Medical Research Council

About: Medical Research Council is a government organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Malaria. The organization has 16430 authors who have published 19150 publications receiving 1475494 citations.

Effect of loud noise on attentional selectivity

Abstract: The effects of loud noise are examined by observing its influence upon a combined tracking and multi-source monitoring task. Tracking (the primary task) improves in noise, as does the detection of centrally located signals in the monitoring task. Peripheral signals are detected less often in noise. The data are interpreted in terms of increased selectivity of attention with arousal.

Bias modelling in evidence synthesis

Abstract: Policy decisions often require synthesis of evidence from multiple sources, and the source studies typically vary in rigour and in relevance to the target question We present simple methods of allowing for differences in rigour (or lack of internal bias) and relevance (or lack of external bias) in evidence synthesis The methods are developed in the context of reanalysing a UK National Institute for Clinical Excellence technology appraisal in antenatal care, which includes eight comparative studies Many were historically controlled, only one was a randomized trial and doses, populations and outcomes varied between studies and differed from the target UK setting Using elicited opinion, we construct prior distributions to represent the biases in each study and perform a bias-adjusted meta-analysis Adjustment had the effect of shifting the combined estimate away from the null by approximately 10%, and the variance of the combined estimate was almost tripled Our generic bias modelling approach allows decisions to be based on all available evidence, with less rigorous or less relevant studies downweighted by using computationally simple methods

Osteoclasts derived from haematopoietic stem cells

Abstract: The origins of the multinucleated osteoclast have been controversial, with osteogenic precursors and haematopoietic stem cells as candidates. Recent evidence for the latter is persuasive but circumstantial. We report here direct evidence obtained in radiation chimaeras from a natural cytoplasmic cell marker transmitted by the donated haematopoietic stem cell.

Trichomonas vaginalis Is Associated with Pelvic Inflammatory Disease in Women Infected with Human Immunodeficiency Virus

Abstract: We assessed the association between the causative agents of vaginal discharge and pelvic inflammatory disease (PID) among women attending a rural sexually transmitted disease clinic in South Africa; the role played by coinfection with human immunodeficiency virus type 1 (HIV-1) was studied. Vaginal and cervical specimens were obtained to detect Neisseria gonorrhoeae, Chlamydia trachomatis, Trichomonas vaginalis, and bacterial vaginosis. HIV-1 infection was established by use of serum antibody tests. A total of 696 women with vaginal discharge were recruited, 119 of whom had clinical PID. Patients with trichomoniasis had a significantly higher risk of PID than did women without trichomoniasis (P = .03). PID was not associated with any of the other pathogens. When the patients were stratified according to HIV-1 status, the risk of PID in HIV-1-infected patients with T. vaginalis increased significantly (P = .002); no association was found in patients without HIV-1. T. vaginalis infection of the lower genital tract is associated with a clinical diagnosis of PID in HIV-1-infected women.

Multistate Markov models for disease progression with classification error

Abstract: Summary. Many chronic diseases have a natural interpretation in terms of staged progression. Multistate models based on Markov processes are a well-established method of estimating rates of transition between stages of disease. However, diagnoses of disease stages are sometimes subject to error. The paper presents a general hidden Markov model for simultaneously estimating transition rates and probabilities of stage misclassification. Covariates can be fitted to both the transition rates and the misclassification probabilities. For example, in the study of abdominal aortic aneurysms by ultrasonography, the disease is staged by severity, according to successive ranges of aortic diameter. The model is illustrated on data from a trial of aortic aneurysm screening, in which the screening measurements are subject to error. General purpose software for model implementation has been developed in the form of an R package and is made freely available.