925 resultados para Staphylococcus


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Hand hygiene is critical in the healthcare setting and it is believed that methicillin-resistant Staphylococcus aureus (MRSA), for example, is transmitted from patient to patient largely via the hands of health professionals. A study has been carried out at a large teaching hospital to estimate how often the gloves of a healthcare worker are contaminated with MRSA after contact with a colonized patient. The effectiveness of handwashing procedures to decontaminate the health professionals' hands was also investigated, together with how well different healthcare professional groups complied with handwashing procedures. The study showed that about 17% (9–25%) of contacts between a healthcare worker and a MRSA-colonized patient results in transmission of MRSA from a patient to the gloves of a healthcare worker. Different health professional groups have different rates of compliance with infection control procedures. Non-contact staff (cleaners, food services) had the shortest handwashing times. In this study, glove use compliance rates were 75% or above in all healthcare worker groups except doctors whose compliance was only 27%.

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A new method for estimating the time to colonization of Methicillin-resistant Staphylococcus Aureus (MRSA) patients is developed in this paper. The time to colonization of MRSA is modelled using a Bayesian smoothing approach for the hazard function. There are two prior models discussed in this paper: the first difference prior and the second difference prior. The second difference prior model gives smoother estimates of the hazard functions and, when applied to data from an intensive care unit (ICU), clearly shows increasing hazard up to day 13, then a decreasing hazard. The results clearly demonstrate that the hazard is not constant and provide a useful quantification of the effect of length of stay on the risk of MRSA colonization which provides useful insight.

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Healthcare-associated methicillin-resistant Staphylococcus aureus(MRSA) infection may cause increased hospital stay or, sometimes, death. Quantifying this effect is complicated because it is a time-dependent exposure: infection may prolong hospital stay, while longer stays increase the risk of infection. We overcome these problems by using a multinomial longitudinal model for estimating the daily probability of death and discharge. We then extend the basic model to estimate how the effect of MRSA infection varies over time, and to quantify the number of excess ICU days due to infection. We find that infection decreases the relative risk of discharge (relative risk ratio = 0.68, 95% credible interval: 0.54, 0.82), but is only indirectly associated with increased mortality. An infection on the first day of admission resulted in a mean extra stay of 0.3 days (95% CI: 0.1, 0.5) for a patient with an APACHE II score of 10, and 1.2 days (95% CI: 0.5, 2.0) for a patient with an APACHE II score of 30. The decrease in the relative risk of discharge remained fairly constant with day of MRSA infection, but was slightly stronger closer to the start of infection. These results confirm the importance of MRSA infection in increasing ICU stay, but suggest that previous work may have systematically overestimated the effect size.

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The purpose of this paper is to determine the prevalence of the toxic shock toxin gene (tst) and to enumerate the circulating strains of methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant S. aureus (MRSA) in Australian isolates collected over two decades. The aim was to subtype these strains using the binary genes pvl, cna, sdrE, pUB110 and pT181. Isolates were assayed using real-time polymerase chain reaction (PCR) for mecA, nuc, 16 S rRNA, eight single-nucleotide polymorphisms (SNPs) and for five binary genes. Two realtime PCR assays were developed for tst. The 90 MRSA isolates belonged to CC239 (39 in 1989, 38 in 1996 and ten in 2003), CC1 (two in 2003) and CC22 (one in 2003). The majority of the 210 MSSA isolates belonged to CC1 (26), CC5 (24) and CC78 (23). Only 18 isolates were tst-positive and only 15 were pvl-positive. Nine MSSA isolates belonged to five binary types of ST93, including two pvlpositive types. The proportion of tst-positive and pvl-positive isolates was low and no significant increase was demonstrated. Dominant MSSA clonal complexes were similar to those seen elsewhere, with the exception of CC78. CC239 MRSA (AUS-2/3) was the predominant MRSA but decreased significantly in prevalence, while CC22 (EMRSA-15) and CC1 (WA-1) emerged. Genetically diverse ST93 MSSA predated the emergence of ST93- MRSA (the Queensland clone).

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The aim was to determine the evolutionary position of the Staphylococcus aureus clonal complex 75 (CC75) that is prevalent in tropical northern Australia. Sequencing of gap, rpoB, sodA, tuf, and hsp60 and the multilocus sequence typing loci revealed a clear separation between conventional S. aureus and CC75 and significant diversity within CC75.

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Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) infections are emerging in southeast Queensland, Australia, but the incidence of carriage of CA-MRSA strains is unknown. The aim of this study was to assess the nasal carriage rate of S. aureus, including CA-MRSA strains, in the general adult population of southeast Queensland. 396 patients presenting to general practices in two Brisbane suburbs and 303 volunteers randomly selected from the electoral rolls in the same suburbs completed a medical questionnaire and had nasal swabs performed for S. aureus. All isolates of S. aureus underwent antibiotic susceptibility testing and single-nucleotide polymorphism (SNP) and binary typing, including determination of Panton–Valentine leukocidin (PVL). The nasal carriage rate of methicillin-susceptible S. aureus (MSSA) was 202/699 (28%), a rate similar to that found in other community-based nasal carriage studies. According to multivariate analysis, nasal carriage of S. aureus was associated with male sex, young adult age group and Caucasian ethnicity. Only two study isolates (one MSSA and one CA-MRSA) carried PVL. The nasal carriage rate of MRSA was low, at 5/699 (0.7%), and only two study participants (0.3%) had CA-MRSA strains. CA-MRSA is an emerging cause of infection in southeast Queensland, but as yet the incidence of carriage of CA-MRSA in the general community is low.

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Staphylococcus aureus is a common pathogen that causes a variety of infections including soft tissue infections, impetigo, septicemia toxic shock and scalded skin syndrome. Traditionally, Methicillin-Resistant Staphylococcus aureus (MRSA) was considered a Hospital-Acquired (HA) infection. It is now recognised that the frequency of infections with MRSA is increasing in the community, and that these infections are not originating from hospital environments. A 2007 report by the Centers for Disease Control and Prevention (CDC) stated that Staphylococcus aureus is the most important cause of serious and fatal infections in the USA. Community-Acquired MRSA (CA-MRSA) are genetically diverse and distinct, meaning they are able to be identified and tracked by way of genotyping. Genotyping of MRSA using Single nucleotide polymorphisms (SNPs) is a rapid and robust method for monitoring MRSA, specifically ST93 (Queensland Clone) dissemination in the community. It has been shown that a large proportion of CA-MRSA infections in Queensland and New South Wales are caused by ST93. The rationale for this project was that SNP analysis of MLST genes is a rapid and cost-effective method for genotyping and monitoring MRSA dissemination in the community. In this study, 16 different sequence types (ST) were identified with 41% of isolates identified as ST93 making it the predominate clone. Males and Females were infected equally with an average patient age of 45yrs. Phenotypically, all of the ST93 had an identical antimicrobial resistance pattern. They were resistant to the β-lactams – Penicillin, Flu(di)cloxacillin and Cephalothin but sensitive to all other antibiotics tested. Virulence factors play an important role in allowing S. aureus to cause disease by way of colonising, replication and damage to the host. One virulence factor of particular interest is the toxin Panton-Valentine leukocidin (PVL), which is composed of two separate proteins encoded by two adjacent genes. PVL positive CA-MRSA are shown to cause recurrent, chronic or severe skin and soft tissue infections. As a result, it is important that PVL positive CA-MRSA is genotyped and tracked. Especially now that CA-MRSA infections are more prevalent than HA-MRSA infections and are now deemed endemic in Australia. 98% of all isolates in this study tested positive for the PVL toxin gene. This study showed that PVL is present in many different community based ST, not just ST93, which were all PVL positive. With this toxin becoming entrenched in CA-MRSA, genotyping would provide more accurate data and a way of tracking the dissemination. PVL gene can be sub-typed using an allele-specific Real-Time PCR (RT-PCR) followed by High resolution meltanalysis. This allows the identification of PVL subtypes within the CA-MRSA population and allow the tracking of these clones in the community.

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Methicillin-resistant Staphylococcus Aureus (MRSA) is a pathogen that continues to be of major concern in hospitals. We develop models and computational schemes based on observed weekly incidence data to estimate MRSA transmission parameters. We extend the deterministic model of McBryde, Pettitt, and McElwain (2007, Journal of Theoretical Biology 245, 470–481) involving an underlying population of MRSA colonized patients and health-care workers that describes, among other processes, transmission between uncolonized patients and colonized health-care workers and vice versa. We develop new bivariate and trivariate Markov models to include incidence so that estimated transmission rates can be based directly on new colonizations rather than indirectly on prevalence. Imperfect sensitivity of pathogen detection is modeled using a hidden Markov process. The advantages of our approach include (i) a discrete valued assumption for the number of colonized health-care workers, (ii) two transmission parameters can be incorporated into the likelihood, (iii) the likelihood depends on the number of new cases to improve precision of inference, (iv) individual patient records are not required, and (v) the possibility of imperfect detection of colonization is incorporated. We compare our approach with that used by McBryde et al. (2007) based on an approximation that eliminates the health-care workers from the model, uses Markov chain Monte Carlo and individual patient data. We apply these models to MRSA colonization data collected in a small intensive care unit at the Princess Alexandra Hospital, Brisbane, Australia.

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Objective: To assess the cost-effectiveness of screening, isolation and decolonisation strategies in the control of methicillin-resistant Staphylococcus aureus (MRSA) in intensive care units (ICUs). Design: Economic evaluation. Setting: England and Wales. Population: ICU patients. Main outcome measures: Infections, deaths, costs, quality adjusted life years (QALYs), incremental cost-effectiveness ratios for alternative strategies, net monetary benefits (NMBs). Results: All strategies using isolation but not decolonisation improved health outcomes but increased costs. When MRSA prevalence on admission to the ICU was 5% and the willingness to pay per QALY gained was between £20,000 and £30,000, the best such strategy was to isolate only those patients at high risk of carrying MRSA (either pre-emptively or following identification by admission and weekly MRSA screening using chromogenic agar). Universal admission and weekly screening using polymerase chain reaction (PCR)-based MRSA detection coupled with isolation was unlikely to be cost-effective unless prevalence was high (10% colonised with MRSA on admission to the ICU). All decolonisation strategies improved health outcomes and reduced costs. While universal decolonisation (regardless of MRSA status) was the most cost-effective in the short-term, strategies using screening to target MRSA carriers may be preferred due to reduced risk of selecting for resistance. Amongst such targeted strategies, universal admission and weekly PCR screening coupled with decolonisation with nasal mupirocin was the most cost-effective. This finding was robust to ICU size, MRSA admission prevalence, the proportion of patients classified as high-risk, and the precise value of willingness to pay for health benefits. Conclusions: MRSA control strategies that use decolonisation are likely to be cost-saving in an ICU setting provided resistance is lacking, and combining universal PCR-based screening with decolonisation is likely to represent good value for money if untargeted decolonisation is considered unacceptable. In ICUs where decolonisation is not implemented there is insufficient evidence to support universal MRSA screening outside high prevalence settings.

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The Implementation Guide for the Hospital Surveillance of SAB has been produced by the Healthcare Associated Infection (HAI) Technical Working Group of the Australian Commission on Safety and Quality in Health Care (ACSQHC), and endorsed by the HAI Advisory Group. The Technical Working Group is made up of representatives invited from surveillance units and the ACSQHC, who have had input into the preparation of this Guide. The Guide has been developed to ensure consistency in reporting of SAB across public and private hospitals to enable accurate national reporting and benchmarking. It is intended to be used by Australian hospitals and organisations to support the implementation of healthcare associated Staphylococcus aureus bacteraemia(SAB) surveillance using the endorsed case definition1 in the box below and further detail in the Data Set Specification.

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Staphylococcus aureus, one of the major pathogenic bacteria, is associated with substantial morbidity and mortality. The disease burden of staphylococcal infections is significant, which is primarily attributed to its adaptability and resistance to environmental stresses. S. aureus has the ability to develop multiple resistances to antimicrobial agents. These high resistances make pathogenicity of S. aureus one of the most complex mechanisms to understand and manage. Proteomic and bioinformatics approaches show great potential in exploring microbial adaptation strategies, ability to cause disease by pathogenic bacteria and the development of diagnostic tools. A summary of the latest developments in the application of ‘omics’ technologies to understand resistance mechanisms in S. aureus and their future role in antistaphylococcal vaccine and/or drug discovery is given here.