SummaryDirect laryngoscopy using the Macintosh laryngoscope is a difficult skill to acquire. Videolaryngoscopy is a widely accepted airway management technique that may be easier for novices to learn. We compared the McGrath Ò videolaryngoscope and Macintosh laryngoscope by studying the performance of 25 medical students with no previous experience of performing tracheal intubation using an easy intubation scenario in a manikin. The order of device use was randomised for each student. After brief instruction each participant performed eight tracheal intubations with one device and then eight tracheal intubations with the other laryngoscope. Novices achieved a higher overall rate of successful tracheal intubation, avoided oesophageal intubation and produced less dental trauma when using the McGrath. The view at laryngoscopy was significantly better with the McGrath. Intubation times were similar for both laryngoscopes and became shorter with practice. There was no difference in participants' rating of overall ease of use for each laryngoscope.

The peer-assisted mock OSCE improved tutee confidence and reduced the anxieties associated with OSCEs. Tutors gain valuable teaching skills. This PAL model is an acceptable, feasible and beneficial method of preparing students for this challenging style of health care examination.

AimTo estimate the proportional contribution of influenza viruses (IV), parainfluenza viruses (PIV), adenoviruses (AV), and coronaviruses (CV) to the burden of severe acute lower respiratory infections (ALRI).MethodsThe review of the literature followed PRISMA guidelines. We included studies of hospitalized children aged 0-4 years with confirmed ALRI published between 1995 and 2011. A total of 51 studies were included in the final review, comprising 56 091 hospitalized ALRI episodes.ResultsIV was detected in 3.0% (2.2%-4.0%) of all hospitalized ALRI cases, PIV in 2.7% (1.9%-3.7%), and AV in 5.8% (3.4%-9.1%). CV are technically difficult to culture, and they were detected in 4.8% of all hospitalized ALRI patients in one study. When respiratory syncytial virus (RSV) and less common viruses were included, at least one virus was detected in 50.4% (40.0%-60.7%) of all hospitalized severe ALRI episodes. Moreover, 21.9% (17.7%-26.4%) of these viral ALRI were mixed, including more than one viral pathogen. Among all severe ALRI with confirmed viral etiology, IV accounted for 7.0% (5.5%-8.7%), PIV for 5.8% (4.1%-7.7%), and AV for 8.8% (5.3%-13.0%). CV was found in 10.6% of virus-positive pneumonia patients in one study.ConclusionsThis article provides the most comprehensive analysis of the contribution of four viral causes to severe ALRI to date. Our results can be used in further cost-effectiveness analyses of vaccine development and implementation for a number of respiratory viruses.

The natural history of relapsing remitting multiple sclerosis (RRMS) is variable and prediction of individual prognosis challenging. The inability to reliably predict prognosis at diagnosis has important implications for informed decision making especially in relation to disease modifying therapies. We conducted a systematic review in order to collate, describe and assess the methodological quality of published prediction models in RRMS. We searched Medline, Embase and Web of Science. Two reviewers independently screened abstracts and full text for eligibility and assessed risk of bias. Studies reporting development or validation of prediction models for RRMS in adults were included. Data collection was guided by the checklist for critical appraisal and data extraction for systematic reviews (CHARMS) and applicability and methodological quality assessment by the prediction model risk of bias assessment tool (PROBAST). 30 studies were included in the review. Applicability was assessed as high risk of concern in 27 studies. Risk of bias was assessed as high for all studies. The single most frequently included predictor was baseline EDSS (n = 11). T2 Lesion volume or number and brain atrophy were each retained in seven studies. Five studies included external validation and none included impact analysis. Although a number of prediction models for RRMS have been reported, most are at high risk of bias and lack external validation and impact analysis, restricting their application to routine clinical practice.