Medicine (RMH) - Research Publications
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ItemNo Preview AvailableLow serum mannose-binding lectin level increases the risk of death due to pneumococcal infection(OXFORD UNIV PRESS INC, 2008-08-15)BACKGROUND: Previous studies have shown associations between low mannose-binding lectin (MBL) level or variant MBL2 genotype and sepsis susceptibility. However, MBL deficiency has not been rigorously defined, and associations with sepsis outcomes have not been subjected to multivariable analysis. METHODS: We reanalyzed MBL results in a large cohort with use of individual data from 4 studies involving a total of 1642 healthy control subjects and systematically defined a reliable deficiency cutoff. Subsequently, data were reassessed to extend previous MBL and sepsis associations, with adjustment for known outcome predictors. We reanalyzed individual data from 675 patients from 5 adult studies and 1 pediatric study of MBL and severe bacterial infection. RESULTS: XA/O and O/O MBL2 genotypes had the lowest median MBL concentrations. Receiver operating characteristic analysis revealed that an MBL cutoff value of 0.5 microg/mL was a reliable predictor of low-producing MBL2 genotypes (sensitivity, 82%; specificity, 82%; negative predictive value, 98%). MBL deficiency was associated with increased likelihood of death among patients with severe bacterial infection (odds ratio, 2.11; 95% confidence interval, 1.30-3.43). In intensive care unit-based studies, there was a trend toward increased risk of death among MBL-deficient patients (odds ratio, 1.58; 95% confidence interval, 0.90-2.77) after adjustment for Acute Physiology and Chronic Health Enquiry II score. The risk of death was increased among MBL-deficient patients with Streptococcus pneumoniae infection (odds ratio, 5.62; 95% confidence interval, 1.27-24.92) after adjustment for bacteremia, comorbidities, and age. CONCLUSIONS: We defined a serum level for MBL deficiency that can be used with confidence in future studies of MBL disease associations. The risk of death was increased among MBL-deficient patients with severe pneumococcal infection, highlighting the pathogenic significance of this innate immune defence protein.
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ItemNo Preview AvailableBayesian modelling of an epidemic of severe acute respiratory syndrome(SPRINGER, 2006-05)This paper analyses data arising from a SARS epidemic in Shanxi province of China involving a total of 354 people infected with SARS-CoV between late February and late May 2003. Using Bayesian inference, we have estimated critical epidemiological determinants. The estimated mean incubation period was 5.3 days (95% CI 4.2-6.8 days), mean time to hospitalisation was 3.5 days (95% CI 2.8-3.6 days), mean time from symptom onset to recovery was 26 days (95% CI 25-27 days) and mean time from symptom onset to death was 21 days (95% CI 16-26 days). The reproduction ratio was estimated to be 4.8 (95% CI 2.2-8.8) in the early part of the epidemic (February and March 2003) reducing to 0.75 (95% CI 0.65-0.85) in the later part of the epidemic (April and May 2003). The infectivity of symptomatic SARS cases in hospital and in the community was estimated. Community SARS cases caused transmission to others at an estimated rate of 0.4 per infective per day during the early part of the epidemic, reducing to 0.2 in the later part of the epidemic. For hospitalised patients, the daily infectivity was approximately 0.15 early in the epidemic, but fell to 0.0006 in the later part of the epidemic. Despite the lower daily infectivity level for hospitalised patients, the long duration of the hospitalisation led to a greater number of transmissions within hospitals compared with the community in the early part of the epidemic, as estimated by this study. This study investigated the individual infectivity profile during the symptomatic period, with an estimated peak infectivity on the ninth symptomatic day.
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ItemA Biological Model for Influenza Transmission: Pandemic Planning Implications of Asymptomatic Infection and Immunity(PUBLIC LIBRARY SCIENCE, 2007-11-28)BACKGROUND: The clinical attack rate of influenza is influenced by prior immunity and mixing patterns in the host population, and also by the proportion of infections that are asymptomatic. This complexity makes it difficult to directly estimate R(0) from the attack rate, contributing to uncertainty in epidemiological models to guide pandemic planning. We have modelled multiple wave outbreaks of influenza from different populations to allow for changing immunity and asymptomatic infection and to make inferences about R(0). DATA AND METHODS: On the island of Tristan da Cunha (TdC), 96% of residents reported illness during an H3N2 outbreak in 1971, compared with only 25% of RAF personnel in military camps during the 1918 H1N1 pandemic. Monte Carlo Markov Chain (MCMC) methods were used to estimate model parameter distributions. FINDINGS: We estimated that most islanders on TdC were non-immune (susceptible) before the first wave, and that almost all exposures of susceptible persons caused symptoms. The median R(0) of 6.4 (95% credibility interval 3.7-10.7) implied that most islanders were exposed twice, although only a minority became ill in the second wave because of temporary protection following the first wave. In contrast, only 51% of RAF personnel were susceptible before the first wave, and only 38% of exposed susceptibles reported symptoms. R(0) in this population was also lower [2.9 (2.3-4.3)], suggesting reduced viral transmission in a partially immune population. INTERPRETATION: Our model implies that the RAF population was partially protected before the summer pandemic wave of 1918, arguably because of prior exposure to interpandemic influenza. Without such protection, each symptomatic case of influenza would transmit to between 2 and 10 new cases, with incidence initially doubling every 1-2 days. Containment of a novel virus could be more difficult than hitherto supposed.