Antimicrobial Susceptibility Data Research Articles

Phylotyping and Determining the Antimicrobial Susceptibility of Cutibacterium acnes Isolated from Patients with Acne Vulgaris

Cutibacterium acnes (formerly known as Propionibacterium acnes), obligate anaerobic gram-positive diphtheroid, is a member of normal skin microbiota and frequently isolated from acne lesions and also in various infections as an opportunist pathogen. Within the last decade, distinct phylogroups of C.acnes have been discovered, and specific strains associated with human disease were defined. Increasing resistance to antimicrobials used in the treatment of C.acnes infections has been reported. Resistance rates vary among isolates from different geographic locations. However, knowledge about the antimicrobial susceptibility patterns of C.acnes is limited in Turkey. Determining the phylotypes of C.acnes isolates and providing antimicrobial susceptibility data will be very useful in understanding the pathogenesis of the disease, preventing the development of resistance, and applying rational and effective empirical treatment. The aim of this study was to determine the phylotypes and antimicrobial susceptibility patterns of C.acnes and to investigate the relationship among C.acnes phylotypes, the severity of acne and the antimicrobial resistance. C.acnes isolates cultivated from the acne lesions of 57 patients who admitted to the dermatology outpatient clinic of our university hospital and from the skin of 62 healthy control group in a six-month period were included in the study. The acne lesions on the face and chest/upper back were given a score according to the Global acne grading system (GAGS) for describing the severity of acne. The severity was graded as mild if the score was 1-18, moderate with scores from 19 to 30, severe with scores from 31 to 38, and as very severe if the score is more than 39. The isolates were identified by using matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) . Phylotype analysis was performed by polymerase chain reaction (PCR) using specific primers. The minimum inhibitory concentrations (MICs) of clindamycin, erythromycin, azithromycin, tetracycline and doxycycline were determined by agar dilution technique recommended by Clinical and Laboratory Standards Institute (CLSI) for anaerobic bacteria. The majority of the isolates (patient; n= 47, control; n= 47) in both of the patient and control groups were phylotype IA, followed by type IB and type II, respectively and no type III C.acnes was detected. There was no correlation between acne severity and bacterial phylotypes. The resistance rates of clindamycin, erythromycin, azithromycin, tetracycline and doxycycline were found to be 22.8%, 29.8%, 35.2%, 3.5% and 5.3% in the acne patients group, respectively, whereas in the control group the incidence of resistance to these antimicrobials was 11.3%, 21%, 38.7%, 1.6% and 1.6%, respectively. There was no significant difference in antimicrobial resistance between the patient and control groups, except erythromycin (p= 0.043, Fisher's exact) as well as no relationship was found between antimicrobial resistance and phylotypes in both of the groups. The number of isolates, resistant to two or more antimicrobials, was higher in the patients with acne. C.acnes isolates were highly resistant to clindamycin, erythromycin and azithromycin. Type IA constituted the majority of the phylotypes. There was no significant relationship between C.acnes phylotype, antimicrobial resistance and acne severity.

Antimicrobial Susceptibility Sensitivity Pattern in Positive Urine Culture for Urinary Tract Pathogens from Tertiary Care Hospital

Hospital specific monitoring studies aims to determine the prevalence of the type of microorganisms that causes urinary infections and to assess the antimicrobial sensitivity pattern. A hospital based short term prospective cross-sectional study was conducted at Sagar Hospital, Bengaluru from August to October 2020. Antimicrobial susceptibility in MIC test was performed for the isolated pathogens by using automated VITEK compact method and stratification was done according to ICU and NON-ICU patients with over 260 urine culture tests of the suspected in-patient for urinary tract infection. All antimicrobial susceptibility data was analyzed using WHONET software 5.6. Sixty-six urine culture tests showed culture positive, 41 from non-ICU and 23 from ICU. Gram-negative bacilli E.Coli (61% in ICU, 52% IN non-ICU) was the most prevalent bacterium, followed by Klebsiella pneumoniae ss. pneumoniae (9% in ICU, 20% IN non-ICU), and Candida albicans 9% prevalence was seen only in ICU isolates. The study shows that the rate of resistance towards ampicillin (100%) was high among gram negative isolates and penicillin (100%) among gram positive isolates. The susceptibility was favorable towards polymixinB, colistin in gram negative organisms and nitrofurantoin, vancomycin in gram positive organisms. The present study revealed that E.Coli is the predominant bacterial pathogen. It also demonstrates there is an increasing resistance to ampicillin (88.2%) and ESBL (90%) among UTI pathogens. While, polymixin B (100%) and colistin was found most effective among gram negative and nitrofurantoin was most effective among gram positive organisms.
 Keywords: Antibiotic, antimicrobial resistance, urinary tract infection

The Bacterial Profile and Microbial Susceptibility of Acute and Chronic Dacryocystitis in Matini Hospital, Kashan, Iran

Background: Recent studies have shown an increasing incidence of antibiotic resistance in dacryocystitis. Management of diseases may include determining microbial agents and choosing appropriate antibiotics for treatment. Objectives: This study aimed to present the best treatments for dacryocystitis. To this end, specimens' microbiology and antibiotic susceptibility were examined in patients with dacryocystitis in the microbiology laboratory of the Kashan University of Medical Sciences. Methods: This cross-sectional study was performed on 172 patients presenting with acute and chronic dacryocystitis at the Matini Hospital, Kashan, between 2017 - 2018. Patient characteristics, culture isolates, and antimicrobial susceptibility data were collected. The PCR assay of the mecA gene was performed in all methicillin-resistant Staphylococcus isolates. Results: The most common bacteria were coagulase-negative staphylococci (CoNS), Staphylococcus aureus, Pseudomonas aeruginosa, and Acinetobacter baumannii. The majority of the isolated microbes were sensitive to rifampicin, linezolid, amikacin, and gentamicin. In Gram-negative bacilli, nine of the isolates were extended-spectrum beta-lactamase positive. The PCR test showed the frequency of mecA gene of resistant S. aureus and resistant CoNS isolates to be 40 and 46.3%, respectively. Conclusions: Coagulase-negative staphylococci were the most frequently isolated bacteria. The highest antibiotic susceptibility was observed to rifampin, linezolid, amikacin, and gentamicin. A high percentage of CoNS carried the mecA gene.

Machine Learning for Antibiotic Resistance Prediction: A Prototype Using Off-the-Shelf Techniques and Entry-Level Data to Guide Empiric Antimicrobial Therapy.

ObjectivesIn the era of increasing antimicrobial resistance, the need for early identification and prompt treatment of multi-drug-resistant infections is crucial for achieving favorable outcomes in critically ill patients. As traditional microbiological susceptibility testing requires at least 24 hours, automated machine learning (AutoML) techniques could be used as clinical decision support tools to predict antimicrobial resistance and select appropriate empirical antibiotic treatment.MethodsAn antimicrobial susceptibility dataset of 11,496 instances from 499 patients admitted to the internal medicine wards of a public hospital in Greece was processed by using Microsoft Azure AutoML to evaluate antibiotic susceptibility predictions using patients’ simple demographic characteristics, as well as previous antibiotic susceptibility testing, without any concomitant clinical data. Furthermore, the balanced dataset was also processed using the same procedure. The datasets contained the attributes of sex, age, sample type, Gram stain, 44 antimicrobial substances, and the antibiotic susceptibility results.ResultsThe stack ensemble technique achieved the best results in the original and balanced dataset with an area under the curve-weighted metric of 0.822 and 0.850, respectively.ConclusionsImplementation of AutoML for antimicrobial susceptibility data can provide clinicians useful information regarding possible antibiotic resistance and aid them in selecting appropriate empirical antibiotic therapy by taking into consideration the local antimicrobial resistance ecosystem.

In vitro antimicrobial susceptibility of clinical respiratory isolates to ceftazidime-avibactam and comparators (2016\u20132018)

BackgroundThis antimicrobial surveillance study reports in vitro antimicrobial activity and susceptibility data for a panel of agents against respiratory isolates of Enterobacterales and Pseudomonas aeruginosa.MethodsIsolates from respiratory specimens were collected in Africa/Middle East, Asia/South Pacific, Europe and Latin America between 2016 and 2018, as part of the Antimicrobial Testing Leadership and Surveillance (ATLAS) program. Broth microdilution methodology was used to quantify minimum inhibitory concentrations, from which rates of susceptibility were determined using EUCAST breakpoints (version 10). Rates of subsets with genes encoding β-lactamases (extended-spectrum β-lactamases [ESBLs], serine carbapenemases and metallo-β-lactamases [MBLs]) were also determined, as well as rates of multidrug-resistant (MDR) P. aeruginosa.ResultsAmong all respiratory Enterobacterales isolates, susceptibility to ceftazidime-avibactam, meropenem, colistin and amikacin was ≥94.4% in each region. For Enterobacterales isolates that were ESBL-positive or carbapenemase-positive/MBL-negative, ceftazidime-avibactam susceptibility was 93.6 and 98.9%, respectively. Fewer than 42.7% of MBL-positive Enterobacterales isolates were susceptible to any agents, except colistin (89.0% susceptible). Tigecycline susceptibility was ≥90.0% among Citrobacter koseri and Escherichia coli isolates, including all β-lactamase-positive subsets. ESBL-positive Enterobacterales were more commonly identified in each region than isolates that were ESBL/carbapenemase-positive; carbapenemase-positive/MBL-negative; or MBL-positive. Among all respiratory P. aeruginosa isolates, the combined susceptibility rates (susceptible at standard dosing regimen plus susceptible at increased exposure) were highest to ceftazidime-avibactam, colistin and amikacin (≥82.4% in each region). Susceptibility to colistin was ≥98.1% for all β-lactamase-positive subsets of P. aeruginosa. The lowest rates of antimicrobial susceptibility were observed among MBL-positive isolates of P. aeruginosa (≤56.6%), with the exception of colistin (100% susceptible). MDR P. aeruginosa were most frequently identified in each region (18.7–28.7%), compared with the subsets of ESBL-positive; carbapenemase-positive/MBL-negative; or MBL-positive isolates.ConclusionsRates of susceptibility among the collections of respiratory Enterobacterales and P. aeruginosa isolates were highest to ceftazidime-avibactam, colistin and amikacin in each region. Tigecycline was active against all subsets of C. koseri and E. coli, and colistin was active against all subsets of P. aeruginosa. The findings of this study indicate the need for continued antimicrobial surveillance among respiratory Gram-negative pathogens, in particular those with genes encoding MBLs.

Antimicrobial resistance in Shigella species: Our five years (2015–2019) experience in a tertiary care center in north India

PurposeShigella is the second leading cause of diarrhoeal mortality especially in children <5 years of age in African and Asian countries. Rapid changes are occurring in the epidemiology of shigellosis and Shigella are increasingly becoming highly drug resistant. To determine the serogroup distribution and antimicrobial resistance of Shigella isolated at our tertiary care centre in North India. MethodsA retrospective study was conducted where demographic details along with antimicrobial susceptibility data of Shigella isolated from stool specimens from 1st January 2015 till 31st December 2019 were retrieved from records and analyzed by WHONET 2019 software. ResultsShigella species was isolated in 1.31% (n = 137) of a total of 10,456 stool samples. Males predominated (n = 82; 59.8%) and majority of cases were admitted (n = 94; 68.6%). Children ≤5 years of age (n = 47; 34.3%) were the most commonly affected. Adults in the 21–40 age group contributed 27% of cases (n = 37). Overall, Shigella flexneri (n = 87; 63.5%) was the most common serogroup followed by non-agglutinable Shigella (n = 28; 20.4%) while Shigella sonnei (n = 12, 8.8%) and Shigella boydii (n = 9, 6.6%) fluctuated over the years. Shigella dysenteriae reappeared in 2019 after a hiatus of ten years. Overall, 45.3% (n = 62) of isolates were multidrug resistant to CLSI recommended drugs and high resistance was noted for ampicillin/amoxicillin (68.1%), cotrimoxazole (75.8%) ciprofloxacin (61.5%) and ceftriaxone/cefotaxime (45.2%). ConclusionsShigella have become highly drug resistant to fluoroquinolones and cephalosporins. Community based studies are required to truly assess the burden of AMR in India.

Characterization of Streptococcus pneumoniae detected in clinical respiratory tract samples in southern Sweden 2 to 4 years after introduction of PCV13

To determine the serotype distribution and antimicrobial resistance of Streptococcus pneumoniae associated with mucosal infections in patients of all ages, 2 to 4 years after the transition from a 10-valent pneumococcal conjugate vaccine (PCV10) to PCV13 in the childhood immunization programme. Background information and antimicrobial susceptibility data regarding all respiratory tract, middle ear, and conjunctival samples positive for growth of S. pneumoniae (n=2,131) were collected during 18 months in 2016-2018. Available corresponding bacterial isolates were serotyped by PCR and/or antisera (n=1,858). In total, 17% of isolates were covered by PCV13, predominantly represented by serotypes 3 (9%) and 19A (5%). The most common nonvaccine serotypes were 11A (10%), 23B (10%), 15A (6%) and 35F (5%). Isolates exhibiting serotype 15A or 23B were often multidrug-resistant (21%) or penicillin nonsusceptible (38%), respectively. The overall proportion of serotype 19A was halved compared to a previous observation period when PCV10 was used (years 2011-2013), suggesting herd protection related to PCV13. The proportion of serotype 3 was, however, unchanged. Despite most nonvaccine serotypes causing mucosal infections have a low invasive potential, certain antibiotic resistant serotypes may pose a clinical problem.

Klebsiella pneumoniae pneumonia in patients with rheumatic autoimmune diseases: clinical characteristics, antimicrobial resistance and factors associated with extended-spectrum \u03b2-lactamase production

BackgroundOver the past decades, Klebsiella pneumoniae (K. pneumoniae) infections have been increasing and affected immunocompromised patients nosocomially and communally, with extended-spectrum β-lactamase (ESBL) production becoming a major concern. Patients with rheumatic autoimmune diseases, mostly receiving immunosuppressive therapy, are vulnerable to various infections, including K. pneumoniae. However, few have investigated K. pneumoniae infections in this specific population. This study aimed to identify factors associated with ESBL production and mortality of K. pneumoniae pneumonia among patients with rheumatic autoimmune diseases in the Emergency Department.MethodsWe retrospectively investigated patients with rheumatic diseases who were diagnosed with K. pneumoniae pneumonia. The diagnosis of K. pneumoniae pneumonia was based on clinical manifestations, radiological findings and microbiological testing results. Prognostic factors and risk factors for ESBL production were determined with univariate and multivariate logistic regression analysis. Empirical therapy and antimicrobial susceptibility data were also collected.ResultsOf 477 K. pneumoniae pneumonia patients, 60 were enrolled into this study. The in-hospital mortality was 28.3%. Septic shock, ICU admission, the need for mechanical ventilation and change of antibiotics due to clinical deterioration, all related to mortality, were included as unfavorable clinical outcomes. Multivariate analysis suggested that ESBL production (OR, 6.793; p = 0.012), initial PCT ≥ 0.5 ng/ml (OR, 5.024; p = 0.033) and respiratory failure at admission (OR, 4.401; p = 0.046) predicted increased mortality. ESBL production was significantly associated with dose of corticosteroids (OR, 1.033; p = 0.008) and CMV viremia (OR, 4.836; p = 0.032) in patients with rheumatic autoimmune diseases. Abnormal leukocyte count (OR, 0.192; p = 0.036) was identified as a protective factor of ESBL-producing K. pneumoniae pneumonia. The most commonly used empirical antibiotic was ceftazidime, while most isolates showed less resistance to carbapenems and amikacin in susceptibility testing.ConclusionsK. pneumoniae pneumonia could be life-threatening in patients with rheumatic autoimmune diseases. Our findings suggested that ESBL production, initial PCT ≥ 0.5 ng/ml and respiratory failure at admission were independent factors associated with poor prognosis. Dose of corticosteroids and CMV viremia, predicting ESBL production in K. pneumoniae pneumonia, may help make individualized antibiotic decisions in clinical practice.

Characterization of antimicrobial-resistant Gram-negative bacteria that cause neonatal sepsis in seven low- and middle-income countries

Antimicrobial resistance in neonatal sepsis is rising, yet mechanisms of resistance that often spread between species via mobile genetic elements, ultimately limiting treatments in low- and middle-income countries (LMICs), are poorly characterized. The Burden of Antibiotic Resistance in Neonates from Developing Societies (BARNARDS) network was initiated to characterize the cause and burden of antimicrobial resistance in neonatal sepsis for seven LMICs in Africa and South Asia. A total of 36,285 neonates were enrolled in the BARNARDS study between November 2015 and December 2017, of whom 2,483 were diagnosed with culture-confirmed sepsis. Klebsiella pneumoniae (n = 258) was the main cause of neonatal sepsis, with Serratia marcescens (n = 151), Klebsiella michiganensis (n = 117), Escherichia coli (n = 75) and Enterobacter cloacae complex (n = 57) also detected. We present whole-genome sequencing, antimicrobial susceptibility and clinical data for 916 out of 1,038 neonatal sepsis isolates (97 isolates were not recovered from initial isolation at local sites). Enterobacterales (K. pneumoniae, E. coli and E. cloacae) harboured multiple cephalosporin and carbapenem resistance genes. All isolated pathogens were resistant to multiple antibiotic classes, including those used to treat neonatal sepsis. Intraspecies diversity of K. pneumoniae and E. coli indicated that multiple antibiotic-resistant lineages cause neonatal sepsis. Our results will underpin research towards better treatments for neonatal sepsis in LMICs.

#74: Development of a Solid-Organ Transplant-Specific Antibiogram in a Tertiary Pediatric Hospital in Canada

Abstract Background Solid-organ transplant (SOT) patients are more vulnerable to infections by antimicrobial-resistant organisms (AROs) because of their hospital exposure, compromised immune systems, and antimicrobial exposure. Therefore, it may be useful for transplant facilities to create transplant-specific antibiograms to direct empirical antimicrobial regimens and monitor trends in antimicrobial resistance. Methods SOT (i.e., lung, liver, renal, and heart) antibiograms were created using antimicrobial susceptibility data on isolates from 2012 to 2018 at The Hospital for Sick Children, a tertiary pediatric hospital and transplant center in Toronto, Ontario. The Clinical Laboratory Standards Institute (CLSI) guidelines were followed to generate the antibiograms. The first clinical isolate of a species from a patient in each year was included irrespective of body site; duplicates were eliminated and surveillance cultures were excluded. Results from 2 years of data were pooled on a rolling basis to achieve an adequate sample size in both SOT and hospital-wide antibiogram. The SOT antibiogram was then compared with the hospital-wide antibiogram of the compatible 2 pooled years from 2012 to 2018. For subgroup analyses in the SOT population, organ-specific antibiograms and transplant timing-specific antibiograms (pretransplant, post-transplant &amp;lt;1 year, and post-transplant ≥1 year) between transplant and sample collection dates were analyzed. All proportions were compared using the χ 2 test. Results The top 5 organisms in one (2 year) analysis period of the SOT antibiogram were Escherichia coli (n = 29), Staphylococcus aureus (n = 28), Pseudomonas aeruginosa (n = 20), Enterobacter cloacae complex (n = 18), and Klebsiella pneumoniae (n = 17). For E.coli, susceptibility in the SOT antibiogram was significantly lower than those in the hospital-wide antibiogram in 2017/2018 for ampicillin (27% vs. 48%; P = 0.015), piperacillin/tazobactam (55% vs. 87%; P &amp;lt; 0.001), cefotaxime (59% vs. 88%; P &amp;lt; 0.001), ciprofloxacin (71% vs. 87%; P = 0.007) and cotrimoxazole (41% vs. 69%; P &amp;lt; 0.001), but not significantly different for gentamicin (94% vs. 91%; P = 0.490), tobramycin (88% vs. 90%; P = 0.701) and amikacin (100% vs. 99%; P = 0.558). These findings were consistent throughout the study period in E.coli. There was no statistically significant difference between the SOT and hospital-wide antibiograms for other organisms. There were no significant differences in susceptibility between organ-specific antibiograms or transplant timing-specific antibiograms in 2012–2018. Conclusions We found that E.coli from the SOT population had a significantly lower sensitivity to all antimicrobials, except aminoglycosides, compared with those from the hospital-wide population. Other organisms had similar susceptibility to the hospital-wide population. Developing a SOT antibiogram will assist in revising and improving empiric treatment guidelines for this population.

Editorial: Coronavirus disease 2019 (COVID-19) - advances in epidemiology, diagnostics, treatments, host-directed therapies, pathogenesis, vaccines, and ongoing challenges.

Editorial: Coronavirus disease 2019 (COVID-19) - advances in epidemiology, diagnostics, treatments, host-directed therapies, pathogenesis, vaccines, and ongoing challenges.

Solid organ transplant-specific antibiogram in a tertiary pediatric hospital in Canada.

SOT recipients are more vulnerable to infections with antimicrobial-resistant organisms, and therefore, it may be useful for transplant centers to create transplant-specific antibiograms to direct empirical antimicrobial regimens and monitor trends in antimicrobial resistance. SOT-specific antibiograms were created using antimicrobial susceptibility data on isolates from 2012 to 2018 at The Hospital for Sick Children, Toronto, Ontario, Canada. The CLSI guidelines were followed to generate the antibiograms except that results from 2years of data were pooled on a rolling basis to achieve larger sample sizes. The 3 most frequent organisms in one analysis period of the SOT antibiogram wereEscherichia coli (average sample size ±standard deviation; n=28.7±3.8), Staphylococcus aureus (n=27.8±5.0), and Pseudomonas aeruginosa (non-CF) (n=19.8±8.8). For E.coli, susceptibilities in the SOT antibiogram were significantly lower than those in the hospital-wide antibiogram in 2017-2018 for ampicillin (27% vs 47%;p=.014), piperacillin/tazobactam (55% vs 88%;p<.001), cefotaxime (59% vs 89%;p<.001), ciprofloxacin (71% vs 88%;p=.007), and trimethoprim-sulfamethoxazole (41% vs 69%;p=.001), but not significantly different for aminoglycosides and meropenem.In the SOT antibiogram of E. coli, decreased susceptibility trend was confirmed in some antibiotics, including piperacillin/tazobactam (83% in 2012-2013 vs 55% in 2017-2018). At our center, the solid organ transplant-specific antibiogram revealed important differences inE. colisusceptibilities and trends in antimicrobial resistance. Developing a SOT antibiogram will assist in revising and improving empiric treatment guidelines as well as monitoring antimicrobial resistance in this population.

New guidelines for severe community-acquired pneumonia.

We highlight the recent advances in the guidelines for treating patients with severe community-acquired pneumonia (sCAP). sCAP is a significant cause of hospital admissions. We performed an extensive review of the literature, covering studies from the last several years, to summarise the most important points in the diagnosis and treatment of patients hospitalised with sCAP. sCAP is associated with a high clinical burden. Therefore, deep knowledge is necessary for its management. In general, diagnosis, treatment and management are based on many published guidelines. However, the mortality rate is still unacceptably high, indicating the need for clear recommendations in the management of patients with sCAP. The choice of empirical antibiotic therapy for sCAP depends on multiple factors, such as national and local antimicrobial susceptibility data and the characteristics of the patients, including their risk factors for acquiring infections caused by multidrug-resistant pathogens. Currently, there are several published international guidelines. The aim of this review is to explore the areas that require further knowledge and new recommendations for current clinical practice.

Use of Local Antibiogram Data and Antimicrobial Importance Ratings to Select Optimal Empirical Therapies for Urinary Tract Infections in Dogs and Cats.

International and Australian veterinary antimicrobial use guidelines recommend amoxicillin or trimethoprim-sulfonamide (TMS) for the empirical treatment of sporadic urinary tract infections (UTIs) in dogs and cats. However, in practice, these antibiotics are rarely used, and no large-scale analyses have examined the antibiograms of bacteria isolated from UTIs to validate these recommendations in Australia. We analyzed five years of urine culture and antimicrobial susceptibility data from an Australian veterinary laboratory. The analysis included 6196 urinary isolates from dogs and cats, 78% of which were from samples submitted by first-opinion veterinary clinics. Escherichia coli, Enterococcus faecalis, Staphylococcus pseudintermedius and Proteus spp. were the most prevalent organisms. More than 80% of all isolated cocci were susceptible to amoxicillin, and more than 80% of bacilli were susceptible to TMS. A total of 94% of isolates were susceptible to at least one antimicrobial drug categorized as low-importance in Australia. The prevalence of multi-drug resistance (MDR) was highest in E. coli, at 9.7%; 84% of these MDR isolates were susceptible to amoxicillin-clavulanate. We performed population-level antimicrobial treatment simulations and proposed a novel method for integrating antimicrobial importance ratings with antibiogram data to optimize the selection of empirical therapy. Our findings support current guideline recommendations to use amoxicillin or TMS. We also found that bacterial morphology assisted with selection; amoxicillin was a better choice for cocci and TMS for bacilli.

Innovation for a digital world: An evaluation of an open-access antimicrobial resistance surveillance system in tropical Australia

Background: Timely, accurate and accessible antimicrobial susceptibility data are essential for effective clinical and public health responses. In northern Australia, bacterial infection rates are high but resistance to antibiotics is poorly described. HOTspots (amrhotspots.com.au) is a regional, laboratory-based, passive surveillance system that aims to inform clinical management of patients, treatment guidelines and policies. Here we evaluate the utility of this prototype system to end users. Methods and materials: The evaluation was guided by the Centre for Disease Control's framework for evaluating public health surveillance systems. Evidence to assess the system attributes of simplicity, flexibility, acceptability, timeliness, and stability was collected through interviews with clinicians, guideline contributors and policy-makers. Data quality and sensitivity were determined by interviews and an audit of HOTspots data against available antimicrobial susceptibility data. Representativeness was analysed by comparing population coverage of participating and non-participating pathology service providers. Results: The system is simple in structure and operation but could be improved by standardising data collection from laboratories. The data management process facilitates system flexibility, but platform limitations are a barrier to the simplicity, flexibility and acceptability of the system. Acceptability was reduced by the inability to support nuanced clinical and public health decision-making, although enhanced by timely data provision. Future challenges to stability include sustainable governance, funding and human resourcing. Data completeness was high and validity good, though could be improved through quality assurance. The system was found to be sensitive, with an average 94.9% agreement between HOTspots data and local susceptibility data. Three major pathology service providers, who service public and private, hospital and community populations, have contributed data, establishing high quality representativeness of the system. Conclusion: HOTspots’ strength lies in its provision of timely, representative and accurate antimicrobial susceptibility data to end users in northern Australia. Recommendations to enhance the system include standardising data collection, upgrading the platform and working with end users to build more nuanced clinical and public health decision-making support. Sustainable governance and resourcing are essential to achieving this aim. Successful implementation of HOTspots into regional surveillance activities will innovate the way health services receive and act on changing patterns of antimicrobial resistance.

Early Detection and Prediction of Infection using Infrared Thermography

Helicobacter pylori infection causes gastritis and gastric ulcers and associated gastric cancer. Approximately 50% of the world's population H pylori infection. Developing countries with high prevalence rates. In most individuals, low socio economic means and infections are acquired during childhood. Affected family members at higher risk for childhood acquisi tion. The definitive routes of transmission are not clear evidence oral-oral, gastro-oral and fecal-oral routes of transmission. If left untreated, H pylori infection can last a lifetime. The disease is usually clinical and often occurs decades after the initial infection. H pylori infection can cause gastritis in children. Lesions, mucus-associated lymphoid lymphoma, and rarely, intes tinal metaplasia with/without gastric dysplasia.Synovial fluid aspirates were analyzed total knee arthroplasty by polymerase chain reaction in 50 patients with symptoms. Its presence indicates a bacterial infection called deoxyribonucleic acid. Syn ovial fluid samples were processed using a rapid bacterial degradation and extracts are amplified using protocol polymerase chain reaction and products analyzed including universal bacterial primers polymerase chain reaction deoxyribonucleic acid compound. A total of 32 samples were positive for bacterial infection with pre-polymerase chain reaction aspirates. We ana lyzed antimicrobial use in 509 episodes with microbiology laboratory report implications. Antibiotic stewardship. Most the rapeutic interventions occurred during phlebotomy and results by telephone after reporting gram stain release antimicrobial susceptibility data were limited impact on microbial management.A significant cause of hospitalization is leading to infection North America the second leading cause of death children and under after 1 year of malaria worldwide. Because of its global and human health impact, relatively few treatments exist. Paradoxically, there is a huge amount of information available on RSV replication during purification, RSV-induced mechanisms and social spread. RSV adds to the high burden of infection with existing chronic respiratory diseases.A major concern in clinical practice is vancomycin-resistant enterococci (VRE). Increased prevalence and their potential other bacteria to develop resistance to vancomycin (including methicillin-resistant Staphylococcus aureus) subjected them to closer scrutiny and intensive investigation. Colonialism was generally acquired high colonization rate of VRE in patients surrounding susceptible hosts.

Antimicrobial susceptibility of Neisseria gonorrhoeae in Barcelona during a five-year period, 2013 to 2017.

IntroductionIncreasing rates of antimicrobial resistance in Neisseria gonorrhoeae cause problems for treating gonorrhoea.AimThis observational study aimed to describe isolates from all patients found infected with N. gonorrhoeae, in Barcelona, Spain, between 2013 and 2017, and with available antimicrobial susceptibility data.MethodsMinimum inhibitory concentrations (MICs) of penicillin (PEN), cefixime (CFM), ceftriaxone (CRO), azithromycin (AZM), ciprofloxacin (CIP), spectinomycin (SPT), fosfomycin (FOF) and gentamicin (GEN) were determined by E-test. Susceptibility was assessed using clinical breakpoints from the European Committee on Antimicrobial Susceptibility Testing. Time trends for PEN, CFM, AZM and CIP were investigated using logistic regression.ResultsOf 1,979 patients with infection (2,036 isolates), 1,888 (95.4%) were men. Patient median age was 32 years. The proportions of isolates resistant to extended-spectrum cephalosporins were low, with 0.3% (5/1,982) resistant to CRO and 4.9% (98/1,985) to CFM. AZM resistance prevalence was 2.7% (52/1,981), including 16 isolates detected in 2016 and 2017, with high-level resistance. For CIP, 51.3% (1,018/1,986) of isolates were resistant, and for PEN, 20.1% (399/1,985). All isolates were susceptible to SPT. MIC50 and MIC90 values of GEN were 4 and 6 mg/L and of FOF 12 and 24 mg/L, respectively. Between 2013 and 2017, PEN and CFM resistance rates each decreased from 28.1% (92/327) to 12.2% (70/572) and from 8.3% (27/327) to 4.4% (25/572) (p ≤ 0.0073). In contrast, AZM resistance prevalence appeared to increase from 1.5% in 2014 (5/340) to 3.0% (17/572) in 2017. No trend was identified for CIP.ConclusionAntimicrobial susceptibility surveillance is important to timely detect new phenotypes and trends.

Antimicrobial stewardship in Australian hospitals: how does compliance with antimicrobial stewardship standards compare across key hospital classifications?

BackgroundThere is little information on the prevalence and type of antimicrobial stewardship (AMS) activities that are currently occurring in Australian hospitals.ObjectivesTo determine what AMS activities are currently occurring in Australian hospitals, identify gaps in compliance with the Australian Commission on Safety and Quality in Health Care (ACSQHC) standards and determine perceived barriers and enablers for implementing AMS programmes.MethodsA cross-sectional survey open to all Australian hospitals, conducted online and available to hospitals between November 2016 and July 2017.ResultsResponses were received from 254 hospitals. Compliance with ACSQHC AMS essential activities was high, except for essential activity 3 (post-prescription reviews), which was conducted by only 39% of respondent hospitals. Importantly, compliance varied by hospital remoteness classification for all activities except essential activity 1 (availability and endorsement of guidelines) and additional activity 4 (publishing antimicrobial susceptibility data annually), with major city hospitals having the highest compliance across all activities. The three most frequently reported barriers to implementing AMS programmes were a lack of training and education, lack of pharmacy resources and a lack of willingness from medical officers to change.ConclusionsDue to low response rates from certain hospital groups, the survey results are not generalizable to all Australia hospitals. This survey has identified that several gaps in compliance still exist and outlines the need to address lower AMS compliance in hospitals located outside major cities. The key barriers and enablers for AMS programme implementation identified should be used to inform future strategies.

Importance of Susceptibility Rate of 'the First' Isolate: Evidence of Real-World Data.

Background and objectives: For proper antimicrobial therapy, cumulative antibiograms should be representative of geographic region and be accurate. Clinical and Laboratory Standards Institute (CLSI) guidelines recommend that only the first isolates (FI) of a species per patient are used when reporting cumulative antibiograms. However, >50% of hospitals in the United States report antibiograms of all isolates. We compared antibiograms from the FI with those from total isolates (TI). Materials and Methods: Antimicrobial data of all isolates identified in the Microbiology unit of Ilsan Paik Hospital in 2019 were retrospectively acquired from the hospital information system. The susceptibility rates to antimicrobials of Escherichia coli, Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, Enterococcus faecium, and Enterococcus faecalis were analyzed by FI and TI, respectively. Isolate counts and susceptibility rates of each species for the reported antimicrobials were compared. Results: The numbers of isolates by FI/TI were as follows: 1824/2692 E. coli, 480/1611 A. baumannii, and 662/1306 K. pneumoniae, and 407/953 P. aeruginosa for gram-negative bacteria and 649/1364 S. aureus, 211/313 E. faecium, and 323/394 E. faecalis for gram-positive bacteria. All antimicrobial agents showed higher susceptibility rates when calculated as FI than as TI in gram-negative bacteria except colistin: 3.7% for E. coli, 14.5% for A. baumannii, 8.3% for K. pneumoniae, and 7.9% for P. aeruginosa. In S. aureus, 8/11 antimicrobial agents revealed higher susceptibility rates for FI than for TI. E. faecalis and E. faecium showed lower susceptibility rates for 7/10 antimicrobial agents for FI than for TI. The oxacillin susceptibility rates of S. aureus were 36.6%/30.2% with FI/TI and vancomycin susceptibility rates for E. faecium were 54.1% and 49.5%, respectively. Conclusions: When comparing cumulative antibiograms by FI with TI using real-world data, there is a large gap for critical species requiring hospital infection control. Although FI calculation is difficult, antibiograms must be calculated as FI for proper preemptive antimicrobial therapy because FI provides proper antimicrobial susceptibility data.

Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning

It is important that antibiotics prescriptions are based on antimicrobial susceptibility data to ensure effective treatment outcomes. The increasing availability of next-generation sequencing, bacterial whole genome sequencing (WGS) can facilitate a more reliable and faster alternative to traditional phenotyping for the detection and surveillance of AMR. This work proposes a machine learning approach that can predict the minimum inhibitory concentration (MIC) for a given antibiotic, here ciprofloxacin, on the basis of both genome-wide mutation profiles and profiles of acquired antimicrobial resistance genes. We analysed 704 Escherichia coli genomes combined with their respective MIC measurements for ciprofloxacin originating from different countries. The four most important predictors found by the model, mutations in gyrA residues Ser83 and Asp87, a mutation in parC residue Ser80 and presence of the qnrS1 gene, have been experimentally validated before. Using only these four predictors in a linear regression model, 65% and 93% of the test samples’ MIC were correctly predicted within a two- and a four-fold dilution range, respectively. The presented work does not treat machine learning as a black box model concept, but also identifies the genomic features that determine susceptibility. The recent progress in WGS technology in combination with machine learning analysis approaches indicates that in the near future WGS of bacteria might become cheaper and faster than a MIC measurement.