Knowledge of stroke risk factors among primary care patients with previous stroke or TIA: a questionnaire study

<p>Abstract</p> <p>Background</p> <p>Survivers of stroke or transient ischaemic attacks (TIA) are at risk of new vascular events. Our objective was to study primary health care patients with stroke/TIA regarding their knowledge about risk factors for having a new event of stroke/TIA, possible associations between patient characteristics and patients' knowledge about risk factors, and patients' knowledge about their preventive treatment for stroke/TIA.</p> <p>Methods</p> <p>A questionnaire was distributed to 240 patients with stroke/TIA diagnoses, and 182 patients (76%) responded. We asked 13 questions about diseases/conditions and lifestyle factors known to be risk factors and four questions regarding other diseases/conditions ("distractors"). The patients were also asked whether they considered each disease/condition to be one of their own. Additional questions concerned the patients' social and functional status and their drug use. The t-test was used for continuous variables, chi-square test for categorical variables, and a regression model with variables influencing patient knowledge was created.</p> <p>Results</p> <p>Hypertension, hyperlipidemia and smoking were identified as risk factors by nearly 90% of patients, and atrial fibrillation and diabetes by less than 50%. Few patients considered the distractors as stroke/TIA risk factors (3-6%). Patients with a family history of cardiovascular disease, and patients diagnosed with carotid stenosis, atrial fibrillation or diabetes, knew these were stroke/TIA risk factors to a greater extent than patients without these conditions. Atrial fibrillation or a family history of cardiovascular disease was associated with better knowledge about risk factors, and higher age, cerebral haemorrhage and living alone with poorer knowledge. Only 56% of those taking anticoagulant drugs considered this as intended for prevention, while 48% of those taking platelet aggregation inhibitors thought this was for prevention.</p> <p>Conclusions</p> <p>Knowledge about hypertension, hyperlipidemia and smoking as risk factors was good, and patients who suffered from atrial fibrillation or carotid stenosis seemed to be well informed about these conditions as risk factors. However, the knowledge level was low regarding diabetes as a risk factor and regarding the use of anticoagulants and platelet aggregation inhibitors for stroke/TIA prevention. Better teaching strategies for stroke/TIA patients should be developed, with special attention focused on diabetic patients.</p

Diversity of Methicillin-Resistant Staphylococcus aureus (MRSA) Strains Isolated from Inpatients of 30 Hospitals in Orange County, California

There is a need for a regional assessment of the frequency and diversity of MRSA to determine major circulating clones and the extent to which community and healthcare MRSA reservoirs have mixed. We conducted a prospective cohort study of inpatients in Orange County, California, systematically collecting clinical MRSA isolates from 30 hospitals, to assess MRSA diversity and distribution. All isolates were characterized by spa typing, with selective PFGE and MLST to relate spa types with major MRSA clones. We collected 2,246 MRSA isolates from hospital inpatients. This translated to 91/10,000 inpatients with MRSA and an Orange County population estimate of MRSA inpatient clinical cultures of 86/100,000 people. spa type genetic diversity was heterogeneous between hospitals, and relatively high overall (72%). USA300 (t008/ST8), USA100 (t002/ST5) and a previously reported USA100 variant (t242/ST5) were the dominant clones across all Orange County hospitals, representing 83% of isolates. Fifteen hospitals isolated more t008 (USA300) isolates than t002/242 (USA100) isolates, and 12 hospitals isolated more t242 isolates than t002 isolates. The majority of isolates were imported into hospitals. Community-based infection control strategies may still be helpful in stemming the influx of traditionally community-associated strains, particularly USA300, into the healthcare setting. © 2013 Hudson et al

Human leukocyte interferon produced by E. coli is biologically active

A human leukocyte interferon cDNA was enzymatically synthesized, inserted into the vector pBR322, and cloned in Escherichia coli. The DNA sequence codes for a 23-amino acid signal peptide followed by an interferon polypeptide of 165 amino acids. An expression plasmid was constructed which permits the synthesis in E. coli of 2.5 x 10(8) units of interferon per litre of culture. This LeIF protected squirrel monkeys from lethal encephalomyocarditis virus infection

Human leukocyte interferon produced by E. coli is biologically active

A human leukocyte interferon cDNA was enzymatically synthesized, inserted into the vector pBR322, and cloned in Escherichia coli. The DNA sequence codes for a 23-amino acid signal peptide followed by an interferon polypeptide of 165 amino acids. An expression plasmid was constructed which permits the synthesis in E. coli of 2.5 x 10(8) units of interferon per litre of culture. This LeIF protected squirrel monkeys from lethal encephalomyocarditis virus infection

Modelling the transmission of healthcare associated infections: a systematic review.

BACKGROUND: Dynamic transmission models are increasingly being used to improve our understanding of the epidemiology of healthcare-associated infections (HCAI). However, there has been no recent comprehensive review of this emerging field. This paper summarises how mathematical models have informed the field of HCAI and how methods have developed over time. METHODS: MEDLINE, EMBASE, Scopus, CINAHL plus and Global Health databases were systematically searched for dynamic mathematical models of HCAI transmission and/or the dynamics of antimicrobial resistance in healthcare settings. RESULTS: In total, 96 papers met the eligibility criteria. The main research themes considered were evaluation of infection control effectiveness (64%), variability in transmission routes (7%), the impact of movement patterns between healthcare institutes (5%), the development of antimicrobial resistance (3%), and strain competitiveness or co-colonisation with different strains (3%). Methicillin-resistant Staphylococcus aureus was the most commonly modelled HCAI (34%), followed by vancomycin resistant enterococci (16%). Other common HCAIs, e.g. Clostridum difficile, were rarely investigated (3%). Very few models have been published on HCAI from low or middle-income countries.The first HCAI model has looked at antimicrobial resistance in hospital settings using compartmental deterministic approaches. Stochastic models (which include the role of chance in the transmission process) are becoming increasingly common. Model calibration (inference of unknown parameters by fitting models to data) and sensitivity analysis are comparatively uncommon, occurring in 35% and 36% of studies respectively, but their application is increasing. Only 5% of models compared their predictions to external data. CONCLUSIONS: Transmission models have been used to understand complex systems and to predict the impact of control policies. Methods have generally improved, with an increased use of stochastic models, and more advanced methods for formal model fitting and sensitivity analyses. Insights gained from these models could be broadened to a wider range of pathogens and settings. Improvements in the availability of data and statistical methods could enhance the predictive ability of models