cohort and open or closed group (P>0.05), but a nonlinear relationship was exhibited non-traumatic group (P=0.03); the cut-off point were 2.4 days for overall cohort and 3.6 days (open), 2.6 days (closed), 1.1 days (non-trauma) for three subgroups. In adjusted logistic regression, prolonging SAP duration did not demonstrate a statistically significant protective effect in overall cohort (aOR=0.868; 95% CI, 0.746-1.011) and three groups (open: aOR=0.867; 95% CI, 0.668-1.124; closed: aOR=0.925; 95% CI, 0.754-1.135; non-trauma: aOR=1.184; 95% CI, 0.832-1.683). The relative contribution ranks of SAP duration were 21st overall among 34 factors, 14th for open fractures, 28th for closed fractures, and 3rd for non-traumatic group among 33 factors. Prolonged postoperative SAP duration has no protective effect against SSI in orthopaedic surgery. Our findings support current guidelines against the practice of continuing SAP postoperatively.

A Deeper Look at Proposed Surveillance of Superficial Incision Surgical Site Infections (SSISSIs)

Although the National Healthcare Safety Network (NHSN) recommends the reporting of superficial incisional SSIs, the standardized infection ratio (SIR) models used by the NSHN exclude superficial incisional SSIs cases. Yet, some superficial incisional SSIs may lead to serious adverse patient outcomes. We previously proposed a new category of such infections: serious superficial incisional surgical site infections (SSISSIs), defined as a superficial incisional SSI that (1) required debridement in an operating room and/or (2) led to a hospital readmission within 30 days of surgery. The objective of our study was to determine the prevalence of SSISSIs in a large network of community hospitals and compare hospital rankings of SSI rates of organ/space and deep SSIs (complex SSIs) with and without SSISSIs. We performed a retrospective descriptive analysis of prospectively collected data on 35 NHSN surgical categories in 47 community hospitals within the Duke Infection Control Outreach Network (DICON) from 1/1/2013-12/31/2022. All hospitals used standardized surveillance and data collection strategies throughout the study period. The Wilcoxon rank-sum was used to test for differences in performance rankings of hospitals sorted by rates of complex SSIs alone compared to complex and SSISSI rates. A two-tailed P value of .05 or less was considered significant. Overall, 11,617 SSIs occurred after 1,272,257 surgeries (0.91 SSIs/100 procedures). Out of 3,996 superficial SSIs, 2,038 (17.5% overall, 51.0% of superficial incisional) met criteria for SSISSI. 112 (5.5%) were diagnosed during the current admission and required takeback to the OR for infection; 1,926 (94.5%) were diagnosed during a readmission; and 3841 (33.1%) were diagnosed during readmission and returned to the OR. (Table1) The highest proportion of SSISSIs was diagnosed in patients who underwent gastrointestinal surgery (32.0%) or orthopedic surgery (24.0%). (Table2) Performance ranking of individual hospitals based on rates of complex SSIs, differed significantly when including SSISSIs (p= 0.02). (Table3) Discussion Our findings suggest that SSISSIs make up a moderate but important proportion of SSIs in community hospitals. SSISSIs can be identified through established database surveillance looking at objective measures of returning to the OR for debridement and/or readmission within 30 days. Hospital rankings differed significantly when SSISSIs were added to complex SSIs to calculate SSI rates. As such, including SSISSIs likely provides a more accurate depiction of SSIs with important outcomes and is not as subjective to surveillance bias. Next steps would be specifically to look at outcomes data for complex SSIs compared to SSISSIs to fully evaluate theDisclosure: Jessica Seidelman: UptoDate- Section Editor; BoneSupport- Consultant

National Surgical Site Infection Surveillance System Results Report: July 2021 through June 2022

National Surgical Site Infection Surveillance System Results Report: July 2021 through June 2022

Surgical Antimicrobial Prophylaxis in Low-Risk Cholecystectomies is Associated with Fewer Surgical Site Infections: Nationwide Cohort Study in Switzerland.

To assess whether administration of surgical antimicrobial prophylaxis (SAP) versus absence of SAP is associated with a decreased risk of surgical site infections (SSI) after low-risk cholecystectomies (LR-CCE). Current guidelines do not recommend routine SAP administration prior to LR-CCE. This cohort study included adult patients who underwent LR-CCE and were documented by the Swissnoso SSI surveillance system between 1/2009-12/2020 at 66 Swiss hospitals. LR-CCE was specified as elective endoscopic surgery, age <70, no active cholecystitis, ASA score <3, operating time <120 minutes without implantation of foreign material. Exposure was defined as the administration of cefuroxime or cefazoline ± metronidazole within 120 minutes prior to incision versus no SAP administration. Our main outcome was occurrence of SSI until day 30. Logistic regression models were used to adjust for institutional, patient, and perioperative variables. Of 44 682 surveilled adult cholecystectomy patients, 12 521 (8 726 women [69.7%]; median [IQR] age, 49.0 [38.1-58.2] years), fulfilled inclusion criteria. SSI was identified in 143 patients (1.1%). SAP was administered in 9 269 patients (74.0%) and was associated with a lower SSI rate (adjusted odds ratio [aOR], 0.50; 95% CI, 0.35-0.70; P < 0.001). The number needed to treat to prevent one SSI episode is 100. The overall LR-CCE SSI rate was 1.1%. SAP was associated with a 50% lower overall SSI rate. Patients undergoing LR-CCE may benefit from routine surgical antimicrobial prophylaxis.

Evaluation of a multifaceted implementation strategy for semi-automated surveillance of surgical site infections after total hip or knee arthroplasty: a multicentre pilot study in the Netherlands

IntroductionTo promote the nation-wide implementation of semi-automated surveillance (AS) of surgical site infection after hip and knee arthroplasty, the Dutch National Institute for Public Health and the Environment (RIVM) deployed a decentralised multifaceted implementation strategy. This strategy consisted of a protocol specifying minimum requirements for an AS system, supported by a user manual, education module, individual guidance for hospitals and user-group meetings. This study describes an effect evaluation and process evaluation of the implementation strategy for AS in five frontrunner hospitals.MethodsTo evaluate the effect of the implementation strategy, the achieved phase of implementation was determined in each frontrunner hospital at the end of the study period. The process evaluation consisted of (1) an evaluation of the feasibility of strategy elements, (2) an evaluation of barriers and facilitators for implementation and (3) an evaluation of the workload for implementation. Interviews were performed as a basis for a subsequent survey quantifying the results regarding the feasibility as well as barriers and facilitators. Workload was self-monitored per profession. Qualitative data were analysed using a framework analysis, whereas quantitative data were analysed descriptively.ResultsOne hospital finished the complete implementation process in 240 person-hours. Overall, the elements of the implementation strategy were often used, positively received and overall, the strategy was rated effective and feasible. During the implementation process, participants perceived the relative advantage of AS and had sufficient knowledge about AS. However, barriers regarding complexity of AS data extraction, data-infrastructure, and validation, lack of capacity and motivation at the IT department, and difficulties with assigning roles and responsibilities were experienced.ConclusionA decentralised multifaceted implementation strategy is suitable for the implementation of AS in hospitals. Effective local project management, including clear project leadership and ownership, obtaining commitment of higher management levels, active involvement of stakeholders, and appropriate allocation of roles and responsibilities is important for successful implementation and should be facilitated by the implementation strategy. Sufficient knowledge about AS, its requirements and the implementation process should be available among stakeholders by e.g. an education module. Furthermore, exchange of knowledge and experiences between hospitals should be encouraged in user-group meetings.

Surveillance of Surgical Site Infections in Post-operative Patients and Bacterial Susceptibility in Tanzania

Surgical site infections (SSI) are infections occurring within 30 days of the post-operative procedure. They are common post-operative morbid complications that may cause death if not treated timely. The common causes of SSI include infectious bacteria, such as Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli, and some Enterobacteriaceae. This was a cross-sectional study conducted at St. Francis Referral Hospital, Ifakatra, Tanzania over a period of 12 months to investigate the causes of SSI and antimicrobial susceptibility of the causal agents. The study included consenting patients who developed post-operative wound infections during the study period. Identification of infecting micro-organisms and their antimicrobial susceptibility was done at St Francis Referral Hospital Laboratory. Antibiotic susceptibility tests of the isolates were performed by the Kirby–Bauer (K–B 1966) disc diffusion test, and extended spectrum β-lactamase producing Gram-negative species were tested by using the modified double disc synergy test. A total of 130 patients developed post-operative wound infection. Third and fourth decades were the most affected age groups; females were the dominant group with a 1:1.4 male: female ratio. Out of the 130 specimens, 121 isolates were obtained, and nine specimens were negative for culture. P. aeruginosa was the most commonly isolated agent (42.1%), followed by S. aureus (19.8%), while the least were Streptococcus spp. at 0.8%. The isolates showed the highest resistance to ampicillin (91.7%), and least to ciprofloxacin (1.7%). P. aeruginosa was highly resistant to both amoxicillin + clavulanic acid (98%), and to ampicillin (98.0%). Extended spectrum β-lactamase E. coli producers were 68.4%. The bacteria causing SSI require continuous monitoring to obtain data that will support local and national guidelines in the battle against antimicrobial resistance, and improve therapeutic outcomes following surgical interventions.

Surveillance of surgical site infections in orthopedic prosthetic surgery: a tool for identifying risk factors and improving clinical practice.

Surgical site infections (SSIs) are among the most frequently encountered complications in prosthetic surgery, and are associated with increased hospitalization, costs and in-hospital mortality. There is no national system for the comprehensive monitoring of the incidence of SSIs. All patients undergoing orthopedic prosthetic surgery from April 1 to June 30, 2023 were enrolled. Clinical evaluation of the surgical site was conducted at 30 days, and a follow-up telephone interview was carried out by means of a specially designed questionnaire at 90 days. A total of 59 patients were included. Surgery was performed on the knee in 71.19% and on the hip in 28.81%. The patients' mean BMI was 28.25 ± 2.97, and their mean ASA score was 2.67 ± 0.58. Six patients had diabetes mellitus. The incidence of SSIs was 5.08%; two infections occurred in knee prosthesis surgery and one in hip surgery. Analysis of the data revealed that diabetes was the main risk factor for the development of infection. Although based on a small number of patients, these results are encouraging, especially considering that the patients had an average ASA score of more than 2 and a high BMI. However, to further reduce the risk of infection, improved hygiene measures have now been implemented in the operating room and the antibiotic prophylaxis protocol has been updated to take into account the potential for MRSA colonization.

ITS 101 - Results: of a 2-year Surgical Site Infection (SSI) Surveillance Program for Caesarean Sections (C-sections) at a Community Hospital

ITS 101 - Results: of a 2-year Surgical Site Infection (SSI) Surveillance Program for Caesarean Sections (C-sections) at a Community Hospital

Advocating for Alignment in Pediatric Cardiothoracic Surgical Site Infection Surveillance Definitions.

Reporting definitions for Surgical Site Infections (SSIs) are frequently used to identify cases for quality improvement purposes. Here we highlight the discrepancies in reporting criteria for pediatric cardiac surgery procedures and call for alignment in definitions.

Quality check: concordance between two monitoring systems for postoperative organ/space-surgical site infections in rectal cancer surgery. Linkage of data from the Catalan Cancer Plan and the VINCat infection surveillance programme

BackgroundThe Catalan Cancer Plan (CCP) undertakes periodic audits of cancer treatment outcomes, including organ/space surgical site infections (O/S-SSI) rates, while the Catalan Healthcare-associated Infections Surveillance Programme (VINCat) carries out standardized prospective surveillance of surgical site infections (SSI) in colorectal surgery. This cohort study aimed to assess the concordance between these two monitoring systems for O/S-SSI following primary rectal cancer surgery.MethodsThe study compared O/S-SSI incidence data from CCP clinical audits versus the VINCat Programme in patients undergoing surgery for primary rectal cancer, in 2011-12 and 2015-16, in publicly funded centres in Spain. The main outcome variable was the incidence of O/S-SSI in the first 30 days after surgery. Concordance between the two registers was analysed using Cohen’s kappa. Discordant cases were reviewed by an expert, and the main reasons for discrepancies evaluated.ResultsPooling data from both databases generated a sample of 2867 patients. Of these, O/S-SSI was detected in 414 patients—235 were common to both registry systems, with satisfactory concordance (κ = 0.69, 95% confidence interval 0.65–0.73). The rate of discordance from the CCP (positive cases in VINCat and negative in CCP) was 2.7%, and from VINCat (positive in CCP and negative in VINCat) was 3.6%. External review confirmed O/S-SSI in 66.2% of the cases in the CCP registry and 52.9% in VINCat.ConclusionsThis type of synergy shows the potential of pooling data from two different information sources with a satisfactory level of agreement as a means to improving O/S-SSI detection. ClinicalTrials.gov Identifier: NCT06104579. Registered 30 November 2023.

The obesity paradox exists for perioperative complications and mortality following lower extremity arterial bypass surgery

ObjectiveThe obesity paradox refers to a phenomenon by which obese individuals experience lower risk of mortality and even protective associations from chronic disease sequelae when compared with the non-obese and underweight population. Prior literature has demonstrated an obesity paradox after cardiac and other surgical procedures. However, the relationship between body mass index (BMI) and perioperative complications for patients undergoing major open lower extremity arterial revascularization is unclear. MethodsWe queried the Vascular Quality Initiative for individuals receiving unilateral infrainguinal bypass between 2003 and 2020. We used multivariable logistic regression to assess the relationship of BMI categories (underweight [<18.5 kg/m2], non-obese [18.5-24.9 kg/m2], overweight [25-29.9 kg/m2], Class 1 obesity [30-34.9 kg/m2], Class 2 obesity [35-39.9 kg/m2], and Class 3 obesity [>40 kg/m2]) with 30-day mortality, surgical site infection, and adverse cardiovascular events. We adjusted the models for key patient demographics, comorbidities, and technical and perioperative characteristics. ResultsFrom 2003 to 2020, 60,588 arterial bypass procedures met inclusion criteria for analysis. Upon multivariable logistic regression with the non-obese category as the reference group, odds of 30-day mortality were significantly decreased among the overweight (odds ratio [OR], 0.64; 95% confidence interval [CI], 0.53-0.78), Class 1 obese (OR, 0.65; 95% CI, 0.52-0.81), Class 2 obese (OR, 0.66; 95% CI, 0.48-0.90), and Class 3 obese (OR, 0.61; 95% CI, 0.39-0.97) patient categories. Conversely, odds of 30-day mortality were increased in the underweight patient group (OR, 1.58; 95% CI, 1.16-2.13). Furthermore, a BMI-dependent positive association was present, with odds of surgical site infections with patients in Class 3 obesity having the highest odds (OR, 2.10; 95% CI, 1.60-2.76). Finally, among the adverse cardiovascular event outcomes assessed, only myocardial infarction (MI) demonstrated decreased odds among overweight (OR, 0.82; 95% CI, 0.71-0.96), Class 1 obese (OR, 0.78; 95% CI, 0.65-0.93), and Class 2 obese (OR, 0.66; 95% CI, 0.51-0.86) patient populations. Odds of MI among the underweight and Class 3 obesity groups were not significant. ConclusionsThe obesity paradox is evident in patients undergoing lower extremity bypass procedures, particularly with odds of 30-day mortality and MI. Our findings suggest that having higher BMI (overweight and Class 1-3 obesity) is not associated with increased mortality and should not be interpreted as a contraindication for lower extremity arterial bypass surgery. However, these patients should be under vigilant surveillance for surgical site infections. Finally, patients that are underweight have a significantly increased odds of 30-day mortality and may be more suitable candidates for endovascular therapy.

Comparison of an algorithm, and coding data, with traditional surveillance to identify surgical site infections in Australia: a retrospective multi-centred cohort study

Surveillance of healthcare-associated infections (HAIs) in Australia is disparate, resource intensive, unsustainable, and provides limited information. Traditional HAI surveillance is time intensive and agreement levels between clinicians have been shown to be variable. To compare two methods: a semi-automated algorithm, and coding data, against traditional surgical site infection (SSI) surveillance methods. This retrospective multi-centre cohort study included all patients undergoing a hip (HPRO) or knee (KPRO) prosthesis and coronary artery bypass graft (CABG) surgery during a two-year period at two large metropolitan hospitals. Routine SSI data were obtained via the infection prevention and control (IPC) team, a previously developed algorithm was applied to all patient records, and the ICD-10-AM data were searched for those categorized as having an SSI. Overall, 1447, 1416, and 1026 patients who underwent HPRO, KPRO, and CABG, respectively, were included. The highest sensitivity values were generated by the algorithm: HPRO deep or organ-space (D/O) 0.87 (95% confidence interval: 0.66-0.96), CABG 0.86 (0.64-0.96), and HPRO all SSI 0.77 (0.57-89); the lowest sensitivity was Code CABG D/O 0.03 (0.00-0.21). The highest PPV values were generated by the algorithm: HPRO D/O 0.97 (0.77-0.99), CABG D/O 0.97 (0.76-0.99), and the Code HPRO D/O 0.9 (0.66-0.99). Both the algorithm and coding data resulted in a substantial reduction in the number of medical records required to review. The application of algorithms to enhance SSI surveillance demonstrates high accuracy in identifying patient records that require review by IPC teams to determine the presence of an SSI. Coding data alone should not be used to identify SSIs.

An explainable long short-term memory network for surgical site infection identification

BackgroundCurrently, surgical site infection surveillance relies on labor-intensive manual chart review. Recently suggested solutions involve machine learning to identify surgical site infections directly from the medical record. Deep learning is a form of machine learning that has historically performed better than traditional methods while being harder to interpret. We propose a deep learning model, a long short-term memory network, for the identification of surgical site infection from the medical record with an attention layer for explainability. MethodsWe retrieved structured data and clinical notes from the University of Utah Health System’s electronic health care record for operative events randomly selected for manual chart review from January 2016 to June 2021. Surgical site infection occurring within 30 days of surgery was determined according to the National Surgical Quality Improvement Program definition. We trained the long short-term memory model along with traditional machine learning models for comparison. We calculated several performance metrics from a holdout test set and performed additional analyses to understand the performance of the long short-term memory, including an explainability analysis. ResultsSurgical site infection was present in 4.7% of the total 9,185 operative events. The area under the receiver operating characteristic curve and sensitivity of the long short-term memory was higher (area under the receiver operating characteristic curve: 0.954, sensitivity: 0.920) compared to the top traditional model (area under the receiver operating characteristic curve: 0.937, sensitivity: 0.736). The top 5 features of the long short-term memory included 2 procedure codes and 3 laboratory values. ConclusionSurgical site infection surveillance is vital for the reduction of surgical site infection rates. Our explainable long short-term memory achieved a comparable area under the receiver operating characteristic curve and greater sensitivity when compared to traditional machine learning methods. With explainable deep learning, automated surgical site infection surveillance could replace burdensome manual chart review processes.

Surveillance of infections of surgical sites and lower respiratory tracts should be combined: experiences from the German surveillance module for operated patients (OP-KISS), 2018 to 2022.

BackgroundSurveillance of lower respiratory tract infections (LRTI) of operated patients conventionally focuses on intubated patients in intensive care units (ICU). Post-operative immobilisation increases the risk of LRTI not associated with ventilators. Operated patients, however, have thus far not been a primary target for LRTI surveillance.AimWe aimed to describe the applied LRTI surveillance method in the German surveillance module for operated patients (OP-KISS) and to report data between 2018 and 2022.MethodsSurveillance of LRTI can be performed voluntarily in addition to surgical site infection (SSI) surveillance in OP-KISS. We calculated LRTI rates per 100 operations for all procedures combined, as well as for individual surgical groups and procedures. Additionally, a combined post-operative infection rate (SSI and LRTI) was calculated.ResultsSurveillance of LRTI was performed in 4% of all participating OP-KISS departments and for 2% (23,239 of 1,332,438) of all procedures in the OP-KISS database. The pooled LRTI rate was 0.9 per 100 operations, with marked differences between different types of surgery (3.6 for lobectomies, 0.1 for traumatology and orthopaedics). The share of LRTI among all post-operative infections was highly variable. For lobectomies, the LRTI rate was higher than the SSI rate (3.6 vs 1.5 per 100 operations).ConclusionSurveillance of post-operative LRTI is not yet widely adopted by German hospitals. Based on the data in this study, lobectomies represent a prime target for post-operative LRTI surveillance.