Bmc Med
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Meta Analysis
Trends of blood pressure and heart rate in normal pregnancies: a systematic review and meta-analysis.
Current reference ranges for blood pressure and heart rate throughout pregnancy have a poor evidence base. ⋯ PROSPERO CRD42014009673.
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The epidemiology of CNS infections in Europe is dynamic, requiring that clinicians have access to up-to-date clinical management guidelines (CMGs) to aid identification of emerging infections and for improving quality and a degree of standardisation in diagnostic and clinical management practices. This paper presents a systematic review of CMGs for community-acquired CNS infections in Europe. ⋯ We identified variations in the quality and recommendations of CMGs for community-acquired CNS infections in use across Europe. A harmonised European "framework-CMG" with adaptation to local epidemiology and risks may improve access to up-to-date CMGs and the early identification and management of (re-)emerging CNS infections with epidemic potential.
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Diagnostic codes from electronic health records are widely used to assess patterns of disease. Infective endocarditis is an uncommon but serious infection, with objective diagnostic criteria. Electronic health records have been used to explore the impact of changing guidance on antibiotic prophylaxis for dental procedures on incidence, but limited data on the accuracy of the diagnostic codes exists. Endocarditis was used as a clinically relevant case study to investigate the relationship between clinical cases and diagnostic codes, to understand discrepancies and to improve design of future studies. ⋯ Commonly used diagnostic codes in studies of endocarditis had good predictive ability. Other apparently plausible codes were poorly predictive. Use of diagnostic codes without examining sensitivity and predictive ability can give inaccurate estimations of incidence and trends. Similar considerations may apply to other diseases. Health record studies require validation of diagnostic codes and careful data curation to minimise risk of serious errors.
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In 2015, the Zika virus spread from Brazil throughout the Americas, posing an unprecedented challenge to the public health community. During the epidemic, international public health officials lacked reliable predictions of the outbreak's expected geographic scale and prevalence of cases, and were therefore unable to plan and allocate surveillance resources in a timely and effective manner. ⋯ Sensitivity analysis illustrated the model performance to be robust across a range of features. Critically, the model performed consistently well at various stages throughout the course of the outbreak, indicating its potential value at any time during an epidemic. The predictive capability was superior for shorter forecast windows and geographically isolated locations that are predominantly connected via air travel. The highly flexible nature of the proposed modeling framework enables policy makers to develop and plan vector control programs and case surveillance strategies which can be tailored to a range of objectives and resource constraints.