Background Xpert MTB/RIF Ultra (Xpert Ultra) might have higher sensitivity than its predecessor, Xpert MTB/RIF (Xpert), but its role in tuberculous meningitis diagnosis is uncertain. We aimed to compare Xpert Ultra with Xpert for the diagnosis of tuberculous meningitis in HIV-uninfected and HIV-infected adults. Methods In this prospective, randomised, diagnostic accuracy study, adults (≥16 years) with suspected tuberculous meningitis from a single centre in Vietnam were randomly assigned to cerebrospinal fluid testing by either Xpert Ultra or Xpert at baseline and, if treated for tuberculous meningitis, after 3-4 weeks of treatment. Test performance (sensitivity, specificity, and positive and negative predictive values) was calculated for Xpert Ultra and Xpert and compared against clinical and mycobacterial culture reference standards. Analyses were done for all patients and by HIV status.

Background: Tuberculosis kills more people than any other bacterial infection worldwide. In tuberculous meningitis (TBM), a common functional promoter variant (C/T transition) in the gene encoding leukotriene A4 hydrolase (LTA4H), predicts pre-treatment inflammatory phenotype and response to dexamethasone in HIV-uninfected individuals. The primary aim of this study is to determine whether LTA4H genotype determines benefit or harm from adjunctive dexamethasone in HIV-uninfected Vietnamese adults with TBM. The secondary aim is to investigate alternative management strategies in individuals who develop drug induced liver injury (DILI) that will enable the safe continuation of rifampicin and isoniazid therapy.  Methods: We will perform a parallel group, randomised (1:1), double blind, placebo-controlled,  multi-centre Phase III non-inferiority trial, comparing dexamethasone versus placebo for 6-8 weeks in addition to standard anti-tuberculosis treatment in HIV-uninfected patients with TBM stratified by LTA4H genotype. The primary endpoint will be death or new neurological event. The trial will enrol approximately 720 HIV-uninfected adults with a clinical diagnosis of TBM, from two hospitals in Ho Chi Minh City, Vietnam. 640 participants with CC or CT- LTA4H genotype will be randomised to either dexamethasone or placebo, and the remaining TT- genotype participants will be treated with standard-of-care dexamethasone. We will also perform a randomised comparison of three management strategies for anti-tuberculosis DILI. An identical ancillary study will also be perfomed in the linked randomised controlled trial of dexamethasone in HIV-infected adults with TBM (ACT HIV).  Discussion: Previous data have shown that LTA4H genotype may be a critical determinant of inflammation and consequently of adjunctive anti-inflammatory treatment response in TBM. We will stratify dexamethasone therapy according to LTA4H genotype in HIV-uninfected adults, which may indicate a role for targeted anti-inflammatory therapy according to variation in LTA4H C/T transition. A comparison of DILI management strategies may allow the safe continuation of rifampicin and isoniazid.

Sokolow – Lyon index in detection of left ventricular hypertrophy is a hard limited index, so the clinical manifestation of the disease can be ignored when the measured index is near the threshold. Several proposed studies incorporate multiple index to improve diagnostic quality. However, the process of examination and diagnosis will be longer due to the need to collect more data. To solve this problem, the paper proposes a method of classifying left ventricular hypertrophy using fuzzy logic combining with digital signal processing techniques. The proposed method mainly uses the Sokolov-Lyon index (SV1+RV5/V6 ≥ 35 mm) for major changes in ECG signal but with four soft thresholds corresponding to the different clinical manifestations of the disease. In addition, a program is written in C++ language with QT Creator compiler also is developed to implement the algorithm. From there, the doctors can refer and propose to the patient's treatment regimen. Keywords ECG, left ventricular hypertrophy, signal processing, fuzzy logic. References [1] Malcolm S. Thaler, The only EKG book, seventh ed. Lippincott Williams & Wilinks, Philadelphia, 2012. [2] Vakili BA, Okin PM, Devereux RB, Prognostic implications of left ventricular hypertrophy, Am Heart J, 141(3) (2001) 334-341.https://doi.org/10.1067/mhj.2001.113218.[3] Tran Do Trinh, Tran Van Dong, How to read EGC signal, Medical Publishing House, 2011 (in Vietnamese).[4] Himanshu Gothwal1, Silky Kedawat1, Rajesh Kumar, Cardiac arrhythmias detection in an ECG beat signal using fast fourier transform and artificial neural network, J. Biomedical Science and Engineering 4 (2011) 289-296.https://doi.org/10.4236/jbise.2011.44039.[5] El-Sayed A. El-Dahshan, Genetic algorithm and wavelet hybrid scheme for ECG signal denoising, Journal of Telecommunications Systems 46(3) (2011) 209-215.https://doi.org/10.1007/s11235-010-9286-2.[6] C. Li, C. Zheng, and C. Tai, Detection of ECG characteristic points using wavelet transforms, IEEE Trans.Biomed. Eng 42(1) (1995) 21-28.https://doi.org/10.1109/10.362922.[7] A.K.M. Fazlul Haque1, Md. Hanif Ali1, M. Adnan Kiber2 and Md. Tanvir Hasan, Detection of small variations of ECG features using Wavelet, ARPN Journal of Engineering and Applied Sciences 4(6) (2009) 27-30.[8] Krimi Samar, Ouni Kas, Noureddine Ellouze, Using Hidden Markov Models for ECG Characterisation, Hidden Markov Models, Theory and Applications, 4 (2011) 151-165.https://doi.org/10.5772/13916.[9] Van Ngoc Tuyet, Bang Ai Vien, Nguyen Van Tri, Medical Journal Ho Chi Minh city, Diagnosis of left ventricular hypertrophy by ECG I 15(1) (2011) 135-140 (in Vietnamese).[10] Buckley, James J., Eslami, Esfandiar, Introduction to Fuzzy Logic and Fuzzy Sets, Physica-Verlag Heidelberg, Berlin, 2002. [11] Phan Xuan Minh, Nguyen Doan Phuoc, Fuzzy Control Theory, Science and Technics Publishing House, Ha Noi, 2006 (in Vietnamese).