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Background In the absence of proper guidelines and algorithms, available rapid diagnostic tests (RDTs) for common acute undifferentiated febrile illnesses are often used inappropriately. Methods Using prevalence data of 5 common febrile illnesses from India and Cambodia, and performance characteristics (sensitivity and specificity) of relevant pathogen-specific RDTs, we used a mathematical model to predict the probability of correct identification of each disease when diagnostic testing occurs either simultaneously or sequentially in various algorithms. We developed a web-based application of the model so as to visualize and compare output diagnostic algorithms when different disease prevalence and test performance characteristics are introduced. Results Diagnostic algorithms with appropriate sequential testing predicted correct identification of etiology in 74% and 89% of patients in India and Cambodia, respectively, compared with 46% and 49% with simultaneous testing. The optimally performing sequential diagnostic algorithms differed in India and Cambodia due to varying disease prevalence. Conclusions Simultaneous testing is not appropriate for the diagnosis of acute undifferentiated febrile illnesses with presently available tests, which should deter the unsupervised use of multiplex diagnostic tests. The implementation of adaptive algorithms can predict better diagnosis and add value to the available RDTs. The web application of the model can serve as a tool to identify the optimal diagnostic algorithm in different epidemiological settings, while taking into account the local epidemiological variables and accuracy of available tests. [ABSTRACT FROM AUTHOR]

Abstract: Aim: To assess the prevalence and predictors of post-transplant diabetes mellitus (PTDM) in Chinese renal recipients and describe their long-term evolution of glucose metabolism. Methods: 887 non-diabetic Chinese adult renal recipients were studied retrospectively, with a median follow-up of 7 years. PTDM patients were categorized into transient PTDM and permanent PTDM. The cumulative incidence and risk factors of PTDM were estimated by Kaplan–Meier and Cox regression. Results: The cumulative incidence of PTDM at 3 months, 1, 3, 5, 10, 15 and 20 years post-transplant was 10.4%, 11.4%, 13.4%, 15.2%, 22.7%, 27.9% and 38.3%, respectively. 61.9% of PTDM cases were diagnosed within the first three months and 61.6% of them developed persistent diabetes in the future. Risk factors for all PTDM included older age, body mass index (BMI)≥25kg/m2, triglycerides≥1.5mmol/L, rejection, the use of tacrolimus and diltiazem. The predictors of permanent PTDM included age >50 years (RR=2.322, 95% CI 1.255–4.296, P =0.007), BMI≥25kg/m2 (RR=1.699, 95% CI 1.014–2.846, P =0.044) and the use of tacrolimus (RR=1.835, 95% CI 1.181–2.851, P =0.007). Conclusions: Patients were most susceptible to PTDM within the first three months post-transplant and more than half of them developed persistent diabetes in the future. Age >50 years, overweight and tacrolimus application were risk factors for both PTDM and permanent PTDM. [Copyright &y& Elsevier]