View clinical trials related to Tuberculosis.
Filter by:The overall goal of this study is to conduct a Randomized Clinical Trial (RCT) to evaluate a tuberculosis treatment support tool (TB-TST), a cellular phone app developed using user-centered design principles and a paper-based drug metabolite urine test strip modified for home use for testing the presence of isoniazid drug metabolites in urine to directly monitor adherence to treatment, to improve treatment outcomes for patients with TB receiving self-administered treatment (SAT). Poor medication adherence to TB regimens, along with challenges in monitoring patients and returning them to treatment, are important contributing factors to poor outcomes and the development of drug resistance. With advances and proliferation of mobile technology platforms, there is substantial interest in the possible use of mobile health (mHealth) interventions to address these challenges. Of the mHealth approaches under investigation for TB adherence monitoring, drug metabolite testing has been identified as the most promising, ethical, and accurate, and the least intrusive and stigmatizing strategy compared to other mobile solutions, yet its potential remains largely unexplored. Additionally, mobile applications (apps) may provide personalized treatment supervision, increase patients' self-management and improve patient-provider communication by offering more advanced functionalities for patient support and monitoring. The existing version of the TB-TST app offers education on TB and its treatment, communication with a care-coordinator, tracks treatment adherence (both by self-reporting and direct metabolite test strip images), self-reports treatment side-effects, and retains patient's "diary" notes. This proposal builds on preliminary work to: 1) Refine the TB-TST intervention based on pilot study findings and apply principles of user-centered design; 2) Evaluate the impact of the TB-TST on treatment outcomes compared to usual care; 3) Assess patient and provider perceptions of the facilitators and barriers to implementation of the TB-TST and synthesize lessons learned with stakeholders and policy makers. Primary outcome will be treatment success. Secondary outcomes will include: treatment default rates, self-reported adherence, technology use and usability. Findings have broader implications not only for TB adherence but disease management more generally and will improve our understanding of how to support patients facing challenging treatment regimens
To address the multifaceted challenges associated with tuberculosis (TB) in-person directly observed therapy (DOT), the World Health Organization recently recommended countries maximize the use of digital adherence technologies. Sub-Saharan Africa needs to investigate the effectiveness of such technologies in local contexts and proactively contribute to global decisions around patient-centered TB care. This study aims to evaluate the effectiveness of pillbox-enabled self-administered therapy (SAT) compared to standard DOT on adherence to TB medication and treatment outcomes in Ethiopia. It also aims to assess the usability, acceptability, and cost-effectiveness (health-related quality of life and catastrophic costs) of the intervention from the patient and provider perspectives. It is designed as a multicenter, randomized, controlled, open-label, non-inferiority, effectiveness-implementation hybrid, mixed-methods, two-arm trial.
Title: Artificial Neural Network as Diagnostic Tools For Rifampicin-Resistant Tuberculosis In Indonesia. A Predictive Model Study and Economic Evaluation. Background: Drug-resistant tuberculosis has become a global threat particularly in Indonesia. The need to increase detection, followed by appropriate treatment is a concern in dealing with these cases. The rapid molecular test (specifically for detecting rifampicin-resistant) is now being utilized in health care service, particularly at primary care level with some challenges including the lack of quality control (including how to obtained and treat the specimen properly prior to the examination) which then, affect the reliability of the results. Drug-Susceptibility Test (DST) is still, the gold standard in diagnosing drug-resistant tuberculosis but this procedure is time-consuming and costly. The artificial intelligent including data exploration and modeling is a promising method to classify potential drug-resistant cases based on the association of several factors. Objective : 1. To develop a model using an artificial intelligence approach that is able to classify the possibility of rifampicin-resistant tuberculosis. 2. To assess the diagnostic ability and the accuracy of the model in comparison to existing rapid test and the gold standard 3. To evaluate the cost-effectiveness evaluation of Artificial Neural Network model in Web-Based Application in comparison with the standard diagnostic tools Methodology 1. A cross-sectional study involving all suspected drug-resistant tuberculosis cases that being referred to the study center to undergo rapid molecular test and DST test over the past 5 years. 2. A comprehensive, retrospective medical records assessment and tuberculosis individual report will be performed to obtain a variable of interest. 3. Questionnaire assessment for confirmation of insufficient information. 4. Model Building through machine learning and deep learning procedure 5. Model Validation and testing using training data set and data from the different study center Hypothesis : Artificial Intelligent Model will yield a similar or superior result of diagnostic ability compare the Rapid Molecular Test according to the Drug-Susceptibility Test. (Superiority Trial)
The current treatment regimen for MDR-TB has poor outcomes and costs of treating MDR-TB are greater than treating drug susceptible TB, both in terms of health service and patient-incurred costs. Urgent action is needed to Identify short, effective and tolerable treatments for people with MDR-TB. The PRACTECAL economic evaluation sub-study (PRACTECAL-EE) will take place alongside the TB PRACTECAL trial, aiming to assess the costs to patients and providers of such regimens and to estimate the cost-effectiveness and poverty impact of an introduction of new MDR-TB regimens in the three countries participating in the main study.
There is a growing interest for the use of stool samples as an alternative to respiratory samples for the diagnosis of intrathoracic TB in children unable to produce sputum. Unlike respiratory samples, stool samples require processing before molecular testing. Several groups have already evaluated different processing methods. However, it is difficult to know which method has the best accuracy and potential for use at Primary Health Care level, due to the difference in study designs and populations. Therefore, in this study, the investigators propose to evaluate the accuracy of different promising stool processing methods in the same population within the same study with an adapted design. Furthermore, no study has so far evaluated for stool testing the new Xpert MTB/RIF Ultra cartridge that has a lower level of detection than the previous Xpert MTB/RIF cartridge. The investigators propose to evaluate the accuracy of Xpert MTB/RIF Ultra (Ultra) performed on stool samples collected from children with presumptive TB and processed using four different processing methods (Standard sucrose flotation method, optimized sucrose flotation method, SPK, and SOS) against bacteriological results from respiratory specimens and to perform a head-to-head comparison of the diagnostic accuracy and feasibility of these different methods in Uganda and Zambia. The selection of processing methods was based on accuracy results, degree of simplification allowing their introduction at PHC level, and finding from the TB-Speed in-vitro stool processing study. The standard sucrose flotation method is kept to assess if results obtained with the optimised sucrose-flotation method in our in-vitro study can be reproduced in-vivo
This study explores primary care team members' knowledge, attitudinal, and skill gaps related to LTBI testing and treatment. The gaps identified will inform the design of a survey and telementoring educational program (TB infection ECHO course). The EMR data query will further explore the reach of the ECHO model. The hypothesis for this study is that the TB infection ECHO course will be feasible, will have a significant impact on primary care provider participants' learning and performance related to LTBI testing and treatment in their primary care practices, and will increase the number of LTBI tests and treatment prescribed in primary care.
This study aims to find an optimized initial regimen for pulmonary tuberculosis(PTB), evaluating the efficacy, safety and acceptability of isoniazid, rifampicin and moxifloxacin(HRM) for the intensive phase of initial therapy of PTB, compared with the standard initial regimen.
Tuberculosis (TB) is the third leading cause of death in Indonesia. Disturbingly, the prevalence survey showed that over half of TB cases in Indonesia are not notified. The huge private sector in Indonesia, comprising an estimated 70,000 practitioners, provides over 50% of health care but notifies less than 10% of all diagnosed TB cases. INSTEP2 is a cluster randomised controlled intervention trial. The multi-component public health intervention will be administered to private practitioners (PP) in Community Health Centre (CHC) clusters. The change in the number of TB notifications over 12 months before, and 12 months after, the intervention will be compared between study arms. Hypothesis related to the Primary Efficacy Endpoint: A tailored intervention in PPs will increase TB notifications.
Pretomanid is being used in an antimicrobial combination regimen(s) to treat patients with pulmonary tuberculosis (TB). The primary purpose of the Male Reproductive Safety - "BPaMZ/SEM"- clinical study is to evaluate the potential effect of pretomanid on human testicular function whilst being used in a 26 weeks antimicrobial combination regimen consisting of bedaquiline (B) plus pretomanid (Pa) plus moxifloxacin (M) and pyrazinamide (Z) (BPaMZ).
Technology that has a particular focus on patients' needs and ease-of-use and -access plays a significant role in the development of e-health and m-health. The proposed model of a secured mobile health application may promote patient's self-management and enhances adherence in chronic therapy exactly as it is easy-to-use, reducing patient's burden in accessing medication information and instructions, and providing the opportunity for direct communications with health providers in charge for each patient with access to mobile technologies. Consequently, medication errors and unnecessary paperwork in the healthcare system will be avoided as well as giving more time for healthcare providers to pay greater attention to delivering medical care effectively and efficiently.