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Objective: Although influenza vaccination reduces the risk of atrial fibrillation (AF), its protective effect in patients with gout remains unclear. The present study aimed to evaluate the protective effect of influenza vaccination in patients with gout.Methods: A total of 26,243 patients with gout, aged 55 and older, were enrolled from the National Health Insurance Research Database (NHIRD) between 1 January 2001, and 31 December 2012. The patients were divided into vaccinated (n = 13,201) and unvaccinated groups (n = 13,042). After adjusting comorbidities, medications, sociodemographic characteristics, the risk of AF during follow-up period was analyzed.Results: In influenza, non-influenza seasons and all seasons, the risk of AF was significantly lower in vaccinated than in unvaccinated patients (Adjust hazard ratio [aHR]: 0.59, 95% confidence interval [CI]: 0.50–0.68; aHR: 0.50, 95% CI: 0.42–0.63; aHR: 0.55, 95% CI: 0.49–0.62, respectively). In addition, the risk of AF significantly decreased with increased influenza vaccination (aHR: 0.85, 95% CI: 0.69–1.04; aHR: 0.72, 95% CI: 0.60–0.87; aHR: 0.40, 95% CI: 0.33–0.49, after first, 2–3 times, and ≥4 times of vaccination, respectively). Furthermore, sensitivity analysis indicated that the risk of AF significantly decreased after influenza vaccination for patients with different sexes, medication histories, and comorbidities.Conclusions: Influenza vaccination is associated with a lower risk of AF in patients with gout. This potentially protective effect seems to depend on the dose administered.

Background: Outbreaks of several serious infectious diseases have occurred in recent years. In response, to mitigate public health risks, countries worldwide have dedicated efforts to establish an information system for effective disease monitoring, risk assessment, and early warning management for international disease outbreaks. A cloud computing framework can effectively provide the required hardware resources and information access and exchange to conveniently connect information related to infectious diseases and develop a cross-system surveillance and control system for infectious diseases. Objective: The objective of our study was to develop a Hospital Automated Laboratory Reporting (HALR) system based on such a framework and evaluate its effectiveness. Methods: We collected data for 6 months and analyzed the cases reported within this period by the HALR and the Web-based Notifiable Disease Reporting (WebNDR) systems. Furthermore, system evaluation indicators were gathered, including those evaluating sensitivity and specificity. Results: The HALR system reported 15 pathogens and 5174 cases, and the WebNDR system reported 34 cases. In a comparison of the two systems, sensitivity was 100% and specificity varied according to the reported pathogens. In particular, the specificity for Streptococcus pneumoniae, Mycobacterium tuberculosis complex, and hepatitis C virus were 99.8%, 96.6%, and 97.4%, respectively. However, the specificity for influenza virus and hepatitis B virus were only 79.9% and 47.1%, respectively. After the reported data were integrated with patients’ diagnostic results in their electronic medical records (EMRs), the specificity for influenza virus and hepatitis B virus increased to 89.2% and 99.1%, respectively. Conclusions: The HALR system can provide early reporting of specified pathogens according to test results, allowing for early detection of outbreaks and providing trends in infectious disease data. The results of this study show that the sensitivity and specificity of early disease detection can be increased by integrating the reported data in the HALR system with the cases’ clinical information (eg, diagnostic results) in EMRs, thereby enhancing the control and prevention of infectious diseases.