Biochemical Phenotypes to Discriminate Microbial Subpopulations and Improve Outbreak Detection

Background: Clinical microbiology laboratories worldwide constitute an invaluable resource for monitoring emerging threats and the spread of antimicrobial resistance. We studied the growing number of biochemical tests routinely performed on clinical isolates to explore their value as epidemiological markers. Methodology/Principal Findings Microbiology laboratory results from January 2009 through December 2011 from a 793-bed hospital stored in WHONET were examined. Variables included patient location, collection date, organism, and 47 biochemical and 17 antimicrobial susceptibility test results reported by Vitek 2. To identify biochemical tests that were particularly valuable (stable with repeat testing, but good variability across the species) or problematic (inconsistent results with repeat testing), three types of variance analyses were performed on isolates of K. pneumonia: descriptive analysis of discordant biochemical results in same-day isolates, an average within-patient variance index, and generalized linear mixed model variance component analysis. Results: 4,200 isolates of K. pneumoniae were identified from 2,485 patients, 32% of whom had multiple isolates. The first two variance analyses highlighted SUCT, TyrA, GlyA, and GGT as “nuisance” biochemicals for which discordant within-patient test results impacted a high proportion of patient results, while dTAG had relatively good within-patient stability with good heterogeneity across the species. Variance component analyses confirmed the relative stability of dTAG, and identified additional biochemicals such as PHOS with a large between patient to within patient variance ratio. A reduced subset of biochemicals improved the robustness of strain definition for carbapenem-resistant K. pneumoniae. Surveillance analyses suggest that the reduced biochemical profile could improve the timeliness and specificity of outbreak detection algorithms. Conclusions: The statistical approaches explored can improve the robust recognition of microbial subpopulations with routinely available biochemical test results, of value in the timely detection of outbreak clones and evolutionarily important genetic events

Los laboratorios de microbiología del mundo pueden convertirse en una red de detección microbiana

The microbes that infect us spread in global and local epidemics, and the resistance genes that block their treatment spread within and between them. All we can know about where they are to track and contain them comes from the only places that can see them, the world’s microbiology laboratories, but most report each patient’s microbe only to that patient’s caregiver.Sensors, ranging from instruments to birdwatchers, are now being linked in electronic networks to monitor and interpret algorithmically in real-time ocean currents, atmospheric carbon, supply-chain inventory, bird migration, etc. To so link the world’s microbiology laboratories as exquisite sensors in a truly lifesaving real-time network their data must be accessed and fully subtyped.Microbiology laboratories put individual reports into inaccessible paper or mutually incompatible electronic reporting systems, but those from more than 2,200 laboratories in more than 108 countries worldwide are now accessed and translated into compatible WHONET files. These increasingly web-based files could initiate a global microbial sensor network.Unused microbiology laboratory byproduct data, now from drug susceptibility and biochemical testing but increasingly from new technologies (genotyping, MALDI-TOF, etc.), can be reused to subtype microbes of each genus/species into sub-groupings that are discriminated and traced with greater sensitivity. Ongoing statistical delineation of subtypes from global sensor network data will improve detection of movement into any patient of a microbe or resistance gene from another patient, medical center or country. Growing data on clinical manifestations and global distributions of subtypes can automate comments for patient’s reports, select microbes to genotype and alert responders. Los microbios que nos afectan se diseminan por epidemias locales y globales, y los genes resistentes que bloquean los tratamientos disponibles para combatirlos se reproducen dentro de ellos y se transmiten de unos a otros. Todo lo que sabemos sobre dónde rastrearlos y cómo contenerlos proviene de los únicos lugares en donde es posible examinarlos: los laboratorios de microbiología del mundo. Sin embargo, la mayoría de estos laboratorios reportan el microorganismo que afecta a cada paciente específico solamente a los responsables de la atención de ese paciente en particular.Los sensores, que van desde instrumentos hasta observadores de aves, se encuentran hoy conectados por redes electrónicas destinadas a monitorizar e interpretar por medio de algoritmos y en tiempo real las corrientes oceánicas, el carbono de la atmósfera, los inventarios de las cadenas de suministro, la migración de las aves, etc. La vinculación de los laboratorios de microbiología del mundo para que actúen como refinados detectores en una red dedicada a salvar vidas, requiere, no obstante, que sus hallazgos sean sometidos a subtipificación y que sus datos se puedan consultar sin restricción.Los reportes de los laboratorios de microbiología generalmente son documentos en papel que son inaccesibles o están en sistemas electrónicos de notificación mutuamente incompatibles. No obstante, actualmente los resultados de más de 2.200 laboratorios en más de 108 países han sido traducidos a los archivos compatibles de WHONET y están disponibles para consulta. Con estos archivos en la internet se podría iniciar una red global de detección microbiana.Los subproductos de información provenientes de los laboratorios de microbiología que hoy no se utilizan, como los datos sobre sensibilidad a medicamentos y los de pruebas bioquímicas, y aquellos que próximamente comenzarán a generar las nuevas tecnologías (genotipificación, técnicas de ionización suave [Matrix-Assisted Laser Desorption/Ionization Time-of-Flight, MALDI-TOF]), etc., pueden reutilizarse en la subtipificación de microorganismos de cada género y especie clasificados en subgrupos susceptibles de ser discriminados y rastreados con mayor precisión.La delineación estadística de los subtipos que actualmente se lleva a cabo con base en los datos de la red global de sensores mejorará la detección de la transmisión de cualquier microbio o gen resistente de un paciente a otro paciente, centro médico o país. La creciente cantidad de datos relativos a las manifestaciones clínicas y la distribución global de subtipos puede incluir la automatización de comentarios en las historias clínicas, la selección de microorganismos para la subtipificación y la notificación de alertas a los responsables de salud.

Evaluation of the diagnostic performance of the urine dipstick test for the detection of urinary tract infections in patients treated in Kenyan hospitals

This work is a subset of the large HATUA (Holistic approach to unravel antibacterial resistance) consortium funded by the UK Medical Research Council (MR/S004785/1).Introduction. Culture is the gold-standard diagnosis for urinary tract infections (UTIs). However, most hospitals in low-resource countries lack adequately equipped laboratories and relevant expertise to perform culture and, therefore, rely heavily on dipstick tests for UTI diagnosis. Research gap. In many Kenyan hospitals, routine evaluations are rarely done to assess the accuracy of popular screening tests such as the dipstick test. As such, there is a substantial risk of misdiagnosis emanating from inaccuracy in proxy screening tests. This may result in misuse, under-use or over-use of antimicrobials. Aim. The present study aimed to assess the accuracy of the urine dipstick test as a proxy for the diagnosis of UTIs in selected Kenyan hospitals. Methods. A hospital-based cross-sectional method was used. The utility of dipstick in the diagnosis of UTIs was assessed using midstream urine against culture as the gold standard. Results. The dipstick test predicted 1416 positive UTIs, but only 1027 were confirmed positive by culture, translating to a prevalence of 54.1 %. The sensitivity of the dipstick test was better when leucocytes and nitrite tests were combined (63.1 %) than when the two tests were separate (62.6 and 50.7 %, respectively). Similarly, the two tests combined had a better positive predictive value (87.0 %) than either test alone. The nitrite test had the best specificity (89.8 %) and negative predictive value (97.4 %) than leucocytes esterase (L.E) or both tests combined. In addition, sensitivity in samples from inpatients (69.2 %) was higher than from outpatients (62.7 %). Furthermore, the dipstick test had a better sensitivity and positive predictive value among female (66.0 and 88.6 %) than male patients (44.3 and 73.9 %). Among the various patient age groups, the dipstick test’s sensitivity and positive predictive value were exceptionally high in patients ≥75 years old (87.5 and 93.3 %). Conclusion. Discrepancies in prevalence from the urine dipstick test and culture, the gold standard, indicate dipstick test inadequacy for accurate UTI diagnosis. The finding also demonstrates the need for urine culture for accurate UTI diagnosis. However, considering it is not always possible to perform a culture, especially in low-resource settings, future studies are needed to combine specific UTI symptoms and dipstick results to assess possible increases in the test’s sensitivity. There is also a need to develop readily available and affordable algorithms that can detect UTIs where culture is not available.Publisher PDFPeer reviewe

Understanding attitudes to priorities at side road junctions

Junctions are places of interaction and hence conflict for all road users. Two thirds of all collisions in built up areas occur at junctions, with pedestrians and cyclists being most at risk. The aim of the research is to investigate the attitudes to change, and likely behaviour at junctions, of all types of road users, were a general and unambiguous duty to ‘give way on turning’ to be introduced in the UK context. Q-methodology was used because it is good at capturing and describing divergent views and also consensus. Q-mode factor analysis was used and revealed five groups with common perspectives, as follows: optimistic experienced drivers, pessimistic regular cyclists, realistic multi-modals, altruistic pedestrians and the pragmatic sustainably mobile. Differences between groups centred on which road user types should be the prime focus of junction improvements, the relative importance of safety and time saving, and the amount of effort required to implement change. There was a strong consensus between the groups that no level of injury and death at road junctions is acceptable, and that regulation changes should be made. Funding for awareness raising, and supporting any regulation change with concomitant design changes to the physical layout of junctions is also important. There is a consistency of opinion across all groups of road users that the lack of alignment between design and regulation, and lack of compliance with the regulations are not acceptable. Each grouping of respondents thought that it is appropriate to make junctions safe for all, and more attractive and convenient for those that are currently the most at risk. There are practical changes that policy makers and practitioners could and should make. Change in regulations could be undertaken, but it would need to be supported by the following: public awareness raising campaigns; infrastructure design changes; funding; and enforcement

Integrating Escherichia coli Antimicrobial Susceptibility Data from Multiple Surveillance Programs

Collaboration between networks presents opportunities to increase analytical power and cross-validate findings. Multivariate analyses of 2 large, international datasets (MYSTIC and SENTRY) from the Global Advisory on Antibiotic Resistance Data program explored temporal, geographic, and demographic trends in Escherichia coli resistance from 1997 to 2001. Elevated rates of nonsusceptibility were seen in Latin America, southern Europe, and the western Pacific, and lower rates were seen in North America. For most antimicrobial drugs considered, nonsusceptibility was higher in isolates from men, older patients, and intensive care unit patients. Nonsusceptibility to ciprofloxacin was higher in younger patients, rose with time, and was not associated with intensive care unit status. In univariate analyses, estimates of nonsusceptibility from MYSTIC were consistently higher than those from SENTRY, but these differences disappeared in multivariate analyses, which supports the epidemiologic relevance of findings from the 2 programs, despite differences in surveillance strategies

Use of WHONET-SaTScan system for simulated real-time detection of antimicrobial resistance clusters in a hospital in Italy, 2012 to 2014.

Resistant pathogens infections cause in healthcare settings, higher patient mortality, longer hospitalisation times and higher costs for treatments. Strengthening and coordinating local, national and international surveillance systems is the cornerstone for the control of antimicrobial resistance (AMR). In this study, the WHONET-SaTScan software was applied in a hospital in Italy to identify potential outbreaks of AMR. Data from San Filippo Neri Hospital in Rome between 2012 and 2014 were extracted from the national surveillance system for antimicrobial resistance (AR-ISS) and analysed using the simulated prospective analysis for real-time cluster detection included in the WHONET-SaTScan software. Results were compared with the hospital infection prevention and control system. The WHONET-SaTScan identified 71 statistically significant clusters, some involving pathogens carrying multiple resistance phenotypes. Of these 71, three were also detected by the hospital system, while a further 15, detected by WHONET-SaTScan only, were considered of relevant importance and worth further investigation by the hospital infection control team. In this study, the WHONET-SaTScan system was applied for the first time to the surveillance of AMR in Italy as a tool to strengthen this surveillance to allow more timely intervention strategies both at local and national level, using data regularly collected by the Italian national surveillance system

Predominance of multidrug-resistant bacteria causing urinary tract infections among symptomatic patients in East Africa : a call for action

Background In low- and middle-income countries, antibiotics are often prescribed for patients with symptoms of urinary tract infections (UTIs) without microbiological confirmation. Inappropriate antibiotic use can contribute to antimicrobial resistance (AMR) and the selection of MDR bacteria. Data on antibiotic susceptibility of cultured bacteria are important in drafting empirical treatment guidelines and monitoring resistance trends, which can prevent the spread of AMR. In East Africa, antibiotic susceptibility data are sparse. To fill the gap, this study reports common microorganisms and their susceptibility patterns isolated from patients with UTI-like symptoms in Kenya, Tanzania and Uganda. Within each country, patients were recruited from three sites that were sociodemographically distinct and representative of different populations. Methods UTI was defined by the presence of >104 cfu/mL of one or two uropathogens in mid-stream urine samples. Identification of microorganisms was done using biochemical methods. Antimicrobial susceptibility testing was performed by the Kirby–Bauer disc diffusion assay. MDR bacteria were defined as isolates resistant to at least one agent in three or more classes of antimicrobial agents. Results Microbiologically confirmed UTI was observed in 2653 (35.0%) of the 7583 patients studied. The predominant bacteria were Escherichia coli (37.0%), Staphylococcus spp. (26.3%), Klebsiella spp. (5.8%) and Enterococcus spp. (5.5%). E. coli contributed 982 of the isolates, with an MDR proportion of 52.2%. Staphylococcus spp. contributed 697 of the isolates, with an MDR rate of 60.3%. The overall proportion of MDR bacteria (n = 1153) was 50.9%. Conclusions MDR bacteria are common causes of UTI in patients attending healthcare centres in East African countries, which emphasizes the need for investment in laboratory culture capacity and diagnostic algorithms to improve accuracy of diagnosis that will lead to appropriate antibiotic use to prevent and control AMR.Peer reviewe