Across Asia, a large proportion of people with tuberculosis (TB) do not report symptoms, have mild symptoms or only experience symptoms for a short duration. These individuals may not seek care at health facilities or may be missed by symptom screening, resulting in sustained TB transmission in the community. We evaluated the yields of TB from 114 days of community-based, mobile chest X-ray (CXR) screening. The yields at each step of the TB screening cascade were tabulated and we compared cohorts of participants who reported having a prolonged cough and those reporting no cough or one of short duration. We estimated the marginal yields of TB using different diagnostic algorithms and calculated the relative diagnostic costs and cost per case for each algorithm. A total of 34,529 participants were screened by CXR, detecting 256 people with Xpert-positive TB. Only 50% of those diagnosed with TB were detected among participants reporting a prolonged cough. The study’s screening algorithm detected almost 4 times as much TB as the National TB Program’s standard diagnostic algorithm. Community-based, mobile chest X-ray screening can be a high yielding strategy which is able to identify people with TB who would likely otherwise have been missed by existing health services.

Background: Dengue is a common mosquito-borne, with high morbidity rates recorded in the annual. Dengue contributes to a major disease burden in many tropical countries. This demonstrates the urgent need in developing effective approaches to identify severe cases early. For this purpose, many multivariable prognostic models using multiple prognostic variables were developed to predict the risk of progression to severe outcomes. The aim of the planned systematic review is to identify and describe the existing clinical multivariable prognostic models for severe dengue as well as examine the possibility of combining them. These findings will suggest directions for further research of this field. Methods: This protocol has followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta – Analyses Protocol (PRISMA-P). We will conduct a comprehensive search of Pubmed, Embase, and Web of Science. Eligibility criteria include being published in peer-review journals, focusing on human subjects and developing the multivariable prognostic model for severe dengue, without any restriction on language, location and period of publication, and study design. The reference list will be captured and removed from duplications. We will use the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist to extract data and Prediction study risk of bias assessment tool (PROBAST) to assess the study quality. Discussion: This systematic review will describe the existing prediction models, summarize the current status of prognostic research on dengue, and report the possibility to combine the models to optimize the power of each paradigm. PROSPERO registration: CRD42018102907

Background: Dengue is a common mosquito-borne, with high morbidity rates recorded in the annually. Dengue contributes a major disease burden in many tropical countries. This demonstrates the urgent need in developing effective approaches to identify severe cases early. For this purpose, many multivariable prognostic models using multiple prognostic variables were developed to predict the risk of progression to severe outcomes. The aim of the planned systematic review is to identify and describe the existing clinical multivariable prognostic models for severe dengue as well as examine the possibility of combining them. These findings will suggest directions for further research of this field. Methods: This protocol has followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta – Analyses Protocol (PRISMA-P). We will conduct a comprehensive search of Pubmed, Embase and Web of Science. Eligiblity criteria include being published in peer-review journals, focusing on human subjects and developing the multivariable prognostic model for severe dengue, without any restriction on language, location and period of publication, and study design. The reference list will be captured and removed from duplications. We will use the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist to extract data and Prediction study risk of bias assessment tool (PROBAST) to assess the study quality. Discussion: This systematic review will describe the existing prediction models, summarize the current status of prognostic research on dengue, and report the possibility to combine the models to optimize the power of each paradigm. PROSPERO registration: CRD42018102907

Myocardial infarction is a considerable burden on public health. However, there is a lack of information about its economic impact on both the individual and national levels. This study aims to estimate the incremental cost, readmission risk, and length of hospital stay due to myocardial infarction as a post-operative complication. We used data from a standardized national system managed by the Vietnam Social Insurance database. The original sample size was 1,241,893 surgical patients who had undergone one of seven types of surgery. A propensity score matching method was applied to create a matched sample for cost analysis. A generalized linear model was used to estimate direct treatment costs, the length of stay, and the effect of the complication on the readmission of surgical patients. Myocardial infarction occurs most frequently after vascular surgery. Patients with a myocardial infarction complication were more likely to experience readmission within 30 and 90 days, with an OR of 3.45 (95%CI: 2.92–4.08) and 4.39 (95%CI: 3.78–5.10), respectively. The increments of total costs at 30 and 90 days due to post-operative myocardial infarction were 4,490.9 USD (95%CI: 3882.3–5099.5) and 4,724.6 USD (95%CI: 4111.5–5337.8) per case, while the increases in length of stay were 4.9 (95%CI: 3.6–6.2) and 5.7 (95%CI: 4.2–7.2) per case, respectively. Perioperative myocardial infarction contributes significantly to medical costs for the individual and the national economy. Patients with perioperative myocardial infarction are more likely to be readmitted and face a longer treatment duration.