Advanced Expert System Research Articles

Antimicrobial Resistance Profile of Enterococcal Isolates From Clinical Specimens at a Tertiary Care Hospital in Western Maharashtra, India.

Background Enterococcus, once benign intestinal flora, has transformed into formidable nosocomial pathogens as a result of the accelerated emergence of antibiotic resistance represents a major global health challenge, particularly within hospital settings. Enterococcus has grown more prevalent in nosocomial infections, such as urinary tract infections (UTIs), surgical site infections (SSIs) and bacteremia. The potential emergence of vancomycin-resistant Enterococcus(VRE) strains further complicates treatment choices for multi-drug resistant (MDR) infections. This study evaluated the magnitude of Enterococcus infections and their antibiotic resistance patterns in a tertiary care hospital. Material and methods A laboratory-based cross-sectional study was conducted from January 2023 to December 2023 (one year) at Krishna Hospital & Medical Research Centre, Karad, India. A total of 189 enterococcalisolates were identified from various clinical specimens, including urine, blood, pus, and other samples. These isolates were subjected to identification and antimicrobial susceptibility testing using the automated VITEK 2 (bioMérieux SA, Marcy-l'Étoile, France) system.VanA and VanB phenotypes were detected based on minimum inhibitory concentration (MIC) values using the VITEK 2 Advanced Expert System (AES) system (bioMérieux SA). Statistical analysis was done using StatisticalPackage for the Social Sciences (IBM SPSS Statistics for Windows, IBM Corp., Version 21.0, Armonk,NY). Results Among 189 culture-positive enterococcal isolates, the majority were obtained from urine 144 (76%), followed by blood 17 (9%), pus 12 (6%), etc. A larger proportion of these isolateswere from femalepatients 97 (51%) aged over 60 years. A substantial proportion of these isolates originated from in-patient departments (IPD) 178 (94.2%) with intensive care units contributing the highest number 114 (60%) and out-patient departments (OPD) 11 (5.8%). The highest prevalence of infection was observed among patients with a hospital stay of 8 to 14 days (32.3%). E. faecium (57.7%) and E. faecalis (39.6%) were the predominant species with E. faecium displaying significant resistance to benzylpenicillin (96%) and nitrofurantoin (94%) whereas E.faecalis showed higher resistance to high-level gentamicin (80%). E. gallinarum (1.6%)showed complete resistance to benzylpenicillin (100%) and moderate resistance to nitrofurantoin (67%), and high-level gentamicin (67%). Conversely, E. durans showed complete resistance (100%) to both nitrofurantoin and benzylpenicillin. Among 31 VREisolates, 16 (52%) showed the VanA and 15 (48%) showed the VanB phenotype. Conclusion Antimicrobial resistance among E. faecium and E. faecalis, particularly to benzylpenicillin, high-level gentamicinand nitrofurantoinalong with the emergence of resistant species like E. durans and E. gallinarum underscores the urgent need for vigilant antimicrobial stewardship and continuous surveillance of the growing threat of MDRenterococci in clinical settings.

Enhancing gas drainage and ventilation efficiency in underground coal mines: A hybrid expert decision approach for booster fan prioritization

Expanding mining operations in goaf zones heightens gas production potential, posing challenges in maintaining adequate ventilation within development panels, consequently impacting coal production. Various strategies have been explored to enhance mine ventilation and gas drainage effectiveness. However, deficiencies persist in the proposed ventilation system for the Okaba underground coal mine, prompting this study’s necessity. Addressing these concerns, the study evaluates the feasibility of employing booster fans to mitigate the identified drawbacks. Prioritizing booster fans for airflow distribution in underground mines is a complex decision-making process, requiring an advanced expert system approach. To address this, the study proposes an intuitionistic-based fuzzy TOPSIS (IFT) method for booster fan prioritization in the Okaba mine. Results indicate that booster fan 4 (BF4) ranks highest, followed by booster fan 3 (BF3), consistent with fuzzy TOPSIS findings. Sensitivity analysis supports the predicted importance order, affirming the efficacy of the hybrid expert decision method in selecting a booster fan capable of enhancing the overall efficiency of gas drainage and ventilation systems in underground mines. This study introduces a Hybrid Expert Decision Approach that integrates IFT and traditional fuzzy TOPSIS methodologies. This hybrid approach is particularly novel because it combines the strengths of both methods to prioritize booster fans in underground coal mines.

Detection of drug-resistant phenotypes among gram-negative bacterial isolates using Vitek 2 Advanced expert system (AES)

Detection of drug-resistant phenotypes among gram-negative bacterial isolates using Vitek 2 Advanced expert system (AES)

An Advanced Explainable Belief Rule-Based Framework to Predict the Energy Consumption of Buildings

The prediction of building energy consumption is beneficial to utility companies, users, and facility managers to reduce energy waste. However, due to various drawbacks of prediction algorithms, such as, non-transparent output, ad hoc explanation by post hoc tools, low accuracy, and the inability to deal with data uncertainties, such prediction has limited applicability in this domain. As a result, domain knowledge-based explainability with high accuracy is critical for making energy predictions trustworthy. Motivated by this, we propose an advanced explainable Belief Rule-Based Expert System (eBRBES) with domain knowledge-based explanations for the accurate prediction of energy consumption. We optimize BRBES’s parameters and structure to improve prediction accuracy while dealing with data uncertainties using its inference engine. To predict energy consumption, we take into account floor area, daylight, indoor occupancy, and building heating method. We also describe how a counterfactual output on energy consumption could have been achieved. Furthermore, we propose a novel Belief Rule-Based adaptive Balance Determination (BRBaBD) algorithm for determining the optimal balance between explainability and accuracy. To validate the proposed eBRBES framework, a case study based on Skellefteå, Sweden, is used. BRBaBD results show that our proposed eBRBES framework outperforms state-of-the-art machine learning algorithms in terms of optimal balance between explainability and accuracy by 85.08%.

Performance of the Vitek 2 Advanced Expert System (AES) as a Rapid Tool for Reporting Antimicrobial Susceptibility Testing (AST) in Enterobacterales from North and Latin America.

This study evaluated the performance of the Vitek 2 Advanced Expert System (AES) confidence level report as a rapid tool for reporting antimicrobial susceptibility testing (AST) results for a challenging set of Enterobacterales isolates from North and Latin America. Enterobacterales isolates (n = 513) were tested by CLSI broth microdilution (BMD) and Vitek 2 (N802 and XN15 AST cards). Wild-type isolates and isolates harboring acquired β-lactamases by whole-genome sequencing were included. The AES assessment of confidence level (green, yellow, and red reports) was compared to BMD results and known genotypes and reviewed by a microbiologist for accuracy. Totals of 148 (28.8%) wild-type isolates and 365 (71.2%) Enterobacterales isolates harboring carbapenemase (211 [41.1%]), extended-spectrum β-lactamase (ESBL) (122 [23.8%]), and/or transferrable AmpC (tAmpC) (32 [6.2%]) genes were evaluated. The AES confidence level was assessed for 488 isolates, and a phenotype was recognized for 447 (91.6%) isolates. Green, yellow, and red AES reports were noted for 382 (78.3%), 65 (13.3%), and 41 (8.4%) isolates, respectively. Compared to BMD, 96.3% of green AES reports could be confidently and rapidly auto-released, enabling rapid adjustments to antimicrobial therapy. In addition, 69.2% of yellow reports were acceptable, and recommendations to address current AES limitations were made. IMPORTANCE Antimicrobial susceptibility testing (AST) reports are one of the most important clinical microbiology laboratory tasks. AST reports are essential to drive antimicrobial therapy, provide information to monitor antimicrobial resistance rates, and trigger further tests to detect outbreaks or confirm new mechanisms of resistance. Commercial AST devices are frequently used to generate AST reports, and an advanced expert system (AES), such as the Vitek 2 AES, incorporates extensive knowledge to recognize certain susceptibility patterns as indicative of specific phenotypes. Moreover, the Vitek 2 AES also provides a level of confidence for auto-releasing the reports. In this study, the performance of the Vitek 2 AES was compared to state-of-the-art methodologies for AST, broth microdilution and β-lactamase gene detection, whole-genome sequencing, against a collection of 513 Enterobacterales clinical isolates harboring various β-lactamase genes, including carbapenemase, ESBL, and transferrable AmpC genes, from 73 medical centers in 7 countries in North and Latin America.

Machine Learning-Based Classification Models for Diagnosis of Diabetes

Introduction: The goal of this study is to expand the diabetes decision-making framework through the advancement of computational intelligence. Several artificial network and machine- learning-based methods have been developed and validated, most of which are based on the Pima Indian dataset. So far, no method has reached an accuracy of 99-100%. Various tools such as Machine Learning (ML) and Data Mining are used for the correct identification of diabetes. These tools improve the diagnostic process associated with T2DM. Diabetes mellitus type 2 (DMT2) is a major problem in several developing countries, and its early diagnosis can save several people’s lives. Accordingly, we have to build a structure that diagnoses type 2 diabetes. This paper proposes a fuzzy expert system that uses the Mamdani fuzzy inference structure (MFIS) to diagnose type 2 diabetes accurately. The proposed research work has been created using a variety of machine learning algorithms such as J48 Decision-tree (DT), Multilayer perceptron (MLP), Support-vector-machine (SVM), Naive-Bayes (NB), Fusion, and Mixed fusion-based. Actual data from the UCI machine learning datasets are used to validate the advanced Fuzzy expert system (FES) and machine learning algorithms. Objective: A review of recent advances in machine learning-based classification models for diabetes diagnosis is presented in this survey paper. Methods: This paper compares modified fusion processes to fundamental models such as radial basis function, K-nearest neighbor, support vector machine, J48, logistic regression, classification, regression trees, etc., for diagnosing type 2 diabetes. Results: Figs. 3 and 4 show the results for each classifier based on prediction accuracy. Conclusion: The fuzzy expert system is the best among its rival classifiers. SVM performs very poorly with a very low true positive rate, i.e., a very high number of positive cases misclassified as (non-diabetic) negative. Based on the evaluation, it is clear that the fuzzy expert system has the highest precision value. However, J48 is the least accurate classifier. Compared to the other classifiers listed in the testing section, it has the greatest number of false positives. The results show that the fuzzy expert system has the uppermost cost for both precision and recall. Thus, it has the uppermost value for F-measure in the training and testing datasets. J48 is considered the secondbest classifier for the training dataset, whereas Naïve Bayes comes in the second rank in the testing dataset.

Non-Alcoholic Pearl Millet Beverage Innovation with Own Bioburden: Leuconostoc mesenteroides, Pediococcus pentosaceus and Enterococcus gallinarum.

The appropriate solution to the problem of quality variability and microbial stability of traditional non-alcoholic pearl millet fermented beverages (NAPMFB) is the use of starter cultures. However, potential starter cultures need to be tested in the production process. We aimed to identify and purify bioburden lactic acid bacteria from naturally fermented pearl millet slurry (PMS) and assess their effectiveness as cultures for the production of NAPMFB. Following the traditional Kunun-zaki process, the PMS was naturally fermented at 37 °C for 36 h. The pH, total titratable acidity (TTA), lactic acid bacteria (LAB), total viable count (TVC) and the soluble sugar were determined at 3 h interval. The presumptive LAB bacteria were characterized using a scanning electron microscope, biochemical tests and identified using the VITEK 2 Advanced Expert System for microbial identification. The changes in pH and TTA followed a non-linear exponential model with the rate of significant pH decrease of 0.071 h−1, and TTA was inversely proportional to the pH at the rate of 0.042 h−1. The Gompertz model with the mean relative deviation modulus, 0.7% for LAB and 2.01% for TVC explained the variability in microbial growth during fermentation. The LAB increased significantly from 6.97 to 7.68 log cfu/mL being dominated by Leuconostoc, Pediococcus, Streptococcus and Enterococcus with an optimum fermentation time of 18 h at 37 °C and 4.06 pH. L. mesenteroides and P. pentosaceus created an acidic environment while E. gallinarum increased the pH of the pearl millet extract (PME). Innovative NAPMFB was produced through assessment of LAB from PMS to PME fermented with L. mesentoroides (0.05%) and P. pentosaceus (0.025%) for 18 h, thereby reducing the production time from the traditional 24 h.

Evaluation of the VITEK 2 Advanced Expert System performance for predicting resistance mechanisms in Enterobacterales acquired from a hospital-based screening program.

There is limited literature examining the accuracy of the VITEK 2 Advanced Expert System (AES) in characterisation of β-lactamase resistance patterns. We present a prospective single centre study to better ascertain the performance characteristics of this program. The VITEK 2 AES interpretation was compared to established laboratory phenotypic methods. The overall sensitivity for detection of broad-spectrum β-lactamase by the AES was 95%, with a specificity of 78%. One or more discrepancies were noted in 36% of samples, with the majority of these (87/100) due to incorrect 'overcall' of a resistance mechanism. AES characterisation of AmpC resistance mechanisms was excellent. In contrast, the AES had poor specificity in classifying extended spectrum β-lactamases (ESBLs). As a screening aid, the AES can be a valuable tool. However, optimal use requires an adequate working knowledge of resistance mechanisms in order to correctly interpret and accept the result output.

Surveillance of plasmid-mediated mcr-1, mcr-3, mcr-4 and mcr-5 genes in human isolates, in Aveiro, Portugal

Background: Colistin belongs to polymyxins family, with broad-spectrum activity against Gram-negative bacteria, including most Enterobacteriaceae and it is considered last resource for Multidrug resistant (MDR) or Extensively drug-resistant phenotype therapy. The emergence of colistin resistance has caused great concern and resistance mediated by the plasmid-borne mcr genes has been detected worldwide. The aim of this study was to evaluate the presence of mcr-like genes in strains from patients attending the Centro Hospitalar do Baixo Vouga, E.P.E., Portugal. Methods and materials: All isolates included in this study were non-duplicate and identified with the automated method VITEK2® (BioMèrieux, France), antimicrobial susceptibility testing was performed, and the advanced expert system suggestions were taken in consideration. Strains identified as colistin-resistant were confirmed by MICRONAUT-S broth microdilution Colistin MIC test (Merlin Diagnostika). The NG-Test MCR-1 (NG, Biotech, France), was used to detect the presence of the MCR-1 enzyme. Polymerase chain reaction technique was used to screen the presence of the colistin resistance plasmid-mediated mcr-1, mcr-3, mcr-4 and mcr-5 genes using primers described previously. The presence of IncX4 replicon was inspected in all mcr-like-carrying strains. Results: During the timeframe of this study (2017–2019) a total of 6189 strains were isolated, among them 13 exhibited non-intrinsic resistance to colistin (six Klebsiella pneumoniae, four Escherichia coli, two Enterobacter cloacae and one Pseudomonas aeruginosa). Seven strains were recovered from inpatients and six from outpatient samples. Patients age range from 56 to 89 years-old. mcr-1 gene was detected in two strains from patients from orthopedics ward - Escherichia coli (Ec536586) and Klebsiella pneumoniae (Kp574799). IncX4 plasmid was not detected in strains. Conclusion: Resistance in most of the strains included in this study could not be explained by the presence of mcr-1 gene. One can hypothesize that it may be due to chromosomal mutations that have already been described in Enterobacteriaceae and also in P. aeruginosa. Further studies will be undertaken to screen for the presence of other acquired genes. Since the prevalence rate of carbapenem-resistant Enterobacteriaceae has been increasing in our region, we highlight the importance of a Surveillance Program to monitor the spread of the plasmid-mediated colistin resistance genes into MDR Gram-negative bacteria.

Manufacturability assessment in assembly processes

In this paper, there is presented the problem of assessing the manufacturability of complex products at the design stage of the manufacturing process considering the criterion of execution of assembly operations processes and production costs. Assessment of manufacturability was given on the example of the Boothroyd & Dewhurst method. This paper describes how to estimate the times and costs of assembly operations according to the mentioned above criteria with the use of the expert system. The presented example illustrates its practical application. The method of analysis presented in this article, developed by the authors, will be the subject of further research aimed at creation of an advanced expert system supporting the design of assembly systems.

A Simple Method for Direct Detection and Discrimination of <i>A. baumannii</i> in Tracheal Aspirates without Culture Isolation

Currently, available phenotyping and commercial methods report A. baumannii only as Acinetobacter calcoaceticus-baumannii complex (ACB) and do not identify individual members of the complex. This is a single blind study aimed to evaluate certain commonly used species-specific genetic markers namely, Intergenic Transcribed Spacer region in 16S rRNA of A. baumannii (Ab-ITS) and gyrB, for identification of ACB members. These molecular targets were first validated on clinical isolates (n = 200) and subsequently on uncultured tracheal aspirates (n = 172). Among the clinical isolates, 183/200 (91.5%) were positive for Ab-ITS. The clinical isolates 17 (17/200) which are failed to amplify in Ab-ITS PCR were subsequently diagnosed by gyrB PCR as A. calcoaceticus (n = 2), A. pitti (n = 6) and A. nosocomialis (n = 9) but not A. baumannii. Among the tracheal aspirates, 62 samples were reported as sterile in Advanced Expert System of VITEK-2, among the remaining 110 samples, 68.1% (75/110) samples contained Ab-ITS target. Twenty-five of the sterile samples (25/62) were found to contain Ab-ITS target sequence. Since, our sample processing method enabled identification of all the species of ACB complex by PCR even in uncultured tracheal aspirates, adaptation of our protocol would enable same day (6 - 8 h) reporting and help the clinician make evidence based therapeutic decision quickly.

Clonal expansion of colistin-resistant Acinetobacter baumannii isolates in Cape Town, South Africa

ObjectivesTo describe colistin-resistant Acinetobacter baumannii isolates in Cape Town, South Africa. MethodsA. baumannii isolates identified on Vitek 2 Advanced Expert System were collected from Tygerberg Hospital referral laboratory between 2016 and 2017. Colistin resistance was confirmed using broth microdilution and SensiTest. mcr-1–5 were detected using PCR and strain typing was performed by rep-PCR. Whole genome sequencing (WGS) was performed on a subset of isolates to identify chromosomal colistin resistance mechanisms and strain diversity using multilocus sequence typing (MLST) and pairwise single nucleotide polymorphism analyses. ResultsTwenty-six colistin-resistant and six colistin-susceptible A. baumannii were collected separately based on Vitek susceptibility; 20/26 (77%) were confirmed colistin-resistant by broth microdilution. Four colistin-resistant isolates were isolated in 2016 and 16 in 2017, from five healthcare facilities. Thirteen colistin-resistant isolates and eight colistin-susceptible isolates were identical by rep-PCR and MLST (ST1), all from patients admitted to a tertiary hospital during 2017. The remaining colistin-resistant isolates were unrelated. ConclusionsAn increase in colistin-resistant A. baumannii isolates from a tertiary hospital in 2017 appears to be clonal expansion of an emerging colistin-resistant strain. This strain was not detected in 2016 or from other hospitals. Identical colistin-susceptible isolates were also isolated, suggesting relatively recent acquisition of colistin resistance.

Surveillance of ESBL-producers causing UTIs over a 6 year period

Background: Urinary tract infections (UTIs) are one of the most prevalent community-acquired infections. ESBL-producing microorganisms are a growing threat to public health, and their presence among the community is spreading. The aim of this study was to access the prevalence of ESBL-producing isolates collected from urine of elderly attending the Emergency Room (ER) during a 6 year period (2011-2016). Methods & Materials: Bacterial strains were isolated from patients with primary diagnose UTI, older than 65 years, in the ER between 2011 and 2016. The Vitek2 system (according to EUCAST 2014 guidelines) and Advanced Expert System (BioM~rieux, Marcy L'toile, France) were used to identify and perform the antibiotic susceptibility profile of the isolates. ESBL production was confirmed using the Etest(r) (AB Biodisk) method, according to the manufacturer instructions. Results: 2925 samples were collected following the criteria listed above. The percentage of Escherichia coli isolates has been increasing since 2011, up to 51,7% in 2016, and the percentage of Klebsiella pneumoniae, which in 2011 was higher than E. coli, has been significantly decreasing in the last years, to around 15%. A reduction in the percentage of ESBL-producers until 2013 was noted, from where there has been an increase, both among E. coli and K. pneumoniae. In 2011, 82,5% of K. pneumoniae were ESBL-producers, and progressively decreases until 2015 to 32,5%. But a slightly increase in 2014 and 2016 (44,1% and 51,2%) shows the tendency of ESBL-producing K. pneumoniae spread in the community. E. coli ESBL-producers have also progressively diminished until 2013, then exhibiting an increase up to 24,0% in 2016. Conclusion: Considering the criteria used, we can conclude that they are carried by the patients who attend the ER repeatedly, thus spread in the community. Despite ESBL-producers have been significantly reduced in the last years, results show a possible increasing tendency. The same is observed both for E. coli and K. pneumoniae isolates, where the decrease in ESBL-producers until 2013 is now being overcome by higher percentages. Nevertheless, 2016 numbers are still high, being a motive of concern especially considering the elderly population.

Distribution and antifungal susceptibility patterns of Candida species at a university hospital in Northern Turkey.

The aim of this study was to establish local resistance profiles of Candida species isolated from various clinical specimens by identifying isolates and determining their susceptibilities to commonly used antifungal agents. All isolates were identified to species level and amphotericin B, flucytosine, fluconazole, voriconazole, caspofungin and micafungin antifungal susceptibility testing was performed using Vitek 2 Compact Advanced Expert System (AES). The specimens consisted of 152 urines (69%), 49 blood (22%), 15 sputum (7%) and 4 wound (2%) samples. Of the 220 isolated Candida strains, the most prevalent species were Candida albicans (43.3%), Candida tropicalis (25%) and Candida parapsilosis (13.7%). In blood specimens C. parapsilosis was the dominant species (43%), followed by C. albicans (32.5%) and C. tropicalis (12.2%). Overall resistance to amphotericin B, flucytosine, fluconazole, voriconazole, caspofungin and micafungin was 7.3%, 10%, 9.4%, 7.3%, 2% and 6.5%, respectively. Due to the increase in patient populations at risk of Candida infections, rational treatment planning and resistance rates should be checked along with antifungal susceptibility testing on C. albicans, C. tropicalis and C. parapsilosis isolates.

Plasmid-mediated mcr-1 colistin resistance in Escherichia coli and Klebsiella spp. clinical isolates from the Western Cape region of South Africa

BackgroundColistin is a last resort antibiotic for the treatment of carbapenem-resistant Gram negative infections. Until recently, mechanisms of colistin resistance were limited to chromosomal mutations which confer a high fitness cost and cannot be transferred between organisms. However, a novel plasmid-mediated colistin resistance mechanism, encoded by the mcr-1 gene, has been identified, and has since been detected worldwide. The mcr-1 colistin resistance mechanism is a major threat due to its lack of fitness cost and ability to be transferred between strains and species. Surveillance of colistin resistance mechanisms is critical to monitor the development and spread of resistance.This study aimed to determine the prevalence of the plasmid-mediated colistin resistance gene, mcr-1, in colistin-resistant E. coli and Klebsiella spp. isolates in the Western Cape of South Africa; and whether colistin resistance is spread through clonal expansion or by acquisition of resistance by diverse strains.MethodsColistin resistant E. coli and Klebsiella spp. isolates were collected from the NHLS microbiology laboratory at Tygerberg Hospital. Species identification and antibiotic susceptibility testing was done using the API® 20 E system and the Vitek® 2 Advanced Expert System™. PCR was used to detect the plasmid-mediated mcr-1 colistin resistance gene and REP-PCR was used for strain typing of the isolates.ResultsNineteen colistin resistant isolates, including 12 E. coli, six K. pneumoniae and one K. oxytoca isolate, were detected over 7 months from eight different hospitals in the Western Cape region. The mcr-1 gene was detected in 83% of isolates which were shown to be predominantly unrelated strains.ConclusionsThe plasmid-mediated mcr-1 colistin resistance gene is responsible for the majority of colistin resistance in clinical isolates of E. coli and Klebsiella spp. from the Western Cape of South Africa. Colistin resistance is not clonally disseminated; the mcr-1 gene has been acquired by several unrelated strains of E. coli and K. pneumoniae. Acquisition of mcr-1 by cephalosporin- and carbapenem-resistant Gram negative bacteria may result in untreatable infections and increased mortality. Measures need to be implemented to control the use of colistin in health care facilities and in agriculture to retain its antimicrobial efficacy.

Risk factors and predictors of mortality of candidaemia among critically ill patients: role of antifungal prophylaxis in its development and in selection of non-albicans species.

The aim of the present study is to identify risk factors for development and predictors of mortality of candidaemia among critically ill patients. A 1:7 case-control study was conducted during a 4-year period (2012-2015) in a Greek Intensive Care Unit (ICU). Candidaemia was confirmed by positive blood cultures. All yeasts were identified using API 20C AUX System or Vitek 2 Advanced Expert System. Epidemiologic data were collected from the ICU computerized database and patients' chart reviews. Fifty-three patients developed candidaemia with non-albicans species being the predominant ones (33 patients, 62.3%). Multivariate analysis found that prior emergency surgery, malignancy, hospitalization during summer months, prior septic shock by KPC-producing Klebsiella pneumoniae and number of antibiotics administered were independently associated with candidaemia, while, prior administration of azole was a protective factor. Non-albicans candidaemia was associated with number of antibiotics administered and prior administration of echinocandin. Mortality of 14 days was 28.3% (15 patients) and was associated with SOFA score upon infection onset and septic shock, while, appropriate empirical antifungal treatment was associated with better survival. Prophylactic azole administration prevents development of candidaemia, while, echinocandin administration predisposes to non-albicans candidaemia. Empirical administration of an appropriate antifungal agent is associated with better survival.

Trends of Bloodstream Infections in a University Greek Hospital during a Three-Year Period: Incidence of Multidrug-Resistant Bacteria and Seasonality in Gram-negative Predominance.

The aim of the study was to assess the epidemiology, the incidence of multidrug-resistant bacteria and bloodstream infections' (BSIs) seasonality in a university hospital. This retrospective study was carried out in the University General Hospital of Patras, Greece, during 2011-13 y. Blood cultures from patients with clinical presentation suggestive of bloodstream infection were performed by the BacT/ALERT System. Isolates were identified by Vitek 2 Advanced Expert System. Antibiotic susceptibility testing was performed by the disk diffusion method and E-test. Resistance genes (mecA in staphylococci; vanA/vanB/vanC in enterococci; blaKPC/blaVIM/blaNDM in Klebsiella spp.) were detected by PCR. In total, 4607 (9.7%) blood cultures were positive from 47451 sets sent to Department of Microbiology, representing 1732 BSIs. Gram-negative bacteria (52.3%) were the most commonly isolated, followed by Gram-positive (39.5%), fungi (6.6%) and anaerobes bacteria (1.8%). The highest contamination rate was observed among Gram-positive bacteria (42.3%). Among 330 CNS and 150 Staphylococcus aureus, 281 (85.2%) and 60 (40.0%) were mecA-positive, respectively. From 113 enterococci, eight were vanA, two vanB and two vanC-positives. Of the total 207 carbapenem-resistant Klebsiella pneumoniae (73.4%), 202 carried blaKPC, four blaKPC and blaVIM and one blaVIM. A significant increase in monthly BSIs' incidence was shown (R2: 0.449), which may be attributed to a rise of Gram-positive BSIs (R2: 0.337). Gram-positive BSIs were less frequent in spring (P < 0.001), summer (P < 0.001), and autumn (P < 0.001), as compared to winter months, while Gram-negative bacteria (P < 0.001) and fungi (P < 0.001) were more frequent in summer months. BSIs due to methicillin resistant S. aureus and carbapenem-resistant Gram-negative bacteria increased during the study period. The increasing incidence of BSIs can be attributed to an increase of Gram-positive BSI incidence, even though Gram-negative bacteria remained the predominant ones. Seasonality may play a role in the predominance of Gram-negative's BSI.

Prevalence, seasonal variation, and antibiotic resistance pattern of enteric bacterial pathogens among hospitalized diarrheic children in suburban regions of central Kenya.

BackgroundThe epidemiology of enteric pathogens has not been well studied in Kenya because of wide disparities in health status across the country. Therefore, the present study describes the prevalence of enteropathogenic bacteria, their seasonal variation, and antibiotic resistance profiles among hospitalized diarrheic children in a suburban region of central Kenya.MethodsFecal samples were collected between July 2009 and December 2013 from a total of 1410 children younger than 5 years, hospitalized with acute diarrhea in Kiambu County Hospital, Kenya. Conventional culture, biochemical, and molecular methods were conducted to identify causative bacterial pathogens and their virulence factors. Antimicrobial susceptibility tests were performed using E-test strips and VITEK-2 advanced expert system (AES) to evaluate the drug-resistance pattern of the isolates.ResultsOf the 1410 isolates, bacterial infections were identified in 474 cases. Diarrheagenic Escherichia coli (DEC) was the most frequently isolated pathogen (86.5%). Other pathogens such as Aeromonas (5.5%), Shigella (4%), Salmonella (3.4%), Providencia (3.2%), Vibrio spp. (1.1%), Yersinia enterocolitica (1.1%), and Plesiomonas shigelloides (0.2%) were also identified. Mixed bacterial infection was observed among 11.1% of the cases. The highest infection rate was found during the dry season (59.3%, p = 0.04). Most of the DEC was found to be multidrug resistant to trimethoprim/sulfamethoxazole 97.6%, amoxicillin 97.6%, erythromycin 96.9%, ampicillin 96.6%, and streptomycin 89%.ConclusionsThis study suggests that DEC is the leading diarrhea-causing bacterial pathogen circulating in central Kenya, and seasonality has a significant effect on its transmission. Proper antibiotic prescription and susceptibility testing is important to guide appropriate antimicrobial therapy.

Evaluation of the capabilities of disc diffusion and Vitek2-compact GN13 methods for imipenem susceptibility testing and study of the reliability of advanced expert system

Evaluation of the capabilities of disc diffusion and Vitek2-compact GN13 methods for imipenem susceptibility testing and study of the reliability of advanced expert system

Pitfalls in the identification of Enterococcus species and the detection of vanA and vanB genes.

The aims were to assess the performance of Vitek 2 in identifying enterococcal species and the implementation of GeneXpert(®) vanA/vanB PCR for the detection of vancomycin-resistant enterococci (VRE). Gram-positive cocci from clinical and environmental specimens (n=431) suspicious of being enterococci by conventional methods were evaluated by Vitek 2. This system identified 296 Enterococcus faecium, 87 Enterococcus faecalis, 10 Enterococcus villorum, 9 Enterococcus gallinarum, 9 Enterococcus durans, 5 Enterococcus casseliflavus, 1 Enterococcus spp. and 14 isolates as Non-Enterococcus. All strains were submitted to pulsed field gel electrophoresis (PFGE) analysis showing 64 banding patterns. Representative strains from each banding pattern were further characterized to species level by 16S rDNA sequencing. The misidentification rate by Vitek 2 to species level among 429 molecularly identified enterococci was 6% (26 isolates). Additionally, 372 rectal swabs were obtained from critically ill patients. They were evaluated for the presence of VRE by ChromID VRE combined with in-house PCR vs GeneXpert(®) . GeneXpert(®) showed high (>92%) sensitivity, specificity, accuracy for vanA-positive Enterococcus detection, as well as, sensitivity and specificity for vanB-positive strains. Positive predictive value for detection of vanB-positive enterococci by GeneXpert(®) vanA/vanB was low (30%). GeneXpert(®) showed the same efficacy as ChromID VRE in detecting vanA-positive enterococci, but lower for vanB-gene detection. The study shows that even though the performance of Vitek 2 Advanced Expert System was good in identifying enterococci to species level, it is important to verify results by a molecular method when phenotypic findings are discordant with epidemiologic patterns. Furthermore, GeneXpert(®) vanA/vanB PCR and ChromID VRE combined with in-house PCR were applied in rectal samples for the detection of VRE colonization among critically ill patients. GeneXpert(®) showed an excellent performance in detecting vanA-positive enterococci, but false-positive results for vanB-gene detection render its application problematic in departments with high incidence of vanB-positive enterococci.