Diabetes mellitus publication patterns, 1984-2005.
Ontology highlight
ABSTRACT:
SUBMITTER: Lewin HS
PROVIDER: S-EPMC2268230 | biostudies-literature | 2008 Apr
REPOSITORIES: biostudies-literature
Publications
Diabetes mellitus publication patterns, 1984-2005.
Journal of the Medical Library Association : JMLA 20080401 2
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Project description:IntroductionDiabetes Mellitus (DM) is a huge burden for human health. Recent studies show the close relationship between DM and T cells. We investigated the trend in DM and T cells research.MethodsUsing the Web of Science database, we searched the publications on DM and T cells in 1997-2016, and studied the source data using bibliometric methodology. Excel 2016, GraphPad Prism 5, and VOSviewer software were used to analyze the publication trend in DM and T cells research.ResultsWe found a total of 1077 publications with 38109 citations up to January 23, 2017. The highest contribution came from the United States, with 48.38% of the publications, 61.44% of the citations and the highest H-index (74). China had the 5th place for total publications, but ranked 11th both for citation frequency (604) and H-index (13). The inflection point of the global DM and T cells publications was in 2000. Journal of Immunology published the most related articles (164). Santamaria P. was the leading scholar in this field with the most publications (35). The keywords "regulatory T cell" and "autoimmune diabetes" were mentioned more than 300 times. Furthermore, type 2 (T2)DM, T cell immunoglobulin and mucin domain (TIM) and obesity are becoming popular research topics in this field.ConclusionThe quantity of publications on DM and T cells grew rapidly around year 2000, but has relatively decreased recently. The United States had the leading position in global research. There was a discrepancy between productivity and quality of publications from China. Latest progress is most likely first published by the Journal of Immunology. Santamaria P., Roep B.O. and Peakman M. were the pioneer scholars in this field. Most researchers have focused on "regulatory T cell" and "autoimmune diabetes" research. In future, T2DM, TIM and obesity may be the popular areas.
| S-EPMC5604989 | biostudies-literature
Project description:We compared the plasma miRNA expression profiles between healthy and GDM women by microarray analysis.Our study offers new insights into circulating biomarkers of GDM and thus provides a valuable resource for future investigations.
2017-04-22 | GSE98043 | GEO
Project description:Digital teaching, learning and assessment have been part of medical education and continuing education for decades. The objective of this review paper is to highlight developments and perspectives in these areas in the GMS Journal for Medical Education (GMS JME). In the spring of 2020, we conducted a systematic literature search of the Journal for Medical Education (JME) and analysed the articles with regard to different categories such as article type, digital tools used or mode of data collection. Of the 132 articles analysed, 78 were digital interventions (53 of which were exploratory-descriptive), 28 were project descriptions, 16 were surveys of needs or equipment and 10 were concept papers. About one-third of the studies and project reports each dealt with virtual patients or case-based learning, whereas no articles were published on trends such as serious games or virtual reality. Overall, our analysis shows that in many respects, the studies on digital teaching were more broadly based, especially between 2006 and 2010, after which this trend tended to decline again. Our analysis shows that publications in the JME consider some key aspects of digital teaching in medical education and continuing education, such as educational videos or virtual patients. The variability of information and methods of presentation advocate the use of guidelines to optimise the quality of scientific papers. Furthermore, clues for future research topics and experimental study designs are identified.
| S-EPMC9733476 | biostudies-literature
Project description:Six oral medication classes have been approved by the Food and Drug Administration for the treatment of type 2 diabetes. Although all of these agents effectively lower blood glucose, the evidence supporting their impact on other clinical events is variable. There also are substantial cost differences between agents. We aimed to evaluate temporal trends in the use of specific drugs for the initial management of type 2 diabetes and to estimate the economic consequences of non-recommended care.We studied a cohort of 254,973 patients, aged 18 to 100 years, who were newly initiated on oral hypoglycemic monotherapy between January 1, 2006, and December 31, 2008, by using prescription claims data from a large pharmacy benefit manager. Linear regression models were used to assess whether medication initiation patterns changed over time. Multivariate logistic regression models were constructed to identify independent predictors of receiving initial therapy with metformin. We then measured the economic consequences of prescribing patterns by drug class for both patients and the insurer.Over the course of the study period, the proportion of patients initially treated with metformin increased from 51% to 65%, whereas those receiving sulfonylureas decreased from 26% to 18% (P<.001 for both). There was a significant decline in the use of thiazolidinediones (20.1%-8.3%, P<.001) and an increase in prescriptions for dipeptidyl peptidase-4 inhibitors (0.4%-7.3%, P<.001). Younger patients, women, and patients receiving drug benefits through Medicare were least likely to initiate treatment with metformin. Combined patient and insurer spending for patients who were initiated on alpha-glucosidase inhibitors, thiazolidinediones, meglitinides, or dipeptidyl peptidase-4 inhibitors was $677 over a 6-month period compared with $116 and $118 for patients initiated on metformin or a sulfonylurea, respectively, a cost difference of approximately $1120 annually per patient.Approximately 35% of patients initiating an oral hypoglycemic drug did not receive recommended initial therapy with metformin. These practice patterns also have substantial implications for health care spending.
| S-EPMC4347833 | biostudies-other
Project description:BackgroundPrevious studies observed inverse associations of adherence to the alternate Mediterranean (aMED), Dietary Approaches to Stop Hypertension (DASH), and alternate Healthy Eating Index (aHEI) dietary patterns with risk of type 2 diabetes; however, their associations with gestational diabetes mellitus (GDM) risk are unknown.ObjectiveThis study aimed to assess usual prepregnancy adherence to well-known dietary patterns and GDM risk.DesignOur study included 21,376 singleton live births reported from 15,254 participants of the Nurses' Health Study II cohort between 1991 and 2001. Pregnancies were free of prepregnancy chronic disease or previous GDM. Prepregnancy dietary pattern adherence scores were computed based on participants' usual intake of the patterns' components, assessed with a validated food-frequency questionnaire. Multivariable logistic regressions with generalized estimating equations were used to estimate the RRs and 95% CIs.ResultsIncident first-time GDM was reported in 872 pregnancies. All 3 scores were inversely associated with GDM risk after adjustment for several covariables. In a comparison of the multivariable risk of GDM in participants in the fourth and first quartiles of dietary pattern adherence scores, aMED was associated with a 24% lower risk (RR: 0.76; 95% CI: 0.60, 0.95; P-trend = 0.004), DASH with a 34% lower risk (RR: 0.66; 95% CI: 0.53, 0.82; P-trend = 0.0005), and aHEI with a 46% lower risk (RR: 0.54; 95% CI: 0.43, 0.68; P-trend < 0.0001).ConclusionPrepregnancy adherence to healthful dietary patterns is significantly associated with a lower risk of GDM.
| S-EPMC3396443 | biostudies-literature
Project description:Maternal dietary patterns before and during pregnancy play important roles in the development of gestational diabetes mellitus (GDM). We aimed to identify dietary patterns during pregnancy that are associated with GDM risk in pregnant U.S. women. From a 24 h dietary recall of 253 pregnant women (16-41 years) included in the National Health and Nutrition Examination Survey (NHANES) 2003-2012, food items were aggregated into 28 food groups based on Food Patterns Equivalents Database. Three dietary patterns were identified by reduced rank regression with responses including prepregnancy body mass index (BMI), dietary fiber, and ratio of poly- and monounsaturated fatty acids to saturated fatty acid: "high refined grains, fats, oils and fruit juice", "high nuts, seeds, fat and soybean; low milk and cheese", and "high added sugar and organ meats; low fruits, vegetables and seafood". GDM was diagnosed using fasting plasma glucose levels ?5.1 mmol/L for gestation <24 weeks. Multivariable logistic regression models were used to estimate adjusted odds ratio (AOR) and 95% confidence intervals (CIs) for GDM, after controlling for maternal age, race/ethnicity, education, family poverty income ratio, marital status, prepregnancy BMI, gestational weight gain, energy intake, physical activity, and log-transformed C-reactive protein (CRP). All statistical analyses accounted for the appropriate survey design and sample weights of the NHANES. Of 249 pregnant women, 34 pregnant women (14%) had GDM. Multivariable AOR (95% CIs) of GDM for comparisons between the highest vs. lowest tertiles were 4.9 (1.4-17.0) for "high refined grains, fats, oils and fruit juice" pattern, 7.5 (1.8-32.3) for "high nuts, seeds, fat and soybean; low milk and cheese" pattern, and 22.3 (3.9-127.4) for "high added sugar and organ meats; low fruits, vegetables and seafood" pattern after controlling for maternal sociodemographic variables, prepregnancy BMI, gestational weight gain, energy intake and log-transformed CRP. These findings suggest that dietary patterns during pregnancy are associated with risk of GDM after controlling for potential confounders. The observed connection between a high consumption of refined grains, fat, added sugars and low intake of fruits and vegetables during pregnancy with higher odds for GDM, are consistent with general health benefits of healthy diets, but warrants further research to understand underlying pathophysiology of GDM associated with dietary behaviors during pregnancy.
| S-EPMC4663600 | biostudies-literature
Project description:BackgroundReduced rank regression (RRR) has been used to derive dietary pattern scores that predict linear combinations of disease biomarkers. The generalizability of these patterns to independent populations remains unknown.ObjectiveThe goal was to examine the generalizability of dietary patterns from the following prior studies using RRR to predict type 2 diabetes mellitus (T2DM): the Nurses' Health Study (NHS), European Prospective Investigation into Cancer and Nutrition Germany (EPIC), and Whitehall II Study (WS).DesignThe relative weights of food groups of each dietary pattern were used to generate each dietary pattern score in the Framingham Offspring Study (n = 2879). Each of the external scores (confirmatory scores) was examined to determine whether it could predict incident T2DM during 7 y of follow-up as well as scores developed internally in the Framingham Offspring Study using a Cox-proportional hazard model adjusted for T2DM risk factors.ResultsIntakes of meat products, refined grains, and soft drinks (caloric and noncaloric) were found to be common predictive components of all confirmatory scores, but fried foods, eggs, and alcoholic beverages were predictive in some, but not in all, confirmatory scores. On the basis of a continuous increase in the score by 1 SD, the NHS-based confirmatory score predicted T2DM risk (hazard ratio: 1.44; 95% CI: 1.25, 1.66). However, T2DM risk was only weakly predicted by the EPIC-based score (hazard ratio: 1.14; 95% CI: 0.99, 1.32) and the WS-based score (hazard ratio: 1.16; 95% CI: 1.00, 1.35).ConclusionsThe study suggested that dietary patterns that predict T2DM risk in different populations may not be generalizable to different populations. Additional dietary pattern studies should be conducted with regard to generalizability.
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Project description:Obesity is associated with an increased risk of insulin resistance (IR) and type 2 diabetes mellitus (T2DM) which is a multi-factorial disease associated with a dysregulated metabolism and can be prevented in pre-diabetic individuals with impaired glucose tolerance. A metabolomic approach emphasizing metabolic pathways is critical to our understanding of this heterogeneous disease. This study aimed to characterize the serum metabolomic fingerprint and multi-metabolite signatures associated with IR and T2DM. Here, we have used untargeted high-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) to identify candidate biomarkers of IR and T2DM in sera from 30 adults of normal weight, 26 obese adults, and 16 adults newly diagnosed with T2DM. Among the 3633 peak pairs detected, 62% were either identified or matched. A group of 78 metabolites were up-regulated and 111 metabolites were down-regulated comparing obese to lean group while 459 metabolites were up-regulated and 166 metabolites were down-regulated comparing T2DM to obese groups. Several metabolites were identified as IR potential biomarkers, including amino acids (Asn, Gln, and His), methionine (Met) sulfoxide, 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate, serotonin, L-2-amino-3-oxobutanoic acid, and 4,6-dihydroxyquinoline. T2DM was associated with dysregulation of 42 metabolites, including amino acids, amino acids metabolites, and dipeptides. In conclusion, these pilot data have identified IR and T2DM metabolomics panels as potential novel biomarkers of IR and identified metabolites associated with T2DM, with possible diagnostic and therapeutic applications. Further studies to confirm these associations in prospective cohorts are warranted.
| S-EPMC7768025 | biostudies-literature
Project description:The purpose of this study is to describe lipid-lowering therapy (LLT) prescriptions and low-density lipoprotein cholesterol (LDL-C) monitoring in patients with diabetes mellitus (DM) with or without concomitant cardiovascular disease (CVD). Olmsted County, Minnesota residents with a first-ever diagnosis of DM or CVD (ischemic stroke/transient ischemic attack, myocardial infarction, unstable angina pectoris, or revascularization procedure) between 2005 and 2012 were classified as having DM only, CVD only, or CVD + DM. All LLT prescriptions and LDL-C measurements were obtained for 2 years after diagnosis. A total of 4,186, 2,368, and 724 patients had DM, CVD, and CVD + DM, respectively. Rates of LDL-C measurement were 1.31, 1.66, and 1.88 per person-year and 14%, 32%, and 42% of LDL-C measurements were <70 mg/dl in those with DM, CVD, and CVD + DM. Within 3 months after diagnosis, 47%, 71%, and 78% of patients with DM, CVD, and CVD + DM were prescribed LLT. Most prescriptions were for moderate-intensity statins. Under one-fifth of patients with CVD and CVD + DM were prescribed high-intensity statins. Predictors of high-intensity statin prescriptions included male sex, having CVD or CVD + DM, increasing LDL-C, and LDL-C measured more recently (2012 to 2014 vs before 2012). In conclusion, a large proportion of patients at high CVD risk are not adequately treated with LLT. Despite often being considered a risk equivalent, patients with DM have substantially lower rates of LLT prescriptions and lesser controlled LDL-C than those with CVD or CVD + DM.
| S-EPMC6744976 | biostudies-literature
Project description:BackgroundLimited studies have explored the difference of fatty acid profile between women with and without gestational diabetes mellitus (GDM), and the results were inconsistent. Individual fatty acids tend to be interrelated because of the shared food sources and metabolic pathways. Thus, whether fatty acid patters during pregnancy were related to GDM odds needs further exploration.ObjectiveTo identify plasma fatty acid patters during pregnancy and their associations with odds of GDM.MethodsA hospital-based case-control study including 217 GDM cases and 217 matched controls was carried out in urban Wuhan, China from August 2012 to April 2015. All the participants were enrolled at the time of GDM screening and provided fasting blood samples with informed consent. We measured plasma concentrations of fatty acids by gas chromatography-mass spectrometry, and derived potential fatty acid patterns (FAPs) through principal components analysis. Conditional logistic regression and restricted cubic spline model were used to evaluate the associations between individual fatty acids or FAPs and odds of GDM.ResultsTwenty individual fatty acids with relative concentrations ≥0.05% were included in the analyses. Compared with control group, GDM group had significantly higher concentrations of total fatty acids, 24:1n-9, and relatively lower levels of 14:0, 15:0, 17:0, 18:0, 24:0, 16:1n-7, 20:1n-9,18:3n-6, 20:2n-6, 18:3n-3, 20:3n-3, 22:5n-3. Two novel patterns of fatty acids were identified to be associated with lower odds of GDM: (1) relatively higher odd-chain fatty acids, 14:0, 18:0, 18:3n-3, 20:2n-6, 20:3n-6 and lower 24:1n-9 and 18:2n-6 [adjusted odds ratio (OR) (95% confidence interval) (CI) for quartiles 4 vs. 1: 0.42 (0.23-0.76), P-trend = 0.002], (2) relatively higher n-3 polyunsaturated fatty acids, 24:0, 18:3n-6 and lower 16:0 and 20:4n-6 [adjusted OR (95% CI) for quartiles 4 vs. 1: 0.48 (0.26-0.90), P-trend = 0.018].ConclusionOur findings suggested that two novel FAPs were inversely associated with GDM odds. The combination of circulating fatty acids could be a more significant marker of GDM development than individual fatty acids or their subgroups.
| S-EPMC9121815 | biostudies-literature