João Ricardo Nickenig Vissoci

mHealth: Smart Wearable Devices and the Challenges of a Refractory Context

The development of smart wearable devices has strengthened a new area: mHealth. This is characterized by the use of mobile technologies for the diagnosis, monitoring, and intervention of health conditions. When inserted into the wider universe comprising the Internet of Things, mHealth solutions emerge with real-world applications. The myriad of mHealth-based applications already draws a scenario in which these new technologies will be responsible for changing the current logic of healthcare delivery. Nevertheless, there are numerous challenges for mHealth before its full potential can be realized. The Brazilian context is marked by peculiarities regarding the challenges for the dissemination of mHealth. There are few professionals, resistance to adopting new health technologies, an inexistent regulatory framework, regional inequalities, the absence of guidelines for protecting personal data, and difficulty associated with communication networks. Such aspects are discussed throughout this work together with components relating to the current status of development linked to mHealth.

PW 2468 Development of a predictive modeling approach to analysis of patient outcomes related to traumatic brain injury at a emergency center in a low income country

Prognostic models to support clinical decisions is an innovative solution to mitigate the increasing burden of traumatic brain injury (TBI) in low and medium income countries (LMIC). Hospitals, equipped with predictive models, can make data driven decisions based on patient prognosis to improve efficiency, productivity and outcomes. Furthermore, attempts to implement TBI predictive models are limited in both high and LMIC. The main objective of this study was to develop a predictive model for TBI outcomes. Our study is categorized as retrospective, with diagnostic temporal perspective, using the classification approach. Data comprising 3138 patients admitted with TBI were collected from 2014 to 2017. Data about demographics, injury type, vital signs, Glasgow Coma Score, surgeries and outcome observed were analyzed for each patient. Our model considered the good recovery obtained through the Glasgow outcome score extended scale as a result measure. Data were analyzed using Bayesian Generalized Linear Model. The average age of patients were 31.18% and 82.02% were men. Of all TBI patients 67.87% were victims of road traffic injury. Considering the good recovery as outcome our model achieved an accuracy of 0.865 (95% CI 0.859, 0.870), with a sensitivity level of 0.890 and specificity of 0.713. our detection rate of a good recovery due TBI interventions based on admission data were of 0.762. The main predictors of a good recovery were: Glasgow coma level score, pulse oximetry, availability of intensive care unit bed. A predictive model with high accuracy and kappa level can be generated from data available at patient admission in a low resource setting such as Tanzania, Kilimanjaro Christian Medical Centre hospital. To our knowledge, this is the first prognostic model for severe TBI using machine learning techniques in Sub-Saharan Africa.

PA 12-4-2523 Road traffic injuries and alcohol use in africa 2001–2014; a multi-national cross-sectional study

Africa has the second highest rate of alcohol dependence and road traffic fatality rate despite the lowest number of vehicles. Sub-Saharan Africa (SSA) is particularly vulnerable to the growing global burden of alcohol-related injury. Therefore, we aimed to describe and compare the proportion of emergency department (ED) patients presenting with RTIs who are breathalyzer (BAC) positive in three African countries and determine the alcohol dose-response. Secondary data analysis on RTI patients from the International Collaborative Alcohol and Injury Study in EDs used data from Mozambique (Moz, 2001), South Africa (SA, 2001) and Tanzania (Tz, 2014). Patients, 18 years or older, presenting to an ED within 6 hours of an injury had BAC testing and were asked whether they had been drinking prior to injury and the amount consumed. In Tanzania, self-reported alcohol use prior to the injury was collected for case-crossover analysis. Of 1433 patients, 38% (581) suffered RTIs (25% Moz, 21% SA, 73% Tz). Overall 28% of RTI patients were BAC positive (21% Moz, 34% SA, 29% Tz). In Tanzania, we found a 5.26 (CI 3.42 to 8.53) increased odds of RTI with any alcohol with a dose-dependent response. Both motorcycles and cars/trucks have an increased odds of RTI with any alcohol, 4.90 OR (CI 2.54 to 9.45) and 5.70 OR (CI 3.81 to 11.64) respectively; while cars/trucks had a dose dependent response, motorcyclists had their highest odds of injury at 3–4 drinks (5.60 OR, CI 2.22 to 14.10). The burden of road traffic injuries and particularly alcohol-associated road traffic injury is high in sub-Saharan Africa. All motorists have a six times higher odds of road traffic injury due to alcohol with a dose-dependent response while motorcyclists have a high odds of injury with even low doses of alcohol.

O papel mediador da autodeterminação sobre o efeito do perfeccionismo nas estratégias de enfrentamento em atletas juniores de futebol

Recentemente, alguns estudos tem apresentado as relacoes associativas entre os construtos Perfeccionismo (Pe) e Coping (Co), indicando ser um tema atual e importante. Este estudo tem por objetivo testar um modelo de relacoes preditivas das dimensoes Perfeccionismo Ajustado-Normal (PAN) e Perfeccionismo Desajustado-Neurotico (PDN), do construto Pe, sobre os Recursos Totais de Coping (RTC), do construto Co, quando mediadas pela Autodeterminacao (IAD), em uma amostra de atletas juniores de futebol. Para tanto, 182 atletas masculinos, com idades variando de 12 a 19 anos (14,86±1,97) de um clube de futebol do estado do Parana (Brasil), responderam aos seguintes instrumentos: Escala de Motivacao para o Esporte (EME-28), Inventario Atletico de Estrategias de Coping (IAEC-28) e Escala Multidimensional de Perfeccionismo (EMP-33). Os resultados de um Modelo de Equacoes Estruturais, testado sem a mediacao de IAD, explicaram 35% da variância de RTC; enquanto o MEE, considerando a mediacao de IAD, explicou 44% da variância de RTC apresentada pelos atletas. Os dados disponiveis permitem corroborar as hipoteses teoricas quanto a importância da Autodeterminacao na relacao entre Perfeccionismo e Coping. Salienta-se que novos estudos explorem amostras mais variadas permitindo ampliar a variabilidade de respostas e, consequentemente, melhorar ainda mais, por este vies, as relacoes hipotetico-preditivas testadas.