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1.
Lancet Child Adolesc Health ; 7(5): 336-346, 2023 05.
Article in English | MEDLINE | ID: mdl-36924781

ABSTRACT

BACKGROUND: Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres. METHODS: For this meta-analysis, we identified individual participant data from a WHO public call for data on the management of tuberculosis in children and adolescents and referral from childhood tuberculosis experts. We included studies that prospectively recruited consecutive participants younger than 10 years attending health-care centres in countries with a high tuberculosis incidence for clinical evaluation of pulmonary tuberculosis. We collated individual participant data including clinical, bacteriological, and radiological information and a standardised reference classification of pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms. We then used the data to develop two multivariable prediction models that included features used in clinical evaluation of pulmonary tuberculosis-one with chest x-ray features and one without-and we investigated each model's generalisability using internal-external cross-validation. The parameter coefficient estimates of the two models were scaled into two scoring systems to classify tuberculosis with a prespecified sensitivity target. The two scoring systems were used to develop two pragmatic, treatment-decision algorithms for use in primary health-care settings. FINDINGS: Of 4718 children from 13 studies from 12 countries, 1811 (38·4%) were classified as having pulmonary tuberculosis: 541 (29·9%) bacteriologically confirmed and 1270 (70·1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. The scoring system derived from the prediction model that included clinical features and features from chest x-ray had a combined sensitivity of 0·86 [95% CI 0·68-0·94] and specificity of 0·37 [0·15-0·66] against a composite reference standard. The scoring system derived from the model that included only clinical features had a combined sensitivity of 0·84 [95% CI 0·66-0·93] and specificity of 0·30 [0·13-0·56] against a composite reference standard. The scoring system from each model was placed after triage steps, including assessment of illness acuity and risk of poor tuberculosis-related outcomes, to develop treatment-decision algorithms. INTERPRETATION: We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in primary health-care settings with high tuberculosis incidence and limited resources to initiate tuberculosis treatment in children to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Future prospective evaluation of algorithms, including those developed in this work, is necessary to investigate clinical performance. FUNDING: WHO, US National Institutes of Health.


Subject(s)
Tuberculosis, Pulmonary , Tuberculosis , United States , Adolescent , Humans , Child , Retrospective Studies , Tuberculosis, Pulmonary/diagnosis , Tuberculosis, Pulmonary/drug therapy , Tuberculosis, Pulmonary/epidemiology , Triage , Algorithms
2.
J Int Assoc Provid AIDS Care ; 20: 23259582211017742, 2021.
Article in English | MEDLINE | ID: mdl-34013809

ABSTRACT

BACKGROUND: Maintaining essential HIV services has being a Global challenge during the COVID-19 crises. Myanmar has 54 million inhabitants. Neighbor of China, Thailand, India and Bangladesh it was impacted by COVID-19, but came up with a comprehensive and effective response, following WHO recommendations. The HIV Prevalence is 0.58% and it is concentrated among key population. A HIV Contingency Plan was developed to face this challenge. METHODOLOGY: The programme-based cross-sectional descriptive study with analysis of routinely collected data from MoHS data system, between 2019 and 2020 was conducted, comparing first six months of 2019 and 2020. RESULTS: HIV outreach activities and HIV testing were slightly affected after detection of first COVID-19 case, till mid May 2020. After that, outreach activities resumed. Introduction of HIV self-testing was initiated. 72% of more than 21,000 PWID on MMT were receiving take home dose up to 14 days and 60% of ART patients were receiving 6 months ARV dispensing. CONCLUSION: Essential HIV services were maintained.


Subject(s)
COVID-19/epidemiology , Community Health Services/methods , HIV Infections/prevention & control , HIV Infections/diagnosis , HIV Infections/drug therapy , HIV Infections/epidemiology , Health Plan Implementation , Humans , Myanmar/epidemiology , SARS-CoV-2
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