Academic literature on the topic 'Latent Tuberculosis Infection (LTBI)'

More than 10 million people in the United States are known to have latent tuberculosis infection (LTBI), and more than 300,000 begin treatment for LTBI annually. However, many fail to adhere to therapy for numerous reasons. The purpose of this project was to evaluate the impact of a new guideline, Targeted Tuberculin Testing and the Treatment of Latent Tuberculosis, at inner-city tuberculosis (TB) control clinic in the United States. The practice-focused question for the project asked if the implementation of the clinical guideline using a shorter regimen improved LTBI treatment adherence. The health beliefs model was the framework used to guide the project. I analyzed data from deidentified LTBI treatment adherence records of 12 patients before the change to the shorter treatment regimens and 12 patient records 1 year after the change. Results after implementation of the new treatment guideline showed no improvement in adherence. Before the guideline implementation, 75% (n=9) of individuals had adhered to traditional therapy whereas, after the shortened course was implemented, only 66.7% (n=8) of the random sample adhered to treatment. It is important to evaluate new methods of treatment and determine success early to promote health and reduce complications of ineffective treatment of TB. These results can support positive social change by raising awareness of the need to evaluate new treatment effectiveness early. Such knowledge can help providers and clinicians examine the barriers to adherence to the medications used for treating TB and implement appropriate measures to overcome the obstacles.

In 2013 Burma, the country of origin for many refugees of whom have resettled in the U.S. was in the top three countries for notification of suspected Latent Tuberculosis Infection (LTBI). Approximately 5%-10% of individuals diagnosed with LTBI are at risk of developing active tuberculosis (TB) disease; the highest risk occurs within two years following the diagnosis. Burmese refugees face a high potential of developing LTBI during resettlement in the U.S. and are at high risk for subsequent TB. Currently, we have limited knowledge of the Burmese Chin refugees' explanatory model (EM) of LTBI. Understanding the EM of these refugees is important because one's EM facilitates the recognition and response to illness, including early diagnosis and treatment. In the context of LTBI, this relates to the potential prevention of active TB disease. The purpose of this ethnographic study was to discover the Burmese Chin refugees' EM of LTBI and to describe the barriers experienced in receiving LTBI treatment. Kleinman's EM provided a conceptual framework to guide this study. A Burmese refugee gatekeeper assisted with community immersion and participant recruitment. Purposive and snowball sampling were used to recruit participants. Data were collected through participant observation and semi-structured interviews. Three data analysis strategies for ethnography that were used included domain, taxonomic, and componential analyses. Domain analysis began after open, inductive coding of the data. Data saturation was reached and the research questions were answered with eight participants. Data from 15 key informant interviews were abstracted into three domains: EM of LTBI, Fear and Stigmatization, and Barriers to Receiving LTBI Treatment. The over-arching theme, LTBI: My Shadowbox was derived from these three domains, 11 categories, and 25 subcategories through iterative and inductive data analysis. The analysis revealed the participants' language, behavior patterns, beliefs, values and health seeking experiences of LTBI in the U.S. The findings from this study will help to inform culturally tailored interventions to reduce LTBI and TB health disparities among Burmese Chin refugees and potentially other Burmese refugee subgroups in the U.S. Knowledge of the Burmese Chin refugees' EM of LTBI can inform health policy for reducing LTBI treatment barriers.

The decision to give preventive treatment to a person with latent tuberculosis infection (LTBI) is a complex one in which morbidity and mortality from potential progression to active tuberculosis (TB) is weighed against the morbidity and mortality associated with potential adverse effects of treatment. Without objective evidence and careful, model-based evaluation of the evidence, it is likely the risks and benefits of the two alternative strategies (treatment or no treatment) will be inaccurately assessed. It is therefore apparent that medical practitioners need assistance when making decisions about treatment of LTBI. A number of decision analyses in the past that are summarised in a systematic review in this thesis have attempted to address this issue. However, the review identified the need for a more individualised decision analysis tool. Further, the systematic review highlighted the importance of using robust estimates of key variables in any decision analysis model on LTBI treatment and it showed that the inclusion of health-related quality of life adjustments has the potential to change the decision for or against treatment of LTBI. Thus, a systematic review of quality of life in TB-related health states was conducted. A new clinical decision aid is presented that has the potential to improve physicians’ capacity to make better and more consistent decisions on treatment for LTBI by taking patients’ individual clinical characteristics into account. It showed that treatment is beneficial in the majority of scenarios for patients with evidence of LTBI. Other aspects of preventive TB treatment that were examined in this thesis include the completion rate of treatment of LTBI, the risk of developing TB among contacts of patients with TB and the prevalence of LTBI and treatment of LTBI among this group.

<p> Approximately one-third of the world's population is infected with the bacteria that cause Tuberculosis (TB) and nearly nine million people around the world become sick with TB disease annually. A total of 10,521 TB cases were reported in the United States in 2011 with foreign-born and racial/ethnic minorities disproportionately affected. Treating Latent Tuberculosis infection (LTBI) is imperative in decreasing the incidence of TB disease as well as preventing strains of TB that are more difficult to treat. Past research studies have reported conflicting results regarding barriers to LTBI preventive therapy, success of shorter therapies, and how to best encourage compliance with LTBI preventive therapy. This study was guided by the Health Belief Model (HBM) using a comparative descriptive design to examine characteristics of subjects started on LTBI preventive therapy in 2010 and 2011 in a county in which adherence rates dropped from 76.9% in 2010 to 45.4% in 2011. The subjects included all persons identified with LTBI according to North Carolina TB Program guidelines that initiated preventive therapy in the years of 2010 and 2011, with a total of 13 subjects in 2010 and 11 in 2011. A record review was performed to gather information for analysis. Hispanic ethnicity was moderately associated with not completing LTBI preventive therapy. Significant differences between the study groups were reason for not completing therapy and risk factors for progression to TB disease, but neither was significantly associated with preventive therapy completion.</p>

The current, most widely used method to screen for latent tuberculosis infection is the Mantoux tuberculin skin test, where tuberculin is injected into a patient's arm and may result in a cutaneous induration forming at the site of injection. A diameter measurement of the resultant induration, recorded using a ruler and ball point pen, is currently used to indicate the presence of latent tuberculosis infection. Limitations associated with the tuberculin skin test procedure are the crudeness of the induration measurement method, the follow-up clinical visit required from patients to have their induration measured, and the need for trained clinicians who can perform the induration measurement. These limitations motivated research into a mobile phone-based screening system which can be used to obtain a more accurate measurement of the induration without the need for a second visit to the clinic by patients. The prototype screening tool consists of a user interface for capturing induration images and a backend processing system that produces a threedimensional reconstruction of the induration for measurement. Recommendations from previous studies on the prototype screening tool, which involved evaluation of the mobile application using mock induration images, included improving the accuracy of measuring the induration and evaluating the tool on real induration images. The aim of this study was to evaluate the existing backend system and explore an alternative assessment approach for assessing the induration. This was achieved through the following objectives: (1) applying the current backend system to real induration images, (2) examining the need for three-dimensional reconstruction for delineation of the induration for measurement and (3) exploring an alternative method for the assessment of induration images using deep learning. Results for the first objective showed the three-dimensional reconstruction to be unsuccessful on real images. This was due to the homogeneity between the indurations and the surrounding skin, rendering the algorithm ineffective in delineating the indurations to obtain the diameter measurement required for diagnosis. The second objective involved determining whether the image orientation or induration height affected the diagnostic measurement. It was found that real indurations are much flatter and more subtle compared to the mock indurations used in the previous studies. This motivated an alternative image assessment approach using deep learning. However, deep learning approaches require large databases of annotated images to prevent overfitting on training data. The last objective therefore involved the design and implementation of a generative adversarial network for generation of synthetic images from a limited number of real images, which allowed the generation of an unlimited number of realistic-looking synthetic images from 150 real induration images.

Adaptive Immunantworten gegen Mycobacterium tuberculosis (M. tuberculosis) sind von entscheidender Bedeutung für die effektive Eindämmung des Erregers sowie den Schutz vor einer erneuten, sekundären Tuberkulose (TB). Obwohl Schlüsselfaktoren wie die Th1 Zytokine IFN-gamma und TNF-alpha bekannt sind, blieben Bemühungen zur Identifizierung eindeutiger immunologischer Parameter, welche ausschlaggebend für den Krankheitsverlauf sind, bislang erfolglos. Ein besseres Verständnis der zugrunde liegenden Immunprozesse sowie die Identifikation projektiver Biomarker für TB sind zentrale Ziele dieser Arbeit. Zur Bearbeitung dieser Fragestellungen wurden adaptive Immunantworten gegen M. tuberculosis in gesunden Probanden mit LTBI und Patienten mit aktiver TB analysiert. Hierfür wurde die Erkennung unterschiedlicher Proteine des Erregers durch die Messung IFN-gamma exprimierender CD4+ CD45RO+ Gedächtnis T Zellen untersucht. Eine Besonderheit war die Einbeziehung sogenannter Latenz-assoziierter Proteine, welche in Zusammenhang mit Dormanz und Reaktivierung des Bakteriums stehen. 7 Tage in vitro Inkubation in Verbindung mit einer zweimaligen Restimulation belegten eine spezifische Erkennung durch CD4+ CD45RO+ T Zellen für die Mehrheit der getesteten Proteine bei Spendern mit LTBI. Der darauf folgende Vergleich zwischen Patienten mit aktiver TB und Personen mit LTBI zeigte signifikant höhere T Zell Antworten für 7 der 35 M. tuberculosis Proteine während LTBI. Bemerkenswerterweise konnten spezifische T Zellen für eines der Protein, nämlich Rv3407, ausschließlich während LTBI gemessen werden und nicht bei Patienten mit aktiver TB. Diskriminanz Analysen zeigten, dass eine Unterscheidung zwischen LTBI und TB Patienten basierend auf T Zell Antwort gegen ausgewählte Latenz-assoziierte Antigene mit einer Genauigkeit von 82% möglich ist. Erneut erwies sich Rv3407 als der mit Abstand bedeutendste Faktor innerhalb der ausgewählten M. tuberculosis Proteine.<br>Adaptive immune responses to Mycobacterium tuberculosis (M. tuberculosis) are crucial for an efficient containment of the pathogen and protection against secondary tuberculosis (TB). Although key mediators like the Th1 cytokines IFN-gamma and TNF-alpha released by M. tuberculosis-specific T cells are known, the immunological correlates determining the outcome of infection remain elusive. A better understanding of the underlying immune processes and the identification of protective biomarkers for TB are central aims of this thesis. To address these topics adaptive immune responses to M. tuberculosis were analyzed in healthy LTBI and patients with active pulmonary TB. The recognition of M. tuberculosis derived antigens was studied by measuring the expression of IFN-gamma in CD4+ CD45RO+ memory T cells. A special hallmark was the inclusion of latency proteins associated with dormancy, reactivation and resuscitation of the pathogen. Seven days in vitro incubation of PBMC and two rounds of restimulation followed by FACS analysis revealed T cell mediated recognition of the majority of tested latency-associated proteins in donors with LTBI. Comparison between active TB and LTBI documented significantly higher T-cell responses against 7 of 35 tested M. tuberculosis latency-associated antigens in LTBI. Notably, T cells specific for one M. tuberculosis antigen, namely Rv3407, were exclusively detected in the subgroup of LTBI. Discrimination analysis revealed that the T-cell response against selected antigens with our novel assay is capable of distinguishing TB patients and LTBI with 82% accuracy using cross-validation. Again Rv3407 was by far the most influential component present in this cluster. Peptide pool stimulation in a similar fashion identified single distinct candidate epitopes within Rv3407 in four LTBI.

Introduction: Despite management advances worldwide, tuberculosis still remains a serious uncontrolled disease. The absence of either a ‘gold’ standard diagnostic test, or a conventional rapid ‘reference’ laboratory test for asymptomatic Mycobacterium tuberculosis (MTB) carriers complicates disease control. Through mandatory screening of high-risk groups, early diagnosis of latent tuberculosis infection (LTBI) cases allows recognition and better control of the tuberculosis pandemic. Materials and Methods: The current tuberculosis screening guidelines as recommended by the World Health Organization, chest X-ray and tuberculin skin test were assessed and revealed rises in TB morbidity and fatality trends in the Kuwait population (low incidence country). In order to evaluate options for LTBI diagnosis, the current work implemented a 4-month prospective, observational, repeated-measure and randomly implemented survey on 180 new immigrants to Kuwait using a structured risk factor questionnaire whilst, simultaneously evaluating the performance of the two standard diagnostics (chest X-ray and tuberculin skin test) with the new biomarker interferon gamma release assays (T-SPOT .TB test and QuantiFERON Gold In-Tube test (QNF-GIT)); which detect the release of interferon gamma (INF-γ) released from sensitization to specific MTB antigens. Results: Associations between various epidemiological risk factors - such as socio-demographic status, smoking and environmental exposure-contact - were associated in the laboratory diagnosed LTBI participants. Positive identification of LTBI prevalence detected by two radiologists was 10.1% having ‘moderate’ inter-reader agreement (Kappa = 0.505), compared to no positives being detected by three pulmonologists. TST results were negative (less than 10-mm ‘cut-off’) even in the 86.1% Bacillus Calmette-Guérin vaccinated expatriates. Estimated LTBI using QNFGIT was 28.3% compared to 41.1% positive T-SPOT .TB test. Both interferon gamma assays revealed concordant ‘abnormal’ results in 26.1% with ‘good’ agreement (kappa = 0.627). Conclusion: Detection of latent tuberculosis infection can be facilitated by introducing evidence-based diagnostic classification depending on history taking of epidemiological-related risk factors and chest X-ray plus either interferon gamma assays.