Epidemiology of soil transmitted helminth and Strongyloides stercoralis infections in remote rural villages of Ranomafana National Park, Madagascar.

Soil-transmitted helminth (STH) infections carry the highest number of disability adjusted life years among all neglected tropical diseases, disproportionately affecting low-income countries such as Madagascar.  This study describes the epidemiology of STH and S. stercoralis infections in twelve remote villages surrounding Ranomafana National Park (RNP), Ifanadiana, Madagascar. Questionnaires and stool samples were collected from 574 subjects from random households. The Kato-Katz method and spontaneous sedimentation technique were used to examine stool samples for evidence of infection. Infection prevalence rates were 71.4% for Ascaris lumbricoides (95% CI: 67.7-75.1), 74.7% for Trichuris trichiura (95% CI: 71.1-78.2), 33.1% for hookworm (95% CI: 29.2-36.9), and 3.3% for Strongyloides stercoralis (95% CI: 1.84-4.77). Participants who were older in age (OR = 0.96; 95% CI: 0.95-0.99) and who had a high school education (OR = 0.17; 95% CI: 0.04-0.77) were less likely to be infected with a STH. Females were less likely to be infected with A. lumbricoides (OR = 0.52; 95% CI: 0.33-0.82). Participants living in villages further from the main road were more likely to be infected with a STH (F = 4.00, p = 0.02). Overall, this study found that 92.5% (95% CI: 90.3-94.6) of the people living in rural regions near RNP have at least one STH infection. This calls into question the current preventative chemotherapy (PC) program in place and suggests that further medical, socioeconomic, and infrastructural deveopments are needed to reduce STH prevalence rates among this underserved population.

Relationship Between the Subcostal and Right Lateral Ultrasound Views of Inferior Vena Cava Collapse: Implications for Clinical Use of Ultrasonography.

BACKGROUND: The collapsibility index of the inferior vena cava is traditionally visualized from the subcostal region in the sagittal plane, referred to here as cIVCSS. Alternatively, the collapsibility index of the inferior vena cava can be visualized from the right midaxillary line in the coronal plane, referred to here as cIVCRC. It is unclear whether values of cIVCRC are comparable with values of cIVCSS because the inferior vena cava collapses asymmetrically into an elliptical form, quantified as the flat ratio of the inferior vena cava (F-IVC). This study aimed (1) to establish if cIVCRC is concordant or discordant to cIVCSS, and (2) to describe how this concordance or discordance is related to F-IVC. METHODS: This single-center cross-sectional study enrolled 110 spontaneously breathing patients. Values of cIVCRC were compared with cIVCSS. Performance of cIVCRC ≥ 42% in predicting fluid responsiveness, defined as cIVCSS ≥ 42%, was assessed. F-IVC was also correlated to the difference between cIVCSS and cIVCRC. RESULTS: cIVCRC ≥ 42% was 61.5% sensitive (95% CI, 31.58%-86.14%) and 67.1% specific (95% CI, 55.81%-77.06%) for predicting cIVCSS ≥ 42%. cIVCRC underestimated cIVCSS. The degree of discordance between cIVCRC and cIVCSS was proportional to the value of F-IVC. CONCLUSIONS: cIVCRC and cIVCSS measures are discordant, where cIVCRC underestimates cIVCSS. The degree of discordance is directly proportional to the value of F-IVC. Therefore, we recommend that cIVCRC ≥ 42% be used to rule in, but not to rule out, fluid responsivity. Wherever possible, F-IVC should be assessed to understand the clinical relevance of cIVCRC.

OpenHealth Platform for Interactive Contextualization of Population Health Open Data.

The financial incentives for data science applications leading to improved health outcomes, such as DSRIP (bit.ly/dsrip), are well-aligned with the broad adoption of Open Data by State and Federal agencies. This creates entirely novel opportunities for analytical applications that make exclusive use of the pervasive Web Computing platform. The framework described here explores this new avenue to contextualize Health data in a manner that relies exclusively on the native JavaScript interpreter and data processing resources of the ubiquitous Web Browser. The OpenHealth platform is made publicly available, and is publicly hosted with version control and open source, at https://github.com/mathbiol/openHealth. The different data/analytics workflow architectures explored are accompanied with live applications ranging from DSRIP, such as Hospital Inpatient Prevention Quality Indicators at http://bit.ly/pqiSuffolk, to The Cancer Genome Atlas (TCGA) as illustrated by http://bit.ly/tcgascopeGBM.