bluuebunny/crossref_metadata_2025_split huggingface dataset:
In Vitro Activity of Cefiderocol Against Multidrug-Resistant Gram-Negative Clinical Isolates
Authors: Boyd Sandra , Anderson Karen 
Published: November 2020

Background: New antimicrobials are being developed as a response to the global threat of multidrug-resistant and panresistant bacterial pathogens. Cefiderocol (FDC; Shionogi & Co) is a novel parenteral siderophore cephalosporin with activity against gram-negative rods. Here, we report on the in vitro activity of FDC against multidrug-resistant gram-negative isolates collected by the CDC, including isolates available through the CDC and FDA Antibiotic Resistance Isolate Bank (AR Isolate Bank). Methods: The challenge set of gram-negative isolates (n = 339), most of which were obtained from the AR isolate bank (n = 258), comprised 188 Enterobacteriaceae (ENT), 72 Pseudomonas aeruginosa (PSA), and 79 Acinetobacter baumannii (ACB). Minimum inhibitory concentrations (MICs) for FDC in iron-depleted cation-adjusted Mueller-Hinton broth were determined using frozen reference broth microdilution panels (IHMA, Schaumburg, IL) according to CLSI guidelines. Isolates displaying nonsusceptibility to FDC (MIC >4 µg/mL) underwent additional testing with β-lactamase inhibitors (FDC with 4 µg/mL avibactam, FDC with 100 µg/ml dipicolinic acid (DPA), and FDC with both 100 µg/mL dipicolinic acid (DPA) and 4 µg/mL avibactam). Results: Cefiderocol MICs ranged from ≤0.03 to >64 µg/mL, and 313 (92.3%) isolates displayed susceptibility to FDC (MIC ≤4 μg/mL). The proportions of susceptible ENT, PSA, and ACB were 93.1%, 94.4%, and 88.6%, respectively. Among isolates harboring Ambler class A, class B, or class D carbapenemases, the proportions of susceptible isolates were 96.5%, 79.5%, and 94.0%, respectively. Overall, 26 (7.7%) isolates were categorized as FDC nonsusceptible (MIC ≥ 8 µg/mL); 65% of these were NDM producers. We selected 23 isolates for testing with β-lactamase inhibitors. The combination FDC-avibactam reduced the MIC to susceptible for all isolates harboring an Ambler class A or D carbapenemase, except for 1 OXA-71–producing ACB and 1 KPC-producing Citrobacter farmeri. The combination FDC-DPA reduced the MIC to susceptible for 9 of 13 (69.2%) NDM-producing and 4 of 4 (100%) OXA-23–producing ACB. By combining FDC with both DPA and avibactam, the MIC was reduced to susceptible (91%) for all but 1 KPC-producing and 1 NDM-producing Enterobacteriaceae isolate. Conclusions: Cefiderocol (FDC) demonstrated potent activity against a diverse collection of multidrug-resistant, gram-negative isolates, including producers of Ambler class A, B, and D carbapenemases. Among the 26 FDC nonsusceptible isolates, 65% were NDM positive. Our data indicate that FDC combined with β-lactamase inhibitors may restore susceptibility in FDC nonsusceptible isolates. Additional studies are needed to understand the underlying mechanism(s) of FDC resistance and to further explore the use of β-lactamase inhibitors in combination with FDC.Funding: NoneDisclosures: None
Incidence and Risk Factors of Surgical Site Infection Following Pediatric Neurosurgery
Authors: Bergeron Corinne , Doyon-Plourde Pamela , Veronneau Chantal , Quach Caroline 
Published: November 2020

Background: Neurosurgeries are at high risk of surgical site infections (SSI), a complication associated with increased morbidity, mortality, and cost. Our aim was to measure SSI incidence and risk factors following pediatric neurosurgery at CHU Sainte-Justine, the provincial center for pediatric craniofacial surgery in Québec, Canada. Methods: Retrospective cohort study of all patients with elective neurosurgery performed at CHUSJ between October 2014 and October 2018. Medical records were reviewed to compare demographics, clinical presentations, and outcomes of patients. SSIs occurring within 30 days of a procedure without implant and up to 90 days with implant, were identified. SSI incidence was measured in patient years, and risk factors were assessed using univariate logistic regressions. Results: In total, 379 patients were included with an overall SSI incidence of 3.96 patient years. We found a higher SSI incidence in 2014–2015 compared to 2016–2018 (1.82 vs 4.83 patient years). The median age was 3.90 years, and cases seemed younger than controls (1.45 vs 4.15 years). No difference between groups was found for sex, body mass index, prematurity, and length of hospitalization. The proportion of deep SSIs was greater than superficial SSIs (53.3% vs 46.7%). Cases were more likely to present with a more severe ASA score, previous history of neurosurgery, neurological conditions, and pulmonary conditions than controls: OR, 3.90 (95% CI, 1.36–11.49); OR, 2.59 (95% CI, 0.88–7.40); OR, 2.77 (95% CI, 0.98–8.41), and OR, 3.21 (95% CI, 0.86–9.94), respectively. Among patients with history of neurosurgery, a higher proportion of cases experienced a cerebrospinal fluid leak (28.6% vs 2.2%). Most patients (85.8%) received preoperative prophylactic antibiotic. Of those, 49.3% were considered appropriate based on antibiotic and timing of administration. When antibiotic dosage was also considered, the number of patients who received an appropriate antibiotic therapy decreased radically. Conclusions: Patients with comorbidities, especially neurological and pulmonary conditions, are at higher risk of SSI after neurosurgery. We are currently working on a detailed analysis to explain the increase in SSI incidence after 2016. Finally, prophylactic antibiotic therapy needs to be improved and its impact on SSI rates needs to be monitored.Funding: NoneDisclosures: None
Interfacility Spread of OXA-23–Producing Carbapenem-Resistant Acinetobacter—Connecticut, 2018–2019
Authors: Jones Sydney , Maloney Meghan , Paranandi Anu , Pepe Dana , Nazarian Elizabeth , Morris Shannon , Christine Wagner , Bodnar Janine , Cummings Kailee , Leung Vivian 
Published: November 2020

Background: Carbapenem-resistant Acinetobacter baumannii (CRAB), a multidrug-resistant gram-negative bacterium, can cause difficult-to-treat infections with mortality in approximately half of CRAB cases. CRAB can spread among healthcare facilities after transfer of an infected or colonized patient. Strategies to limit CRAB spread include adherence to contact precautions, environmental cleaning with bleach, and screening to identify colonized patients. During July–September 2018, the Connecticut Department of Public Health (DPH) worked with an acute-care hospital (hospital A) to contain an outbreak of OXA-23–producing CRAB (OXA-23 is an enzyme that confers resistance to carbapenems). During November 2018–March 2019, statewide CRAB surveillance identified additional cases of related OXA-23–producing CRAB at other healthcare facilities. DPH, Connecticut State Public Health Laboratory (SPHL), and the Antibiotic Resistance Laboratory Network (ARLN) investigated to prevent additional cases. Methods: Since January 2017, CRAB isolates have been routinely sent to SPHL and ARLN for carbapenemase gene detection and whole-genome sequencing (WGS) to determine isolate relatedness. During November 2018–March 2019, DPH collected patient healthcare history for patients with CRAB isolates to identify outbreaks and provide assistance in infection control and prevention to healthcare facilities reporting CRAB cases. Beginning May 2019, DPH and ARLN offered facilities screening to identify patients colonized with OXA-23–producing CRAB. Results: Of 10 OXA-23–producing CRAB isolates reported to DPH during November 2018–March 2019, 3 were closely related to the 9 isolates from hospital A’s outbreak by WGS (single-nucleotide polymorphism difference range, 1–16). One isolate was from a patient who had been admitted to hospital A during July 2018. All 3 patients with CRAB isolates shared a history of residence at long-term–care facility A (LTCF A). Two patients received a CRAB infection diagnosis upon admission to hospital B after transfer from LTCF A. Both LTCF A and hospital B performed environmental cleaning with bleach and placed CRAB-identified patients on contact precautions. LTCF A declined screening patients for CRAB, whereas hospitals B and C, which receive frequent transfers from LTCF A, screened all patients on admission from LTCF A. During May–September 2019, among 6 patients screened, 1 was colonized with OXA-23–producing CRAB and was placed on contact precautions. Conclusions: Transfer of patients who are infected or colonized with CRAB among hospitals and LTCFs can facilitate the regional spread of CRAB. Strategies for containing the spread of carbapenemase-producing organisms include adherence to contact precautions, colonization screening, interfacility communication, and collaboration with public health.Funding: NoneDisclosures: None
Like a Bat Out of…. the Hospital? Development of a Bat Capture and Testing Protocol Prompted by Two Nosocomial Encounters
Authors: Kessler Michael , Shirley Daniel , Anderson Laura , Safdar Nasia 
Published: November 2020

Background: In the state of Wisconsin, 3%–4% of bats submitted for rabies testing are positive. Inpatient bat encounters at 2 affiliated healthcare facilities at nearly the same time were brought to the attention of the infection prevention and control (IPC) team. The first bat was captured in a patient room and was submitted for testing. Postexposure prophylaxis (PEP) was initiated for 1 patient before the bat testing results came back negative. The second bat was found in a transplant unit hallway and was released before we could request testing. We observed significant variations in responses, including decision to administer PEP and submission of bats for rabies testing. The IPC team developed a protocol to minimize unnecessary PEP, to prevent nosocomial rabies infection from bat exposure, and to limit associated panic. Methods: A systematic literature review of multiple databases was performed. A search of nonscientific articles using Google was also performed to assess unpublished inpatient bat encounters. A workgroup was established including IPC staff, physicians, and facilities management. The county animal services department and the state public health department veterinarian were consulted to aid in development of a protocol. Results: Literature review yielded a single report of a bat discovered in a neonatal intensive care unit (NICU). A lack of protocol resulted in PEP administration to 7 neonates without observed exposure after the bat was released instead of being submitted for testing. Of the first 100 articles retrieved via Google search of “bat in hospital,” 9 pertained to nosocomial discovery of bats in 5 different states over the past 7 years. Encounters included infestations requiring unit shutdowns and PEP administration. One tertiary-care referral center reported 10 encounters per year but did not elaborate on associated procedures. The county animal services staff assisted in training maintenance and engineering services (MES) personnel on how to secure bats for testing and helped develop a “bat kit” with protective gear and equipment to do so safely. In the new protocol, an inpatient bat encounter prompts personnel to capture the bat and begin an investigation into known or potential occult exposure. Known or potential exposures merit submission of the bat for rabies testing, the results of which guide PEP recommendations. All encounters are investigated for point of entry or roost. Conclusions: Inpatient bat encounters are not uncommon. Encounters should prompt systematic assessment for exposures and an investigation of the root cause. Following a protocol may limit unnecessary PEP administration, prevent nosocomial transmission of rabies from bat to patient, and attenuate associated anxiety.Funding: NoneDisclosures: None
Middle East Respiratory Syndrome Coronavirus, Saudi Arabia, 2017 Outbreak: Super-Spreading Event and Control Measures
Authors: Amer Hala 
Published: November 2020

Background: The hallmark of Middle East respiratory syndrome coronavirus (MERS-CoV) disease is the ability to cause major healthcare-associated outbreaks with superspreading events leading to massive transmission and excessive morbidity and mortality. This abstract provides overview of MERS-CoV multi-healthcare facilities outbreak in Riyadh in June 2017, with focus on cluster reported and the control measures taken at King Saud Medical City. The outbreak began with a patient who presented with acute renal failure requiring hemodialysis and became a MERS-CoV superspreader, igniting the cluster of cases in several hospitals in King Saud Medical City. Methods: For epidemiologic investigation, a case was defined as any patient with laboratory-confirmed MERS-CoV infection with connection to the affected healthcare facilities. Contact tracing and testing were performed according to the Ministry of Health (MOH) guidelines. MERS-CoV testing was recommended for HCWs who had unprotected close contact with a confirmed case. Considering the superspreading phenomena, contact tracing was included all persons attended the same area with the positive case either as a patient, an HCW, or a patient’s visitor or companion. Laboratory confirmation was conducted using real-time RT-PCR. Genome sequencing and phylogenetic analysis were performed for available MERS-CoV rRT-PCR–positive samples by the CDC. The infection control measures applied included decreasing patient load through downsizing emergency department acceptance, maintaining low elective services, limiting inpatient admissions, and encouraging discharge. Early detection and quarantining of any suspected cases took place through extensive contact tracing, properly triaging all patients upon admission, consistent monitoring of inpatients and HCWs for any emerging acute respiratory illness, allocation of more single rooms inside the facility and staff dormitory, and extending the services of virology laboratory to get timely results. Further measures consisted of extensive education on infection control practices, monitoring healthcare worker adherence, reassuring the public by maintaining transparency of published reports, and launching a hotline to respond to HCW concerns. Moreover, travel restrictions applied to any person with a history of exposure to a conﬁrmed MERS-CoV case during the 2-week monitoring period. Results: Overall, 44 cases of MERS-CoV infection were reported from 3 simultaneous clusters during the 2017 Riyadh outbreak, including 11 fatal cases. Among all of the cases, 29 cases were reported at King Saud Medical City. The outbreak at KSMC required 30 days to be controlled. Conclusions: High vigilance for early detection is a key control measure. To be more sensitive, point-of-care MERS-CoV testing is required because clinical suspicion is challenging in patients presenting with acute renal failure.Funding: NoneDisclosures: None
Minimum Healthcare Worker Influenza Immunization Rates Required to Decrease Influenza Transmission in Acute-Care Inpatients
Authors: Williams Victoria , Morgan Wendy , McGuire Maja , Katz Kevin , Leis Jerome 
Published: November 2020

Background:
Annual influenza immunization of healthcare workers (HCWs) is widely recommended to reduce the risk of healthcare-associated influenza (HAI). Although there is a clear association between higher HCW immunization and reduced incidence of HAI, data in acute care are lacking compared to the nursing home setting. Objective: Our goal was to assess the association between HCW influenza immunization and the incidence of HAI across 2 acute-care facilities. Methods: A multicenter prospective cohort study was undertaken at 2 acute-care hospitals including 1 university and 1 community-based academic hospital. Any patient prospectively identified with HAI was included between 2013–2014 and 2018–2019, whereas 2017–2018 was excluded due to vaccine mismatch. The HCW influenza immunization rate was defined as the proportion of HCWs (nurses and other allied and support staff but excluding physicians) immunized prior to December 15. A case of HAI was defined as laboratory-confirmed influenza A or B with symptom onset >72 hours after admission. The association between inpatient ward HCW influenza immunization rate and the incidence of HAI was compared using a Poisson regression analysis adjusting for hospital and influenza season. Results: Over 5 influenza seasons, the incidences of HAI at either facility were 0.24 and 0.22 per 1,000 patient days, whereas the median HCW influenza immunization rates were 57.3% (IQR, 42.5%–66.4%) and 66.6% (IQR, 50.6%–76.8%), respectively. When adjusting for hospital and influenza season in the multivariate analysis, HCW influenza immunization rates of 65% and 70% were not associated with HAI incidence. In contrast, HCW influenza immunization rates ≥75% was associated with a trend toward reduced HAI (IRR, 0.65; 95% CI, 0.39–1.08; P = .096) whereas inpatient wards above 80% immunization had significantly lower risk of HAI (IRR, 0.28; 95% CI, 0.089–0.89; P = .03). Conclusions: The risk of HAI across 2 acute-care hospitals was significantly lower among inpatient wards achieving HCW influenza immunization rates >80%. Acute-care facilities should aim for this minimum HCW immunization rate to protect patients from the complications of HAI.Funding: NoneDisclosures: None
National Trends of Incidence of Catheter-Associated Urinary Tract Infections in Acute-Care Hospitals
Authors: Soe Minn , Li Qunna , Nkwata Allan , Dudeck Margaret , Edwards Jonathan 
Published: November 2020

Background:
An indwelling urinary catheter is used in ~12%–16% of adult hospital inpatients during their hospitalization, which poses risks for acquiring a catheter-associated urinary tract infection (CAUTI). CAUTI data have been reported to the NHSN since 2005, and national benchmarks are annually reported in NHSN progress reports. Trends analyses in the incidence of CAUTI reported to the NHSN over long time have not been previously assessed. Objective: We investigated the national trends of CAUTI incidence separately for intensive care units (ICUs) and wards in acute-care hospitals (ACHs) from 2009 through 2018. Methods: We analyzed CAUTI data from ACHs reported to NHSN in 2009–2018. To evaluate trends of CAUTI incidence (per 1,000 catheter days), we conducted interrupted time-series analysis using negative-binomial mixed-effects modeling, separately for ICUs (nonneonatal ICUs) and wards. Due to the reporting requirement for adult and pediatric ICUs in 2012, and medical, surgical, and medical-surgical wards in 2015 by the CMS and the institution of the NHSN CAUTI definitional changes in 2015, calendar years 2012 and 2015 were treated as interruptions to the outcome in ICU models, and year 2015 was treated as a single interruption in the ward models. Regression models were assessed and adjusted, as appropriate, for patient care location type and facility-level characteristics such as hospital type, teaching status, bed size, number (and percentage) of ICU beds, and average length of inpatient stay. Random intercept and slope models were evaluated with covariance tests and were included to account for differential baseline incidence and trends among reporting hospitals. Results: The volume of patient care locations and hospitals reporting to the NHSN increased over time. Among the ICUs, the CAUTI incidence rate did not change in 2009–2012 and increased at an average of 5.6% per year in 2012–2014 (Fig. 1). CAUTI incidence rate dropped nearly 40% in 2015; thereafter, it decreased at an average of 8.9% per year. Among the wards, CAUTI incidence rate decreased at an average of 4.3% per year beginning 2009 (Fig. 2). The CAUTI incidence rate dropped almost 28% in 2015 and then decreased at an average of 4.3% per year. Conclusions: CAUTI incidence decreased substantially in 2015 among both ICUs and wards, which was partially attributable to CAUTI definitional change (see also Fig. 7 at https://www.cdc.gov/hai/data/archive/data-summary-assessing-progress.html). The significant decline of CAUTI incidence in both location types since 2015 is encouraging, and continued efforts in prevention of CAUTI are vital to sustaining this decline in the future.Funding: NoneDisclosures: None
Prediction of Surgical Risk in General Surgeries: Process Optimization Through Support Vector Machine (SVM) Algorithm
Authors: Souza Flávio , Couto Braulio , Silva Gabriel Henrique Silvestre da , Dias Igor Gonçalves , Rigueira Rafael Vieira Magno , Pimenta Gustavo Maciel , Martins Maurilio , Mendes Julio Cesar , Braga Gabriele Maria , Teixeira Jéssica Angelina , Santos Renata Carvalho , Martins Julia Maria Campos , Sousa Karla Silvia de , Souza Douglas Nascimento de , Alves Gustavo Barros , Rocha Vladimir Alexei Rodrigues 
Published: November 2020

Background: In 5 hospitals in Belo Horizonte (population, 3 million) between July 2016 and June 2018, a survey was performed regarding surgical site infection (SSI). We statistically evaluated SSI incidents and optimized the power to predict SSI through pattern recognition algorithms based on support vector machines (SVMs). Methods: Data were collected on SSIs at 5 different hospitals. The hospital infection control committees (CCIHs) of the hospitals collected all data used in the analysis during their routine SSI surveillance procedures; these data were sent to the NOIS (Nosocomial Infection Study) Project. NOIS uses SACIH software (an automated hospital infection control system) to collect data from hospitals that participate voluntarily in the project. In the NOIS, 3 procedures were performed: (1) a treatment of the database collected for use of intact samples; (2) a statistical analysis on the profile of the hospitals collected; and (3) an assessment of the predictive power of SVM with a nonlinear separation process varying in configurations including kernel function (Laplace, Radial Basis, Hyperbolic Tangent and Bessel) and the k-fold cross-validation–based resampling process (ie, the use of data varied according to the amount of folders that cross and combine the evaluated data, being k = 3, 5, 6, 7, and 10). The data were compared by measuring the area under the curve (AUC; range, 0–1) for each of the configurations. Results: From 13,383 records, 7,565 were usable, and SSI incidence was 2.0%. Most patients were aged 35–62 years; the average duration of surgery was 101 minutes, but 76% of surgeries lasted >2 hours. The mean hospital length of stay without SSI was 4 days versus 17 days for the SSI cases. The survey data showed that even with a low number of SSI cases, the prediction rate for this specific surgery was 0.74, which was 14% higher than the rate reported in the literature. Conclusions: Despite the high noise index of the database, it was possible to sample relevant data for the evaluation of general surgery patients. For the predictive process, our results were >0.50 and were 14% better than those reported in the literature. However, the database requires more SSI case samples because only 2% of positive samples unbalanced the database. To optimize data collection and to enable other hospitals to use the SSI prediction tool, a mobile application was developed (available at www.sacihweb.com).Funding: NoneDisclosures: None