Factors responsible for elevated plasma B-type natriuretic peptide levels in severe aortic stenosis: Comparison between elderly and younger patients

AbstractBackgroundElevated plasma B-type natriuretic peptide (BNP) is a predictor of outcome and helpful for risk stratification in aortic stenosis (AS). However, left ventricular (LV) diastolic dysfunction progresses with aging and may also influence plasma BNP levels in elderly patients. We hypothesized that plasma BNP levels may be influenced by age in severe AS, and that factors that affect the elevation of plasma BNP levels may be different between elderly and younger patients with AS.MethodsWe performed echocardiography in 341 patients with severe AS [aortic valve area (AVA)<1.0cm2] and classified them into two groups by age (elderly ≥75 years old, n=201; younger patients <75 years old, n=140). We used multivariate linear regression analysis to assess the factors that determine plasma BNP levels in both groups.ResultsAge was found to be one of the independent determinants of plasma BNP levels in all patients (β=0.135, p=0.005). Although AVA was similar in the two groups, plasma BNP levels and E/e′ were significantly higher in elderly than younger patients [133.0 (IQR, 73.3–329.7)pg/dl vs 92.8 (IQR, 40.6–171.8)pg/dl, p<0.01; 20±8 vs 16±6, p<0.01, respectively). In multivariate stepwise linear regression analysis, AVA index, LV ejection fraction, mass index, E/e′, estimated systolic pulmonary artery pressure (eSPAS), and the presence of atrial fibrillation were independent determinants of plasma BNP levels in younger patients. In contrast, the independent determinants of plasma BNP levels in elderly patients were LV ejection fraction, mass index, E/e′, eSPAS, the presence of atrial fibrillation, age, and hemoglobin levels, but not AVA index.ConclusionsThere may be differences in the factors that influence plasma BNP levels between elderly and younger patients with severe AS. In elderly patients, plasma BNP levels may be influenced more by these factors than AS severity compared with younger patients

Microbiological Investigation of the Iron-Containing Floculent Mats in Various Deep Sea Environments

Conference abstract (August 14-19, 2011, Goldschmidt 2011 in Prague, Czech Republic)http://www.godac.jamstec.go.jp/darwin/cruise/natsushima/nt10-13_leg2/ehttp://www.godac.jamstec.go.jp/darwin/cruise/yokosuka/yk10-10/

各地の深海底に存在する褐色変色域での微生物調査

BE11-P72ポスター要旨 / ブルーアース2011（2011年3月7日～8日, 東京海洋大学品川キャンパス）http://www.godac.jamstec.go.jp/darwin/cruise/natsushima/nt05-18/ehttp://www.godac.jamstec.go.jp/darwin/cruise/natsushima/nt10-06_leg2/ehttp://www.godac.jamstec.go.jp/darwin/cruise/natsushima/nt10-13_leg2/ehttp://www.godac.jamstec.go.jp/darwin/cruise/yokosuka/yk10-10/

Methodology and Application of Spatial Vulnerability Assessment for Evacuation Shelters in Disaster Planning

Evacuation shelters are the most important means for safeguarding people in hazardous areas and situations, and thus minimizing losses, particularly those due to a disaster. Therefore, evacuation shelter assignment and evacuation planning are some of the critical factors for reducing vulnerability and increasing resilience in disaster risk reduction. However, an imbalance of shelter distribution and spatial heterogeneity of a population are the critical issues limiting the accessibility of evacuation shelters in real situations. In this study, we propose a methodology for spatial assessment to reduce vulnerability and evaluate the spatial distribution of both shelter demand and resources, considering spatial accessibility. The method was applied to the case study of Mabi, in the context of a disaster caused by the 2018 flooding. We applied this approach to evaluate the area and identified the vulnerability of the evacuation shelters and the residents. The proposed method revealed that 54.55% of the designated evacuation shelters and 59% of the total population were physically vulnerable to the flood. The results highlight, using GIS maps, that the total shelter capacity was significantly decreased to 43.86%. The outcome assessment addressed specific vulnerable shelters and the imbalance between the demand for and resources of each shelter. Accordingly, this study provides practical information and a valuable reference for supporting local governments and stakeholders to improve future disaster planning, prevention, and preparedness

EpiNurse, Health Monitoring by Local Nurses on Nepal Earth Quake 2015

The name, EpiNurse, refers to local nurses who perform epidemiological surveillance and care to ensure human security in and communicate with health authorities on the health status of communities. They collect and report epidemiological information by using easy-to-use technology in communities in which access to health information of the populace is hindered by catastrophic accidents or other geo-/socio-political reasons. EpiNurse Nepal Project (August 2015–April 2016) carried out epidemiological surveillances at 24 camps in 9 districts after the 2015 Nepal earthquake. By applying ICT and questionnaire, EpiNurse member nurses collected shelter-related data and information, such as location and timestamps, and geo-tagged photos. Identification of typical health behavior patterns and comparative information about differences between community and temporary shelters provided insights into the health security assessment. This initiative experiments how nurse should collect and deliver the health emergency information on their own local culture, lifestyle, and perceptions. The potential of EpiNurse concept lies not only in producing innovative research outcomes by improving or optimizing existing ICT application in health sector, but also in promoting research knowledge and exchange of ideas regarding social issues and challenges in the field of health emergency and community resilience. The most critical challenge in practice relates to collecting and storing data, which later would have been generated into reasonable health security index information to be used for predicting the likelihood of occurrence of health emergency events. It is necessary to apply human behavior modeling using geospatial technology in order to create data transferring modules for first responders and civilian populations regarding DRR and behaviors

Management of Health- and Disaster-Related Data

Prolonged health emergencies and disasters greatly affect health and well-being of individuals and communities. Past experiences on extreme emergencies and disasters have taught communities the value of preparedness. Information is key in responding to health crises especially in areas where health capacity is challenged. This chapter explains the necessity of identifying appropriate health and disaster data and proposes its transformation to information needed for decision-making. It presents different examples of systems and datasets that were used for the management of response during disasters and extreme emergencies. By introducing examples from Japan and Philippines; this chapter also points out that aside from medical data; nonmedical data; such as lifestyle and hygiene information; are necessary to protect the health of disaster victims.The objective of disaster response is to ensure that no one is left behind. It is imperative therefore that disaster response is complemented with targeted information. We recognized difficulties in community monitoring such as lack of geographic-specific information; no standard for minimum health security indicator; limited availability to submit data; and variances in need for meaningful information. There are also challenges in visualizing uncountable data; real-time updating of disaster situations; and accurate statistics disaggregated by characteristics. At the core of decision-making is the appropriate transformation of data to meaningful information. Utilization of data now becomes one of the essential adaptive technologies that needs to be provided at the local level. The challenge lies in preferential options in collecting and storing disaster- and health- and non-health-related data. Although the international initiatives expend significant effort to produce data and maps for the Health EDRM; this review considers the producers and end-users of the data products or how the data was used with the objective of studying mechanisms on how to improve on the product

Comparative Analysis of Microbial Communities in Iron-Dominated Flocculent Mats in Deep-Sea Hydrothermal Environments

It has been suggested that iron is one of the most important energy sources for photosynthesis-independent microbial ecosystems in the ocean crust. Iron-metabolizing chemolithoautotrophs play a key role as primary producers, but little is known about their distribution and diversity and their ecological role as submarine iron-metabolizing chemolithotrophs, particularly the iron oxidizers. In this study, we investigated the microbial communities in several iron-dominated flocculent mats found in deep-sea hydrothermal fields in the Mariana Volcanic Arc and Trough and the Okinawa Trough by culture-independent molecular techniques and X-ray mineralogical analyses. The abundance and composition of the 16S rRNA gene phylotypes demonstrated the ubiquity of zetaproteobacterial phylotypes in iron-dominated mat communities affected by hydrothermal fluid input. Electron microscopy with energy-dispersive X-ray microanalysis and X-ray absorption fine structure (XAFS) analysis revealed the chemical and mineralogical signatures of biogenic Fe-(oxy)hydroxide species and the potential contribution of Zetaproteobacteria to the in situ generation. These results suggest that putative iron-oxidizing chemolithoautotrophs play a significant ecological role in producing iron-dominated flocculent mats and that they are important for iron and carbon cycles in deep-sea low-temperature hydrothermal environments

Influence of baseline ejection fraction on the prognostic value of paravalvular leak after transcatheter aortic valve implantation

BACKGROUND: Moderate or severe paravalvular leak (PVL ≥ moderate) after transcatheter aortic valve implantation (TAVI) is associated with poor outcomes. The aim of this study was to assess whether the baseline ejection fraction (EF) affects the impact of PVL on mortality after TAVI. METHODS: We analyzed 514 consecutive patients with native severe aortic stenosis who underwent TAVI. Patients were divided into two groups: EF < 40% group (n = 84) and EF ≥ 40% group (n = 430) according to baseline EF. RESULTS: The mean age was 79.5 years and 49% were male. Patients in the EF < 40% group were younger and with higher logistic EuroSCORE compared to patients in the EF ≥ 40% group. Diabetes, coronary artery disease, atrial fibrillation and renal insufficiency were more prevalent in the EF < 40% group. Patients in the EF <40% group had more mitral regurgitation. In-hospital mortality was significantly higher in the EF < 40% group (8.3% vs. 0.9%, p < 0.0001). PVL ≥ moderate was significantly associated with increased 2-year estimated mortality only in the EF <40% group (65% vs. 20%, log-rank p < 0.0001) whereas no difference was seen in the EF ≥40% group (24% vs. 19%, log-rank p = 0.509). Interaction between PVL ≥ moderate and EF < 40% was statistically significant. CONCLUSIONS: The impact of PVL ≥ moderate on mortality after TAVI was significant in the EF <40% group but not in the EF ≥ 40% group in our study. Even though operators should aim to minimize PVL in all TAVI patients, special attention is required for patients with reduced baseline EF