Studying Students' Knowledge of the Benefits, Challenges, and Applications of Big Data Analytics in Healthcare

The purpose of this study was to evaluate the students' familiarity from different universities of Mashhad with the benefits, applications and challenges of Big Data analysis. This is a cross-sectional study that was conducted on students of different fields, including Medical Engineering, Medical Informatics, Medical Records and Health Information Management in Mashhad-Iran. A questionnaire was designed. The designed questionnaire evaluated the opinion of students regarding benefits, challenges and applications of Big Data analytics. 200 students participated and participants' opinions were evaluated descriptively and analytically. Most students were between 20 and 30 years old. 43.5% had no work experience. Current and previous field of study of most of the students were HIT, HIM, and Medical Records. Most of the participants in this study were undergraduates. 61.5% were economically active, 54.5% were exposed to Big Data. The mean scores of participants in benefits, applications, and challenges section were 3.71, 3.68, and 3.71, respectively, and process management was significant in different age groups (p=0.046), information, modelling, research, and health informatics across different fields of studies were significant (p=0.015, 0.033, 0.001, 0.024) Information and research were significantly different between groups (p=0.043 and 0.019), research in groups with / without economic activity was significant (p= 0.017) and information in exposed / non-exposed to Big Data groups was significant (p=0.02). Despite the importance and benefits of Big Data analytics, students' lack of familiarity with the necessity and importance is significant. The field of study and level of study does not appear to have an effect on the degree of knowledge of individuals regarding Big Data analysis. The design of technical training courses in this field may increase the level of knowledge of individuals regarding Big Data analysis

A Survey of Students’ Attitudes to Big Data Analysis in Iranian Universities

Today, with the emergence of new technologies and massive data, big data analysis has attracted the attention of researchers, industries and universities on a global scale. The present research aims to explore students’ attitude to big data analysis in different fields of study. The present cross-sectional study was conducted with students at different universities and fields of study in Iran. A questionnaire was developed. This questionnaire explored students’ attitude toward big data analysis. To this aim, 359 university students participated in the research. The data were analyzed using descriptive and inferential statistics. The age of the students ranged between 25 and 34 years. 55.2% were female and 54% were economically active. 40.9% had a work experience of less than a year. The academic degree of the majority of participants was master’s degree. 93.9% of the participants believed that big data analysis was essential for the country. 43.2% maintained that big data mostly belonged to the communication industry. 28.1% perceived MATLAB useful software for analysis. 40.9% were familiar with the benefits of analysis. Engage in economic activities, less than 1 year of experience and studies for a Master’s degree showed to be significantly correlated with familiarity with the benefits of big data (p≤0.01). Such issues as high costs, managers’ unfamiliarity and lack of expertise and complexity were raised by the respondents. Considering the undeniable benefits of big data analysis, it seems essential to familiarize university students with these analyses through particular training courses, conferences and so on

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Understanding the relationship between obesity/ fat distribution/metabolic profiles and vitamin D status in young women (the safe-D study)

© 2018 Dr Marjan TabeshVitamin D deficiency is highly prevalent and associated with an increased risk of many chronic health conditions including obesity, cardiovascular disease and diabetes. Vitamin D deficiency affects millions of Australians, causing considerable suffering, economic loss and mortality. The aim of this study was to evaluate the associations of vitamin D and obesity/fat distribution/metabolic profiles and examine the effects of behavioural intervention and vitamin D supplementation on weight / fat distribution and metabolic profiles in young women. This study was run in two parts. In Part A, we evaluated the associations of obesity/fat distribution/metabolic profiles and 25 hydroxyvitamin D (25 OHD) in a cross-sectional study of 407, 16-25 year-old women. In Part B in a controlled randomised clinical trial over a period of 12 months we examined the effects of behavioural intervention and vitamin D supplementation on weight, fat distribution and metabolic profiles in 123 young women with mild-to-moderate vitamin D deficiency (25 OHD between 25-75 nmol/L). Data were collected at baseline, 4 months and 12 months follow-ups using an online survey and when participants attended a site visit in a fasted state. Parameters including blood pressure, anthropometry, metabolic profiles, serum 25 OHD levels, and body composition (using dual energy X ray absorptiometry) were measured. For the cross-sectional analysis, we combined 407 Safe-D Part A data with 150 participants from another study, the Young Female Health Initiative (YFHI). Cross-sectional analyses showed that after adjustment for covariates, higher 25 OHD levels were associated with greater high density lipoprotein (HDL) levels and greater triglyceride levels. They were also associated with lower body mass index (BMI), total fat percentage, visceral fat percentage, visceral fat to total fat ratio and lower trunk fat to total fat ratio. Although these associations were statistically significant, they were very small in magnitude and of uncertain clinical significance. In the clinical trial part of the project, after four months of intervention, both vitamin D supplementation and the use of a mobile-based application (app), resulted in a significant increase in 25 OHD levels. There were no significant differences between the three groups in lipid profiles, BMI or glucose metabolism after 4 months intervention. However, vitamin D supplementation resulted in a reduction in BMI, and behavioural intervention resulted in a significant reduction in haemoglobin A1c (HbA1c) when compared to baseline. Both the per protocol and intention to treat analyses were used to evaluate the effects of vitamin D improvements on cardiovascular risk factors after 12 months follow-up. In total, 102 participants were included in the 12 months follow-up intention to treat analysis. There were no significant differences in glucose metabolism, lipid profiles, systolic and diastolic blood pressure, anthropometric measures, high sensitivity C-reactive protein (hs-CRP) levels and body composition among the three groups after 12 months of follow-up. Results showed that the improvement in 25 OHD levels by either taking vitamin D supplements or increased safe sun exposure did not affect cardiovascular risk factors in healthy young women. In chapter 7 we evaluated the effects of behavioural intervention over one year follow-up on sun related behaviours. Time spent in the sun did not change following behavioural intervention but sun risky behaviours decreased significantly in summer time in this group. Moreover, in this study no significant associations were observed between ultraviolet radiation (UVR) exposure and skin type, ethnicity or skin sensitivity to sun light. However, significant positive association was observed between sun exposure and physical activity

Calcium-Vitamin D Cosupplementation Influences Circulating Inflammatory Biomarkers and Adipocytokines in Vitamin D-Insufficient Diabetics: A Randomized Controlled Clinical Trial

Context: To the best of our knowledge, no study has examined the effects of vitamin D-calcium cosupplementation on inflammatory biomarkers and adipocytokines in vitamin D-insufficient type 2 diabetics. Objective: This study was performed to assess the effects of vitamin D and calcium supplementation on inflammatory biomarkers and adipocytokines in vitamin D-insufficient people with type 2 diabetes. Methods: Totally, 118 diabetic patients were enrolled in this randomized, placebo-controlled clinical trial. After matching for age, sex, body mass index, type and dose of hypoglycemic agents, and duration of diabetes, subjects were randomly assigned into 4 groups receiving the following: 1) 50000 IU/wk vitamin D + calcium placebo; 2) 1000 mg/d calcium + vitamin D placebo; 3) 50 000 IU/wk vitamin D + 1000 mg/d calcium; or 4) vitamin D placebo + calcium placebo for 8 weeks. Blood sampling was done for the quantification of inflammatory biomarkers and adipocytokines at the study baseline and after 8 weeks of intervention. Results: Calcium (changes from baseline: −75±19 ng/ml, P = .01) and vitamin D alone (−56 ± 19 ng/mL, P = .01) and joint calcium-vitamin D supplementation (−92 ± 19 ng/mL, P = .01) resulted in a significant reduction in serum leptin levels compared with placebo (−9 ± 18 ng/mL). This was also the case for serum IL-6, such that calcium (−2 ± 1 pg/mL, P &amp;lt; .001) and vitamin D alone (−4 ± 1 pg/mL, P &amp;lt; .001) and their combination (−4 ± 1 pg/mL, P &amp;lt; .001) led to significant reductions compared with placebo (3 ± 1 pg/mL). After adjustment for potential confounders, individuals in the calcium (−3.1 ± 1.3, P &amp;lt; .05), vitamin D (−3.1 ± 1.3, P &amp;lt; .05), and joint calcium-vitamin D groups (−3.4 ± 1.3, P &amp;lt; .05) had greater reductions in serum TNF-α concentrations compared with placebo (0.1 ± 1.2). Individuals who received joint calcium-vitamin D supplements tended to have a decrease in serum high-sensitivity C-reactive protein levels compared with placebo after controlling for baseline levels (−1.14 ± 0.25 vs 0.02 ± 0.24 ng/mL, P = .09). Conclusion: Joint calcium-vitamin D supplementation might improve systemic inflammation through decreasing IL-6 and TNF-α concentrations in vitamin D-insufficient people with type 2 diabetes. </jats:sec

The relationship between vegetables and fruits intake and glycosylated hemoglobin values, lipids profiles and nitrogen status in type II inactive diabetic patients

Background: The prevalence of obesity and associated chronic disease such as diabetes is rapidly increasing in all part of the world. The World Health Organization has predicted that between 1997 and 2025 the number of diabetic patients will increase from 143 million to about 300 million. In diabetic patients, oxidative stress leads to non-enzymatic glycosylation of proteins such as hemoglobin and albumin, these proteins can play a significant role in pathogenesis of diabetes and development of chronic disorders in diabetic patients. Antioxidant nutrients can reduce the chronic disorders and complications of diabetes by inhibiting the oxidative reactions. Some important antioxidant such as vitamin A, vitamin C, vitamin E and selenium occur in vegetables and fruits. Our objective of this study was investigation of the relationship between vegetables and fruits intake ssand glycosylated hemoglobin (HbA1C) values in diabetic patients. Methods: One hundred and five diabetic patients participated in this cross-sectional study. The patients were referred to health center in Khomeini shahr. Glycosylated hemoglobin (HbA1C) values were measured by chromatography method. Data on dietary intake and vegetables and fruits consumption were obtained from validated food frequency questionnaires. Results: The unadjusted mean glycosylated hemoglobin (HbA1C) is significantly associated with the amount of vegetables and fruits intake ( P = 0.014), but the relationship between consumption of fruits and HbA1C is not significant and the relationship between consumption of vegetables and HbA1C was roughly significant ( P = 0.049). There were no significant relationship between vegetables and fruits intake and lipids profiles, BUN/creatinine and 24 h urinary protein ( P > 0.05). Conclusions : Intake of vegetables and fruits may reduce the glycosylated hemoglobin, therefore choosing the appropriate diet with high fruits and vegetables may help to develop antioxidant defense and reduce the HbA1C in diabetic patients but it did not have any impact on lipids profiles, BUN/creatinine and urine protein 24 h

Universities Students' Knowledge About Big Data Analysis

Introduction: Big data analysis has raised controversies today and attracted many students and academics for its dramatic advantages. The present research aims to investigate the extent to which students in different universities of Mashhad are familiar with this type of analysis.Material and Methods: The present cross-sectional research was conducted on university students of different fields of study in Mashhad, Iran. A questionnaire was developed based on a review of the related literature in PubMed, Google Scholar, Science Direct and EMBAS. The target questionnaire explored students' knowledge of big data analysis. To this aim, 142 students participated in this research and completed the target questionnaire. Their responses were analyzed descriptively.Results: The majority age of participants ranged between 21 and 28 years. 59% of these participants were female; 27% had less than a year of work experience; the academic grade of the majority of participants was Master's or Ph.D. 42% enjoyed a desirable knowledge of big data analysis. The largest number of hours of scientific and non-scientific studies belonged to basic science students and more specifically that of pharmacology.Conclusion: Despite the significance and benefits of big data analysis, students' unfamiliarity with the essentiality of these analyses in industries and research is considerable. It seems that the field or grade of studies has no effect on one's knowledge of big data analysis. Probably, the design of specialized educational courses with this concern can help to promote individuals' knowledge of big data analysis.</jats:p