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Risk factors for nosocomial COVID-19 outbreaks continue to evolve. The aim of this study was to investigate a multi-ward nosocomial outbreak of COVID-19 between 1st September and 15th November 2020, occurring in a setting without ...
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Risk factors for nosocomial COVID-19 outbreaks continue to evolve. The aim of this study was to investigate a multi-ward nosocomial outbreak of COVID-19 between 1st September and 15th November 2020, occurring in a setting without vaccination for any healthcare workers or patients.Outbreak report and retrospective, matched case–control study using incidence density sampling in three cardiac wards in an 1100-bed tertiary teaching hospital in Calgary, Alberta, Canada. Patients were confirmed/probable COVID-19 cases and contemporaneous control patients without COVID-19. COVID-19 outbreak definitions were based on Public Health guidelines. Clinical and environmental specimens were tested by RT-PCR and as applicable quantitative viral cultures and whole genome sequencing were conducted. Controls were inpatients on the cardiac wards during the study period confirmed to be without COVID-19, matched to outbreak cases by time of symptom onset dates, age within ± 15 years and were admitted in hospital for at least 2 days. Demographics, Braden Score, baseline medications, laboratory measures, co-morbidities, and hospitalization characteristics were collected on cases and controls. Univariate and multivariate conditional logistical regression was used to identify independent risk factors for nosocomial COVID-19.The outbreak involved 42 healthcare workers and 39 patients. The strongest independent risk factor for nosocomial COVID-19 (IRR 3.21, 95% CI 1.47–7.02) was exposure in a multi-bedded room. Of 45 strains successfully sequenced, 44 (97.8%) were B.1.128 and differed from the most common circulating community lineages. SARS-CoV-2 positive cultures were detected in 56.7% (34/60) of clinical and environmental specimens. The multidisciplinary outbreak team observed eleven contributing events to transmission during the outbreak.Transmission routes of SARS-CoV-2 in hospital outbreaks are complex; however multi-bedded rooms play a significant role in the transmission of SARS-CoV-2.
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Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep incisional/organ space) ...
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Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep incisional/organ space) SSIs case detection.This retrospective cohort study included adult patients (age ≥ 18 years) admitted to Calgary, Canada acute care hospitals who underwent primary total elective hip (THA) or knee (TKA) arthroplasty between Jan 1st, 2013 and Aug 31st, 2020. True SSI conditions were judged by the Alberta Health Services Infection Prevention and Control (IPC) program staff. Using the IPC cases as labels, we developed and validated nine XGBoost models to identify deep incisional SSIs, organ space SSIs and complex SSIs using administrative data, electronic medical records (EMR) free text data, and both. The performance of machine learning models was assessed by sensitivity, specificity, positive predictive value, negative predictive value, F1 score, the area under the receiver operating characteristic curve (ROC AUC) and the area under the precision–recall curve (PR AUC). In addition, a bootstrap 95% confidence interval (95% CI) was calculated.There were 22,059 unique patients with 27,360 hospital admissions resulting in 88,351 days of hospital stay. This included 16,561 (60.5%) TKA and 10,799 (39.5%) THA procedures. There were 235 ascertained SSIs. Of them, 77 (32.8%) were superficial incisional SSIs, 57 (24.3%) were deep incisional SSIs, and 101 (42.9%) were organ space SSIs. The incidence rates were 0.37 for superficial incisional SSIs, 0.21 for deep incisional SSIs, 0.37 for organ space and 0.58 for complex SSIs per 100 surgical procedures, respectively. The optimal XGBoost models using administrative data and text data combined achieved a ROC AUC of 0.906 (95% CI 0.835–0.978), PR AUC of 0.637 (95% CI 0.528–0.746), and F1 score of 0.79 (0.67–0.90).Our findings suggest machine learning models derived from administrative data and EMR text data achieved high performance and can be used to automate the detection of complex SSIs.
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Cardiac implantable electronic devices (CIED) are being inserted with increasing frequency. Severe surgical site infections (SSI) that occur after device implantation substantially impact patient morbidity and mortality and can re...
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Cardiac implantable electronic devices (CIED) are being inserted with increasing frequency. Severe surgical site infections (SSI) that occur after device implantation substantially impact patient morbidity and mortality and can result in multiple hospital admissions and repeat surgeries. It is important to understand the costs associated with these infections as well as healthcare utilization. Therefore, we conducted a population-based study in the province of Alberta, Canada to understand the economic burden of these infections.A cohort of adult patients in Alberta who had CIEDs inserted or generators replaced between January 1, 2011 and December 31, 2019 was used. A validated algorithm of International Classification of Diseases (ICD) codes to identify complex (deep/organ space) SSIs that occurred within the subsequent year was applied to the cohort. The overall mean 12-month inpatient and outpatient costs for the infection and non-infection groups were assessed. In order to control for variables that may influence costs, propensity score matching was completed and incremental costs between those with and without infection were calculated. As secondary outcomes, number of outpatient visits, hospitalizations and length of stay were assessed.There were 26,049 procedures performed during our study period, of which 320 (1.23%) resulted in SSIs. In both unadjusted costs and propensity score matched costs the infection group was associated with increased costs. Overall mean cost was $145,312 in the infection group versus $34,264 in the non-infection group. The incremental difference in those with infection versus those without in the propensity score match was $90,620 (Standard deviation $190,185). Approximately 70% of costs were driven by inpatient hospitalizations. Inpatients hospitalizations, length of stay and outpatient visits were all increased in the infection group.CIED infections are associated with increased costs and are a burden to the healthcare system. This highlights a need to recognize increasing SSI rates and implement measures to minimize infection risk. Further studies should endeavor to apply this work to full economic evaluations to better understand and identify cost-effective infection mitigation strategies.
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The objective of this review is to provide a comprehensive overview of the different types of economic evaluations that can be utilized by Infection Prevention and Control practitioners with a particular focus on the use of the qu...
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The objective of this review is to provide a comprehensive overview of the different types of economic evaluations that can be utilized by Infection Prevention and Control practitioners with a particular focus on the use of the quality adjusted life year, and its associated challenges. We also highlight existing economic evaluations published within Infection Prevention and Control, research gaps and future directions. Narrative Review. To date the majority of economic evaluations within Infection Prevention and Control are considered partial economic evaluations. Acknowledging the challenges, which include variable utilities within infection prevention and control, a lack of randomized controlled trials, and difficulty in modelling infectious diseases in general, future economic evaluation studies should strive to be consistent with published guidelines for economic evaluations. This includes the use of quality adjusted life years. Further research is required to estimate utility scores of relevance within Infection Prevention and Control.
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Background Infection Prevention and Control (IPC) surveillance for incident methicillin-resistant Staphylococcus aureus (MRSA) in hospitalized patients is performed in a complete provincial surveillance network of all acute care f...
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Background Infection Prevention and Control (IPC) surveillance for incident methicillin-resistant Staphylococcus aureus (MRSA) in hospitalized patients is performed in a complete provincial surveillance network of all acute care facilities in Alberta, Canada. IPC surveillance is centralized using a web-based data entry platform so that each patient is counted only once. All diagnostic laboratories submit the first clinical MRSA isolate associated with a patient without previous MRSA positive clinical cultures in the preceding year to the Provincial Laboratory for Public Health (ProvLab) for molecular typing. This study will investigate the relationship between the IPC epidemiological classification based on time of detection following admission to hospital (Hospital Acquired and Community Associated) and the matched laboratory MRSA surveillance data using a retrospective cohort study design. Methods Incident IPC MRSA cases were classified according to IPC epidemiologic definitions. DNA sequencing of the Staphylococcus protein A (spa) gene and pulsed-field gel electrophoresis (PFGE) typing was performed. IPC MRSA surveillance data were matched to the ProvLab molecular surveillance data. Univariate comparisons of proportions were performed for categorical variables and the Student’s t test for continuous variables. Results MRSA molecular typing data were available for matching for 46.7?% (2248/4818) of incident IPC cases. There was agreement in definitions for traditional nosocomial clones (USA100/CMRSA2) with Hospital Acquired (HA)-MRSA (65.1?% of all IPC HA-MRSA) and traditional community clones (USA400/CMRSA7 and USA300/CMRSA10) with Community Acquired (CA)-MRSA (62.4?% of CA-MRSA). However, we observed discordance for both traditional nosocomial/CA-MRSA (30.4?% of CA-MRSA) and for traditional community/HA-MRSA (26.9?% of HA-MRSA). Conclusions We note agreement between traditional nosocomial clones and HA-MRSA, and traditional community clones and CA-MRSA. However, approximately one-quarter of HA-MRSA are those of traditional community clones while approximately one-third of CA-MRSA are those of traditional nosocomial clones. Collaborative provincial MRSA surveillance is important as the distinction between IPC case attribution in acute care settings and the historical definitions of MRSA clones as community- or healthcare-associated have blurred.
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Background Fusobacterium species (spp.) bacteremia is uncommon and has been associated with a variety of clinical presentations. We conducted a retrospective, population based study to determine the relative proportion of species ...
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Background Fusobacterium species (spp.) bacteremia is uncommon and has been associated with a variety of clinical presentations. We conducted a retrospective, population based study to determine the relative proportion of species in this genus causing bacteremia and the risk factors for infection and adverse clinical outcomes. Methods All cases of Fusobacterium spp. bacteremia detected at a regional microbiology laboratory serving outpatient and acute care for a population of approximately 1.3 million people over 11?years were identified from a computerized database. Clinical data on these cases was extracted from an administrative database and analyzed to determine underlying risk factors for and outcomes of infection. Results There were 72 incident cases of Fusobacterium spp. bacteremia over the study period (0.55 cases/100,000 population per annum). F. nucleatum was the most frequent species (61%), followed by F. necrophorum (25%). F. necrophorum bacteremia occurred in a younger population without underlying comorbidities and was not associated with mortality. F. nucleatum bacteremia was found in an older population and was associated with underlying malignancy or receiving dialysis. Death occurred in approximately 10% of F. nucleatum cases but causality was not established in this study. Conclusions Fusobacterium spp. bacteremia in our community is uncommon and occurs in approximately 5.5 cases per million population per annum. F. necrophorum occurred in an otherwise young healthy population and was not associated with any mortality. F. nucleatum was found primarily in older patients with chronic medical conditions and was associated with a mortality of approximately 10%. Bacteremias from other Fusobacterium spp. were rare.
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