Rickettsial infections have been found to be the second most common cause of non-malarial febrile illness in Southeast Asia, just after dengue, and are largely neglected treatable causes of morbidity and mortality. The rickettsiae can be divided into three major groups: the scrub typhus group (STG), the typhus group (TG) and the spotted fever group (SFG). Rickettsial infections typically present with an acute fever and are difficult to diagnose due to the many different causes of undifferentiated fever in Southeast Asia. Rickettsial IgG seroprevalence, reflecting past infection, will give an estimate of the burden of rickettsial infections in the population. Background seroprevalence studies in countries around Myanmar have found high rates of rickettsial infections. Yet, in Myanmar there have been no prevalence studies on rickettsial infections since the Second World War. We plan to determine IgG levels to the three different groups of rickettsial infections in leftover blood samples in several clinics and hospitals in different regions of Myanmar.

开始日期2019-06-20

申办/合作机构

University of Medicine, Magway

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2023-05-01·The Lancet Child & Adolescent Health

Development of treatment-decision algorithms for children evaluated for pulmonary tuberculosis: an individual participant data meta-analysis

Article

作者: Cohen, Ted ; Ung, Vibol ; Cranmer, Lisa M ; Mandalakas, Anna ; Smith, Jonathan P ; Batool, Iraj ; Brands, Annemieke ; Banu, Sayera ; Mavhunga, Farai ; Sekadde, Moorine P ; Nampijja, Dorah ; Anwar, Aliya ; Nicol, Mark P ; Siddiqui, Sara Ahmed ; Sant'Anna, Clemax Couto ; Kabir, Senjuti ; Zar, Heather J ; Orikiriza, Patrick ; Hesseling, Anneke C ; Carratalá-Castro, Lucía ; Myint, Aye Aye ; Marcy, Olivier ; Bonnet, Maryline ; Seddon, James A ; Ahmed, Shakil ; Marais, Ben J ; Lopez-Varela, Elisa ; Click, Eleanor S ; Palmer, Megan ; Caws, Maxine ; Huynh, Julie ; Amanullah, Farhana ; Cain, Kevin P ; Viney, Kerri ; Muñoz, Johanna ; van der Zalm, Marieke M ; Augusto, Orvalho ; Myo, Kyaw ; Franke, Molly F ; Lecca, Leonid ; Graham, Stephen M ; Gunasekera, Kenneth S ; García-Basteiro, Alberto L ; Verkuijl, Sabine ; Thuong Thuong, Nguyen Thuy ; Walters, Elisabetta G ; Debray, Thomas P A ; Aurilio, Rafaela Baroni ; Warren, Joshua L ; Song, Rinn

BACKGROUNDMany 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.METHODSFor 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.FINDINGSOf 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.INTERPRETATIONWe 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.FUNDINGWHO, US National Institutes of Health.

2023-01-01·Environmental health and preventive medicine

Gestational arsenic exposure induces anxiety-like behaviors in F1 female mice by dysregulation of neurological and immunological markers.

Article

作者: Htway, Soe-Minn ; Kyi-Tha-Thu, Chaw ; Nohara, Keiko ; Win-Shwe, Tin-Tin ; Suzuki, Takehiro

BACKGROUNDArsenic is a harmful heavy metal and a well-known developmental neurotoxicant. Previously, we have reported that gestational arsenic exposure resulted in impaired social behaviors in F1 and F2 male mice. However, little is known about the developmental arsenic exposure on anxiety-like behavior. This study aimed to detect the effect of gestational arsenic exposure on anxiety-like behavior and related gene expressions in 74-week-old F1 female mice.METHODPregnant C3H/HeN mice (F0) were given drinking water containing 85 ppm sodium arsenite (NaAsO₂) from gestational day 8 to 18. The control mice were given tap water only. At 74-week-old, open field test was performed, then anxiety and apoptosis-related factors were determined by real_time RT_PCR and immunohistochemical analyses.RESULTSThe arsenite-exposed F1 female mice showed decreased center entry and center time in open field test. In addition, the number of grooming and fecal pallet was significantly increased in the arsenite-exposed F1 female mice compared to the control. Downregulation of brain-derived neurotrophic factor (BDNF), serotonin receptor (5HT1A) and upregulation of nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB), interleukin 1 β (IL-1β), cyclooxygenase 2 (COX2), caspase-3, Bcl2-associated X protein (Bax) were detected in the prefrontal cortex in the arsenite-exposed F1 female mice. Microglial marker ionized calcium-binding adapter molecule 1 (Iba1)-positive cells were increased in the arsenite-exposed F1 female mice. Moreover, a significantly increased plasma corticosterone level was observed in the arsenic-exposed F1 female mice.CONCLUSIONSThis study suggested that gestational arsenic exposure induced anxiety-like behavior accompanied with dysregulation of neurological and immunological markers, neuroinflammatory responses, neuronal apoptosis, and decreased neurogenesis in the prefrontal cortex of F1 female mice.

2022-10-01·Archives of Disease in Childhood

Myanmar paediatricians during military coup: we strike and survive

Letter

作者: Win, Thet Htar Shwe Sin ; Kyaw, Kaung Myat ; Me, Myint Me ; Winn, Wah Wah

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