International Journal of Preventive Medicine
Volume:12 Issue: 2, Feb 2021

Hypothesis Chronic methylphenidate abuse or administration causes oxidative stress, inflammation, and mitochondrial dysfunction in brain cells that require therapeutic approaches to inhibit neurotoxicity and neurodegeneration of these types.[1,2] Nonetheless, the function of methylphenidate in the induction of neurodegeneration or neuroprotection is uncertain, but most of the data support the function of methylphenidate in neurodegeneration.

A key goal of clinical care is to treat patients as individuals and to approach therapeutics in such a way that it has optimal efficacy and minimal toxicity. With swift technological advances, such as genomic sequencing and molecular targeted drug exploitation, the concept of precision medicine has been robustly promoted in recent years. Precision medicine endeavors to demarcate diseases using multiple data sources from genomics to digital health metrics in order to facilitate an individualized yet “evidence‑based” decision regarding diagnostic and therapeutic approaches. In this way, therapeutics can be centered toward patients based on their molecular presentation rather than grouping them into broad categories with a “one size fits all” approach. This review article is aimed to provide a broad overview of the advent and emergence of precision medicine in view of its current implications.

Values are at the heart of discussions related to policy-making and any kind of reforms in health systems. Despite wide recognition of its importance, the concept of value is still vague and the policy-making processes remain astray with respect to values. This study aims to provide a model of value-based policy-making and to explain the concept value and how it affects policy-making.

The main question of the current study is to explain the concept of value-based policy-making and developing a model, based on the explained concept. In this line, critical review method and Carnwell and Daly approach and using particular keywords related to stewardship, and searching databases were used. In the initial search, 739 studies were obtained, of which using targeted sampling method, 11 studies were finally selected. Then, in order to design and explain different aspects of the value concept in the health system and to develop a model, selected studies were criticized, and finally, the conceptual model of value is designed and explained.

The concept of value and its effects, dimensions and its relation to principles, evidence and criteria were determined at different stages of the policy-making process. It was also revealed that value-based policy-making in a health system is contingent upon the realization of terminal values.

In the process of selecting the best policy option, it is necessary to identify the relationship between terminal, instrumental, criterion, and evidence to avoid deviating from the reference value framework in any country and to avoid blindly imitating other experiences in other countries.

Seizure and epilepsy are among the initial symptoms of multiple sclerosis (MS), yet different prevalence rates are reported for them in the previous studies. The goal of this systematic review is to estimate the pooled prevalence of seizure and epilepsy in patients with MS.

We searched PubMed, Scopus, EMBASE, Web of Science, google scholar, and gray literature including references from identified studies and conference abstracts published up to October 2019. The search strategy included the MeSH terms and text words as ((Epilepsies OR Seizure Disorder OR Seizure Disorders OR Awakening Epilepsy OR Epilepsy, Awakening OR Epilepsy, Cryptogenic OR Cryptogenic Epilepsies OR Cryptogenic Epilepsy OR Epilepsies, Cryptogenic OR epilepsy OR seizure) AND (Multiple Sclerosis OR Sclerosis, Multiple) OR Sclerosis, Disseminated) OR Disseminated Sclerosis) OR MS (Multiple Sclerosis)) OR Multiple Sclerosis, Acute Fulminating).

The literature review resulted in 4860 articles; 2593 articles remained after eliminating the duplicates. For the final analysis, 39 articles were included, 9 of which were conference abstracts. The pooled prevalence of seizure in MS cases was 2%, 95% confidence interval (CI)(1%‑3%) (I2 = 91.8%, P < 0.001). The pooled prevalence of epilepsy in MS cases was 3%, 95% CI (2%‑4%) (I2 = 92.9%, P < 0.001). The pooled prevalence of epilepsy in Asia, Europe, and America was 6%, 3%, and 3%, respectively. The level of heterogeneity decreased after subgroup analysis in Asian and American subgroups. Meta‑regression analysis showed continent is not a source of heterogeneity (coefficient = ‑0.007, P = 0.6).

The result of this systematic review shows that the pooled prevalence of seizure and epilepsy among MS patients is 2% and 3%, respectively

The world is full of data which is increasing by leaps and bounds. In health care, big data is becoming common with increased electronic health data accumulation and/or accessibility to public data previously held under lock and key. At the same time, health data visualization applications have become popular over recent years. Against this background, a review was done to summarize the application of data visualization in public health & the challenges faced. Peer‑reviewed original research articles and review articles searched in Google Scholar and Pubmed databases that were indexed in the last ten years period, using the keywords “Big data” or “data visualization” or “Interactive visualization techniques.” Other related information in books, blogs, and published documents were searched in Google search engine using the same keywords. Contents from the downloaded documents were presented and discussed under three headings viz. (a) the visualizations that are still current and how they have evolved further, (b) tools or methods that can be used by end‑users to make their own modifications, (c) the platforms to disseminate them. Usage of different plots in public health is explained with suitable examples using the data from public health datasets. From the discussion it can be understood that when big data is visualized well, it can identify implementation gaps and disparities and accelerate implementation strategies to reach the population groups in most need for interventions. As health administrator may come from diverse specialties, robust training and career development for big data in public health is the need of the hour.

The burden of gastrointestinal (GI) cancer is increasing worldwide, and in the past decade, cancer had entered the list of chronic debilitating diseases whose risk is substantially increased by hypernutrition. Obesity may increase the risk of cancer by the imbalance of various mechanisms including insulin and insulin‑like growth factor1 (IGF‑I) signaling, systemic inflammation, immune dysregulation, tumor angiogenesis, adipokines secretion, and intestinal microbiota that usually act interdependently. An increased understanding of the mechanisms underlying obesity‑GI cancer link can provide multiple opportunities for cancer prevention. This review discusses various mechanisms involved molecular mechanisms linking obesity with GI cancers including esophagus, stomach, colorectal and hepatocellular. Furthermore, an optional intervention such as diet restriction and exercise is described, which may be preventive or therapeutic in GI cancer.

Vitamin D is a hormone involved in bone mineral metabolism.[1] The hormone has many extraskeletal effects as well.[2,3] It has multiple immunomodulatory properties,[2] it is involved in glucose metabolism, as it has been proved that it improves glucose metabolism in diabetes mellitus[3] and has a protective role against cardiovascular disease.[4] In this issue of the Journal, in an article the relationship of vitamin D with kidney disease is meticulously reviewed.

Tobacco smoking is one of the most preventable causes of mortality related to noncommunicable diseases (NCDs). This study aimed to estimate the direct economic burden and years of life lost (YLL) attributable to smoking in NCDs in Mashhad, 2015–2016.

Hospital‑based data were utilized to calculate the economic burden of four selected diseases related to smoking. An epidemiological population‑attributable risk method was used to determine the smoking‑attributable fraction (SAF). Moreover, the study was conducted by data related to disease‑specific expenditures and patients’ information on cost and the number of mortality for estimating the YLL for each disease, population and life expectancy data, the prevalence of smoking, and the relative risk of smoking. Data analysis was performed with STATA software, version 12.

The total costs attributable to smoking for stroke, myocardial infarction, chronic obstructive pulmonary disease (COPD), and lung cancer were 94148, 151272, 1191396, and 574784 US Dollars, respectively (per 100000). In 2015, the YLL per deaths due to COPD were 4217 and 3522 among males and females, respectively. Furthermore, in 2016, the YLL per deaths due to the stroke in males and females were 8317 and 7563, respectively. In the same year, the highest proportion of years of potential life lost per 100000 smoking‑attributable deaths belonged to COPD.

The results of this study can be used to inform policy‑makers about smoking‑attributable diseases in Iran. To decrease the smoking‑attributable costs, which have resulted in the spread of NCDs, policy‑makers should adopt and implement effective policies regarding smoking prevention and control.

Background:

 The identification of elderly at risk of new functional disabilities in activities of daily living at admission to the hospital may facilitate referral for purposive interventions to prevent decline and institutionalization. This study was aimed at designing a risk prediction model for identifying the elderly at risk of admission in Iran’s hospitals.

 This is a cross‑sectional descriptive study conducted in 2017. In order to formulate and validate a prediction model, the study was done in two development and validation cohort study. Functional decline was defined as a decline of at least one point on the Katz ADL index at follow‑up compared with preadmission status.

Results:

In development cohort, the mean age was 71 years including 54% of men and 46% women, 22% of men and 17% of women experienced functional decline after 3 months. In the validation cohort, the mean age was 70 years, including 49% of men and 51% women, 19% of men and 15% of women, functional decline after 3 months was observed.

Conclusion:

 On the basis of the findings, aging at risk of hospital admission can be identified by easy designed model with four questions: (1) Is the patient’s age more than 85 years? (2) Does the patient’s mini mental status <22? (3) Does the patient need help for using general transporting? (4) Has the patient lost weight <5% over the past 6 months and body mass index <18.5? And also geriatrics experts can use the designed model as a predictive tool in order to improve the quality level of healthcare services to elderly as a vulnerable and high risk group. The important point of model is easy to use even for nonspecialists

Healthcare research is a systematic inquiry intended to generate robust evidence about important issues in the fields of medicine and healthcare. Qualitative research has ample possibilities within the arena of healthcare research. This article aims to inform healthcare professionals regarding qualitative research, its significance, and applicability in the field of healthcare. A wide variety of phenomena that cannot be explained using the quantitative approach can be explored and conveyed using a qualitative method. The major types of qualitative research designs are narrative research, phenomenological research, grounded theory research, ethnographic research, historical research, and case study research. The greatest strength of the qualitative research approach lies in the richness and depth of the healthcare exploration and description it makes. In health research, these methods are considered as the most humanistic and person-centered way of discovering and uncovering thoughts and actions of human beings.

Health promotion and preserving patients’ safety are the main purposes of care in health‑therapeutic systems. With regard to nursing profession, nursing students are exposed to medications errors (MEs) during clinical activities, which can be considered as a threat to patients’ safety. The study aimed to determine the prevalence of MEs among nursing students using a systematic and meta‑analysis approach.

8 studies (in 9 groups) in English and Persian from inception to March 2019, were collected. Searched was conducted in SID, MagIran, IranMedex, Google Scholar, Web of Science, PubMed and Scopus. The meta‑analysis method and the random effects model were used to analyze the data. In addition, the I2 statistic was used to examine heterogeneity among studies. The analyses were conducted using Stata, version 11.

Analysis of 8 studies (in 9 groups) with a total sample size of 688 showed that the overall MEs’ prevalence among nursing students was 39.68% (95% CI: 22.07‑57.29) and the prevalence of lack of reporting MEs was 48.60% (95%CI: 27.33‑69.86). There were no relationships between the prevalence of MEs and lack of reporting MEs in nursing students with the sample size and the mean age of students.

Considering the relatively high prevalence of MEs and lack of MEs reporting among nursing students and the importance of their effect on the level of patients’ safety, measures such as educations, monitoring by clinical trainers, and examining and eliminating the causes of MEs are essential.

Diabetes mellitus (DM) is an endocrine disorder characterized by hyperglycemia, polyuria, polydipsia, and glucosuria. γ‑aminobutyric acid (GABA) is an inhibitory neurotransmitter in the central nervous system (CNS) of humans and other mammals. GABA acts on two different receptors, which are GABA‑A and GABA‑B. Pancreatic β‑cells synthesize GABA from glutamic acid by glutamic acid decarboxylase (GAD).

The objective of this study was to explore the potential role of pancreatic GABA on glycemic indices in DM.

Evidence from experimental, preclinical, and clinical studies are evaluated for bidirectional relationships between pancreatic GABA and blood glucose disorders. A multiplicity of search strategies took on and assumed included electronic database searches of Medline and Pubmed using MeSH terms, keywords and title words during the search.

The pancreatic GABA signaling system has a role in the regulation of pancreatic hormone secretions, inhibition of immune response, improve β‑cells survival, and change α cell into β‑cell. Moreover, a GABA agonist improves the antidiabetic effects of metformin. In addition, benzodiazepine receptor agonists improve pancreatic β‑cell functions through GABA dependent pathway or through modulation of pancreatic adenosine and glucagon‑like peptide (GLP‑1).

Pancreatic GABA improves islet cell function, glucose homeostasis, and autoimmunity in DM. Orally administered GABA is safe for humans, and acts on peripheral GABA receptors and represents a new therapeutic modality for both T1DM and T2DM. Besides, GABA‑A receptor agonist like benzodiazepines improves pancreatic β‑cell function and insulin sensitivity through activation of GABA‑A receptors.