Abstract

We have proposed a new scoring system (Anaphylaxis SCoring Aichi: ASCA) for a quantitative evaluation of the anaphylactic reaction that is observed in an oral food challenge (OFC). Furthermore, the TS/Pro (Total Score of ASCA/cumulative protein dose) can be a marker to represent the overall severity of a food allergy. We aimed to develop a prediction model for a severe allergic reaction that is provoked in a boiled egg white challenge. We used two separate datasets to develop and validate the prediction model, respectively. The development dataset included 198 OFCs, that tested positive. The validation dataset prospectively included 140 consecutive OFCs, irrespective of the result. A ‘severe reaction’ was defined as a TS/Pro higher than 31 (the median score of the development dataset). A multivariate logistic regression analysis was performed to identify the factors associated with a severe reaction and develop the prediction model. The following four factors were independently associated with a severe reaction: ovomucoid specific IgE class (OM-sIgE: 0–6), aged 5 years or over, a complete avoidance of egg, and a total IgE < 1000 IU/mL. Based on these factors, we made a simple scoring prediction model. The model showed good discrimination in a receiver operating characteristic analysis, area under the curve (AUC) = 0.84 in development dataset, AUC = 0.85 in validation dataset. The prediction model significantly improved the AUC in both datasets compared to OM-sIgE alone. This simple scoring prediction model was useful for avoiding risky OFC.

Abstract

During the last two decades, the development of sustainable transportation systems has been highlighted as a key element in solving environmental problems related to climate change and impacts on greenhouse gases. Globally, the transportation sector has become one of the main contributors to these environmental problems. Thus, the environmental impact assessment of this sector and the implications of new vehicle technologies have begun to be considered as first steps for any long-term future strategies in this sector. In Palestine, the lack of environmental data related to the transportation sector and the absence of studies that address the new vehicle technologies (such as hybrid vehicles) and their future implications make it difficult to set up any future strategies or plans. In this study, the current and the future environmental impacts of the transportation sector have been assessed, and the future implications of hybrid vehicles have been determined. The gross domestic product (GDP), population, and the number of vehicles for the period 1994–2018 have been used to develop an auto regressive integrated moving average (ARIMA) prediction model for the future number of vehicles. Then, the total traveled kilometers and the total consumed fuels (by diesel and gasoline vehicles) have been predicted. After that, the current and future (2020 and 2030) greenhouse gas (GHG) emissions, including CO"sub"2"/sub", N"sub"2"/sub"O, and CH"sub"4"/sub", have been estimated. Finally, the future implications of hybrid vehicles, based on two scenarios (10% and 20% hybrid vehicles) have been estimated. The results have showed that the estimated CO"sub"2"/sub", N"sub"2"/sub"O, and CH"sub"4"/sub" emissions from the transportation sector in 2020 are 4,842,164.5, 213.8, and 445.8 tons, which are very high, and even much higher than the total national emissions of 2014 (the only officially available data). Moreover, in 2030, replacing 20% of internal combustion engine vehicles (ICEVs) by hybrid vehicles would lead to 4.66% and 13.31% reductions in CO"sub"2"/sub" and N"sub"2"/sub"O, respectively, as compared to 100% ICEVs, while the CH"sub"4 "/sub"emissions will increase. However, the overall CO"sub"2"/sub"-equivalent will decrease by 5%; therefore, a more sustainable transport system will be achieved. Document type: Article