bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variations in Concurrent Central-Line Use Among Central-Line–Associated Bloodstream Infection (CLABSI) Patients by National Healthcare Safety Network (NHSN) Location Type
Authors: Dube William , Jacob Jesse , Robichaux Chad , Steinberg James , Fridkin Scott 
Published: November 2020

Background: Current NHSN denominator reporting for central-line–associated bloodstream infection (CLABSI) counts each patient day with n central lines as 1 central-line day. The NHSN does not directly adjust for potential increased risk of CLABSI from concurrent central lines, but the current NHSN standardized infection ratio (SIR) methods may account for differences in concurrence by adjusting for location type. Objective: We examined differences in central-line concurrence by NHSN location type among CLABSI patients. Methods: In a retrospective cohort of adults with CLABSI at 4 hospitals from 2012 to 2017, we linked central-line data to encounter and CLABSI data. Central lines were considered concurrent if they overlapped for >1 day. We calculated proportion of patients with concurrence at both NHSN location and SIR group levels; risk ratios for concurrence between NHSN location types within each SIR group (ie,, locations defined by SIR models as equal “risk”) were determined. Results: In total, 930 CLABIs were identified from 19 NHSN-defined locations that map to 7 SIR groups. Most CLABSIs occurred in locations mapped to either of 2 SIR groups: wards (227, 16% concurrence) and ICUs (294, 33% concurrence). The ward group had 3 NHSN locations (median, 78 CLABSIs) with concurrence range 8% (medical-surgical ward) to 20% (surgical ward). The ICU group had 6 NHSN locations (median, 47.5 CLABSIs) and concurrence ranged from 20% (neurosurgical ICU) to 39% (medical ICU). Despite the noted variations, no risk ratio was statistically different within each SIR group (Table 1). Conclusions: In patients with CLABSIs, the frequency of concurrence varied up to 2-fold between location types within the current NHSN SIR groups, though not statistically significantly. Assessing whether this difference in magnitude persists in all patients with central lines is an important next step in refining risk adjustment methods to account for concurrent central-line use.Funding: NoneDisclosures: Scott Fridkin reports that his spouse receives consulting fees from the vaccine industry.
Whole-Genome Sequencing Reveals Diversity of Carbapenem-Resistant Pseudomonas aeruginosa Collected Through the Emerging Infections Program
Authors: Stanton Richard , Daniels Jonathan , Breaker Erin , Campbell Davina , Lutgring Joseph , Karlsson Maria , Schutz Kyle , Jacob Jesse , Wilson Lucy , Vaeth Elisabeth , Li Linda , Lynfield Ruth , Phipps Erin C. , Hancock Emily , Dumyati Ghinwa , Tsay Rebecca , Cassidy P. Maureen , Mounsey Jacquelyn , Grass Julian , Walters Maroya , Halpin Alison 
Published: November 2020

Background: Carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a frequent cause of healthcare-associated infections (HAIs). The CDC Emerging Infections Program (EIP) conducted population and laboratory-based surveillance of CRPA in selected areas in 8 states from August 1, 2016, through July 31, 2018. We aimed to describe the molecular epidemiology and mechanisms of resistance of CRPA isolates collected through this surveillance. Methods: We defined a case as the first isolate of P. aeruginosa resistant to imipenem, meropenem, or doripenem from the lower respiratory tract, urine, wounds, or normally sterile sites identified from a resident of the EIP catchment area in a 30-day period; EIP sites submitted a systematic random sample of isolates to CDC for further characterization. Of 1,021 CRPA clinical isolates submitted, 707 have been sequenced to date using an Illumina MiSeq. Sequenced genomes were classified using the 7-gene multilocus sequence typing (MLST) scheme, and a core genome MLST (cgMLST) scheme was used to determine phylogeny. Antimicrobial resistance genes were identified using publicly available databases, and chromosomal mechanisms of carbapenem resistance were determined using previously validated genetic markers. Results: There were 189 sequence types (STs) among the 707 sequenced genomes (Fig. 1). The most frequently occurring were high-risk clones ST235 (8.5%) and ST298 (4.7%), which were found across all EIP sites. Carbapenemase genes were identified in 5 (<1%) isolates. Overall, 95.6% of the isolates had chromosomal mutations associated with carbapenem resistance: 93.2% had porinD-associated mutations that decrease membrane permeability to the drugs; 24.8% had mutations associated with overexpression of the multidrug efflux pump MexAB-OprM; and 22.9% had mutations associated with overexpression of the endogenous β-lactamase ampC. More than 1 such chromosomal resistance mutation type was present in 37.8% of the isolates. Conclusions: The diversity of the sequence types demonstrates that HAIs caused by CRPA can arise from a variety of strains and that high-risk clones are broadly disseminated across the EIP sites but are a minority of CRPA strains overall. Carbapenem resistance in P. aeruginosa was predominantly driven by chromosomal mutations rather than acquired mechanisms (ie, carbapenemases). The diversity of the CRPA isolates and the lack of carbapenemase genes suggest that this ubiquitous pathogen can readily evolve chromosomal resistance mechanisms, but unlike carbapenemases, these cannot be easily spread through horizontal transfer.Funding: NoneDisclosures: None
Effectiveness of Stewardship Intervention for Urinary Tract Infections in Primary Care: A Difference in Differences Study
Authors: Grigoryan Larissa , Germanos George , Zoorob Roger , Sidani Mohamad , Wang Haijun , Zare Mohammad , Goebel Melanie , Trautner Barbara 
Published: November 2020

Adherence to 2011 Infectious Diseases Society of America (IDSA) guidelines for urinary tract infections (UTIs) remains low in primary care. Fluoroquinolones are commonly prescribed to treat uncomplicated cystitis, and most antibiotic prescriptions have durations that exceed current recommendations. We performed a difference-in-differences study to assess the effectiveness of a stewardship intervention in a family medicine clinic at an academic outpatient center from August 2016 to March 2019. During our intervention period, the FDA released 2 additional warnings about the side effects of fluoroquinolones. Methods: The study had 2 sites (intervention and comparison) and 3 periods: baseline, before the intervention, and the intervention. During the first 2 years, we obtained baseline data and performed interviews (preintervention period) exploring provider prescribing decisions for cystitis at both sites. During the intervention period at the intervention site only, we presented an educational lecture including an overview of the IDSA guidelines, definitions for various UTI syndromes and actual clinical examples, and instruction on use of a decision aid. During the audit and feedback phase, providers were contacted once per month in person or by phone to provide follow-up on whether their treatment decision adhered to the IDSA guidelines. We performed a log-binomial regression analysis of the primary outcome, adherence to the IDSA guidelines for management of uncomplicated cystitis, both to antibiotic choice and duration of therapy. Results: We performed 156 audit-and-feedback sessions with 13 providers during the intervention period (March 2018–2019). Patients in both sites were similar in terms of age and Charlson comorbidity index. Adherence to the guidelines for antibiotic choice and duration increased in the intervention period at both sites (Fig. 1). The treatment of cystitis in the intervention period of the intervention site was 11.5 times (95% CI, 6.1–21.6) as likely to be guideline-adherent as the treatment in the baseline period of the comparison site (Fig. 2). Conclusions: Adherence to IDSA guidelines for the choice of antibiotic and duration increased in both intervention and comparison sites. Even though the intervention site started with higher compliance, improvement was also greater in the intervention site. FDA warnings about the side effects of fluoroquinolones released during the intervention period may have contributed to the avoidance of fluoroquinolones at both sites. Our intervention was effective at improving antibiotic choice and duration, so our future plans include incorporating our decision-support algorithm into the electronic medical record.Funding: This study was supported by Zambon Pharmaceuticals.Disclosures: None
Firefighters Fighting Germs - Evaluation of a Disinfecting Protocol for Use in the Fire Service
Authors: McGuire-Wolfe Christine 
Published: November 2020

Background: Pasco County Fire Rescue (PCFR) is a rapidly growing suburban fire department located in Florida. PCFR employs >500 firefighters (all cross-trained as either emergency medical technicians or paramedics) in 27 stations to provide both emergency medical services (EMS) and fire suppression response. Although multiple studies have established that pathogens are present in both apparatus and stations within the fire service, there is a knowledge gap regarding the effectiveness of cleaning and disinfecting protocols in this specific setting. Methods: In total, 65 high-touch surfaces in 11 vehicles (ambulances and engines) and common areas of 2 fire stations were swabbed before and after disinfection. Vehicle surfaces swabbed included seats, cabinet doors, door handles, stretchers, medical equipment, keyboard, steering wheels, shared headsets and hand rails. Inside the stations, the refrigerator handle, television remote, radio and alarm buttons, door handles, and locker handles were swabbed. Immediately following the initial swab collection, the surfaces were disinfected with hydrogen peroxide wipes and disinfectant cleaner sprayed through an electrostatic system. The same surfaces were then swabbed after disinfection. Colony-forming units (CFUs) were quantified using standard microbiological techniques by a third-party laboratory. Statistical analysis was performed on the resulting bacterial counts using Minitab version 18.1 software. Results: We detected statistically significant decreases in total bacteria, yeast, and mold counts following implementation of this disinfection protocol. The predisinfection mean of bacteria, yeast, and mold counts for all surfaces combined was reduced 96% after disinfection (from 254,637 CFU to 9,392 CFU). Conclusions: Cleaning and disinfection of surfaces in PCFR emergency vehicles and fire station common areas with the agents described above effectively reduced contamination with bacteria, yeast, and mold spores. The PCFR has implemented this disinfection protocol as a tool in eliminating EMS vehicles and the station environment as reservoirs of infection for patients, visitors, and firefighters. Future efforts will include assessing the impact of regular cleaning and disinfection on baseline levels of bacteria, yeast, and mold spores.Funding: This study was supported by Clorox.Disclosures: None
Influence of Antibiotic Susceptibility Testing on Antibiotic Choice in Hospital-Acquired and Ventilator-Associated Pneumonia
Authors: Zappernick Taissa , Christian Robbie , Sims Sharanie , Wilson Brigid , Perez Federico , Bonomo Robert , Jump Robin 
Published: November 2020

Background: The survival of patients with hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) is largely determined by the timely administration of effective antibiotic therapy. Guidelines for the treatment HAP and VAP recommend empiric treatment with broad-spectrum antibiotics and tailoring of antibiotic therapy once results of microbiological testing are available. Objective: We examined the influence of bacterial identification and antibiotic susceptibility testing on antibiotic therapy for patients with HAP or VAP. Methods: We used the US Veterans’ Health Administration (VHA) database to identify a retrospective cohort of patients diagnosed with HAP or VAP between fiscal year 2015 and 2018. We further analyzed patients who were started on empiric antibiotic therapy, for whom microbiological test results from a respiratory sample were available within 7 days and who were alive within 48 hours of sample collection. We used the antibiotic spectrum index (ASI) to compare antibiotics prescribed the day before and the day after availability of bacterial identification and antibiotic susceptibility testing results. Results: We identified 4,669 cases of HAP and VAP in 4,555 VHA patients. The median time from respiratory sample receipt in the laboratory to final result of bacterial identification and antibiotic susceptibility testing was 2.22 days (IQR, 1.31–3.38 days). The most common pathogen was Staphylococcus aureus (n = 994), with methicillin resistance in 58% of those isolates tested. The next most common pathogen was Pseudomonas spp (n = 946 isolates). The susceptibility of antipseudomonal antibiotics, when tested, was as follows: 64% to carbapenems, 74% to cephalosporins, 75% to β-lactam/β-lactamase inhibitors, 69% to fluoroquinolones, and 95% to amikacin. Lactose-fermenting gram-negative bacteria (296 Escherichia coli and 360 Klebsiella pneumoniae) were also common. Among the 3,094 cases who received empiric antibiotic therapy, 607 (20%) had antibiotics stopped the day after antibiotic susceptibility results became available, 920 (30%) had a decrease in ASI, 1,075 (35%) had no change in ASI, and 492 (16%) had an increase in ASI (Fig. 1). Among the 1,098 patients who were not started on empiric antibiotic therapy, only 154 (14%) were started on antibiotic therapy the day after antibiotic susceptibility results became available. Conclusions: Changes in antibiotic therapy occurred in at least two-thirds of cases the day after bacterial identification and antibiotic susceptibility results became available. These results highlight how respiratory cultures can inform the treatment and improve antibiotic stewardship for patients with HAP/VAP.Funding: This study was supported by Accelerate Diagnostics.Disclosures: None
Patient-Specific Predictive Antibiogram in Decision Support for Empiric Antibiotic Treatment
Authors: Sengupta Debarka , Singh Vaibhav , Singh Seema , Tewari Dinesh , Kapoor Mudit , Ghosh Debabrata , Sharma Shivam 
Published: November 2020

Background: The rising trend of antibiotic resistance imposes a heavy burden on healthcare both clinically and economically (US$55 billion), with 23,000 estimated annual deaths in the United States as well as increased length of stay and morbidity. Machine-learning–based methods have, of late, been used for leveraging patient’s clinical history and demographic information to predict antimicrobial resistance. We developed a machine-learning model ensemble that maximizes the accuracy of such a drug-sensitivity versus resistivity classification system compared to the existing best-practice methods. Methods: We first performed a comprehensive analysis of the association between infecting bacterial species and patient factors, including patient demographics, comorbidities, and certain healthcare-specific features. We leveraged the predictable nature of these complex associations to infer patient-specific antibiotic sensitivities. Various base-learners, including k-NN (k-nearest neighbors) and gradient boosting machine (GBM), were used to train an ensemble model for confident prediction of antimicrobial susceptibilities. Base learner selection and model performance evaluation was performed carefully using a variety of standard metrics, namely accuracy, precision, recall, F1 score, and Cohen &kappa;. Results: For validating the performance on MIMIC-III database harboring deidentified clinical data of 53,423 distinct patient admissions between 2001 and 2012, in the intensive care units (ICUs) of the Beth Israel Deaconess Medical Center in Boston, Massachusetts. From ~11,000 positive cultures, we used 4 major specimen types namely urine, sputum, blood, and pus swab for evaluation of the model performance. Figure 1 shows the receiver operating characteristic (ROC) curves obtained for bloodstream infection cases upon model building and prediction on 70:30 split of the data. We received area under the curve (AUC) values of 0.88, 0.92, 0.92, and 0.94 for urine, sputum, blood, and pus swab samples, respectively. Figure 2 shows the comparative performance of our proposed method as well as some off-the-shelf classification algorithms. Conclusions: Highly accurate, patient-specific predictive antibiogram (PSPA) data can aid clinicians significantly in antibiotic recommendation in ICU, thereby accelerating patient recovery and curbing antimicrobial resistance.Funding: This study was supported by Circle of Life Healthcare Pvt. Ltd.Disclosures: None
Similar Mortality in Patients with Invasive and Noninvasive Pneumonia Due to Group B Streptococcus
Authors: Wilson Brigid , Song Sunah , Zappernick Taissa , Briggs Janet , Banks Richard , Jump Robin , Perez Federico 
Published: November 2020

Background: Rates of invasive infections caused by caused group B Streptococcus (GBS) are increasing among adults. The burden of noninvasive GBS infections, including pneumonia, has not been well characterized. Here, we compare comorbidities and mortality associated with invasive and noninvasive pneumonia caused by GBS. Methods: Using the Veterans’ Health Administration national data warehouse, we studied a retrospective cohort review of veterans diagnosed with GBS pneumonia between 2008 and 2017. Invasive pneumonia was defined as blood cultures positive for GBS associated with an order for a chest x-ray and an International Classification of Disease (ICD) code for pneumonia. Noninvasive pneumonia was defined as a respiratory culture positive for GBS associated with both an order for a chest x-ray and an ICD code for pneumonia among patients with negative or without blood cultures. Patients with respiratory cultures positive for GBS without either an associated chest x-ray or ICD code for pneumonia were considered colonized. We compared demographics, comorbid conditions, and mortality among patients with invasive and noninvasive GBS pneumonia. Results: Between 2008 and 2017, we detected 706 cases of invasive GBS pneumonia, 1,244 cases of noninvasive GBS pneumonia, and 1,470 cases of respiratory colonization with GBS. Most patients were male (97%), with an average age of 69.0 years (SD, 12.0 years). The prevalence of several comorbid conditions differed between those with invasive and noninvasive disease: diabetes mellitus (61% and 46%, respectively); chronic pulmonary diseases (53% and 65%, respectively); chronic heart disease (58% and 44%, respectively), chronic kidney disease (43% and 27%, respectively). Mortality was similar among those with invasive and noninvasive GBS pneumonia at 30 days (17% and 18%, respectively) and at 1 year (38% and 43%, respectively) (Fig. 1). Conclusions: We identified important differences in underlying comorbid conditions between patients with invasive and noninvasive GBS pneumonia, which may give rise to differences in their clinical presentation. Overall mortality, however, was similar: more than one-third of patients with GBS pneumonia died within 1 year. These findings indicate that noninvasive GBS pneumonia is an important clinical entity.Funding: This study was supported by Pfizer.Disclosures: None
Surgical Site Infections with Predominance of Multidrug Resistant in Benin: A Multicenter Study
Authors: YEHOUENOU Carine Laurence , RODRIGUEZ-VILLALOBOS Hector , DALLEUR Olivia , SIMON Anne 
Published: November 2020

Background: Surgical site infections remain common and widespread; they contribute to increasing antimicrobial resistance among the etiological agents. Antimicrobial resistance is the ability of a microorganism like bacteria to stop an antimicrobial from working against it. This study was conducted to determine the spectrum of bacterial isolates from surgical site infections and their susceptibility patterns. A secondary outcome was to compare bacterial identification by a local lab and a European one. Methods: This descriptive cross-sectional study was conducted between January and August 2019 in 6 public hospitals in Benin. Pus specimens were processed using standard microbiological procedures, and identification was performed using the analytical profile index (API). Antimicrobial susceptibility testing was performed in Benin following the modified Kirby-Bauer disk-diffusion technique and was confirmed in Belgium by MALDI-TOF mass spectrometry. A second antimicrobial susceptibility test was performed using BD Phoenix automated microbiology system (Becton Dickinson). Clinical data of enrolled patients were obtained from hospital records. Results: The mean age of patients was 32 &plusmn; 11 years (range, 18–76). The median time for surgical site infections was 9 postoperative days. Of the 229 patients from whom wound swabs were collected, 195 (85.15%) showed positive aerobic bacterial growth. In total, 164 pathogenic bacteria were isolated, including 41 gram-positive organisms (25%), 78 gram-negative fermentative bacteria (47.5%), and 45 gram-negative nonfermentative bacteria (27.5%). We observed 3 discrepancies between API technique and MALDI-TOF. Two Klebsiella pneumoniae and 1 Pseudomonas spp (API) versus, respectively, Klebsiella varicola and Pseudomonas mendocina (MALDI-TOF). The most prevalent bacterial species were E. coli (31%), followed by S. aureus (25%), Pseudomonas aeruginosa (18%), and Klebsiella pneumoniae (11%). Of the 41 S. aureus, 26 (63,41%) were methicillin-resistant Staphylococcus aureus (MRSA), and 3 of these were carrying both MRSA and induced clindamycin resistance (ICR). Extended-spectrum β-lactamase (ESBL)–producing Enterobacteriaceae were observed in 60 of 78 isolates tested (77%). All of 2 Morganella morgannii and 89% of K. pneumoniae were ESBL producers. Conclusions: Among S. aureus, 2 of 3 were MRSA, whereas almost K. pneumoniae and E. coli were ESBL producers. Three strains are pan–drug resistant in nonfermentative bacteria, and no isolate was susceptible to all antibiotics. These findings are of high interest for better management of patients and control of antimicrobial resistance in Benin.Funding: This study was supported by Académie de Recherche pour l’Enseignement Supérieur (ARES).Disclosures: None