Diabetes Technology &amp Therapeutics (DIABETES TECHNOL THE)

Publisher: Mary Ann Liebert

Journal description

This new peer-reviewed quarterly journal covers new technology and new products for the treatment, monitoring, diagnosis, and prevention of diabetes and its complications. Technologies include noninvasive glucose monitoring, implantable continuous glucose sensors, novel routes of insulin administration, genetic engineering, the artificial pancreas, measures of longterm control, computer applications for case management, telemedicine, the internet, and new medications.

Current impact factor: 2.29

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 2.293
2012 Impact Factor 2.205
2011 Impact Factor 1.931
2010 Impact Factor 2.146
2009 Impact Factor 2.62
2008 Impact Factor 2.127

Impact factor over time

Impact factor
Year

Additional details

5-year impact 2.25
Cited half-life 3.80
Immediacy index 0.82
Eigenfactor 0.01
Article influence 0.60
Website Diabetes Technology & Therapeutics website
Other titles Diabetes technology & therapeutics (Online), Diabetes technology & therapeutics, Diabetes technology and therapeutics
ISSN 1557-8593
OCLC 43498340
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Mary Ann Liebert

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • On author's personal website
    • On institutional repository, pre-print server or research network after 12 months embargo
    • Publisher's version/PDF cannot be used
    • Set statement to accompany deposit (see policy)
    • Publisher copyright and source must be acknowledged
    • NIH authors will have their final paper, (post peer review, copy-editing and proof-reading) deposited in PubMed Central on their behalf
    • Must link to publisher version with DOI
  • Classification
    ​ green

Publications in this journal

  • Ashwini Mallad, Ling Hinshaw, Chiara Dalla Man, Claudio Cobelli, Rita Basu, Ravi Lingineni, Rickey E Carter, Yogish C Kudva, Ananda Basu
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    ABSTRACT: Understanding the effect size, variability, and underlying physiology of the dawn phenomenon is important for next-generation closed-loop control algorithms for type 1 diabetes (T1D). We used an iterative protocol design to study 16 subjects with T1D on individualized insulin pump therapy for two successive nights. Endogenous glucose production (EGP) rates at 3 a.m. and 7 a.m. were measured with [6,6-(2)H2]glucose as a single tracer, infused from midnight to 7 a.m. in all subjects. To explore possibility of tracer recycling due to prolonged [6,6-(2)H2]glucose infusion, which was highly probable after preplanned interim data analyses, we infused a second tracer, [6-(3)H]glucose, from 4 a.m. to 7 a.m. in the last seven subjects to measure EGP at 7 a.m. Cortisol concentrations increased during both nights, but changes in glucagon and insulin concentration were inconsistent. Although the plasma glucose concentrations rose from midnight to 7 a.m. during both nights, EGP measured with [6,6-(2)H2]glucose between 3 a.m. and 7 a.m. did not differ during Night 1 but fell in Night 2. However, EGP measured with [6-(3)H]glucose at 7 a.m. was higher than that measured with [6,6-(2)H2]glucose during both nights, thereby suggesting tracer recycling probably underestimating EGP calculated at 7 a.m. with [6,6-(2)H2]glucose. Likewise, EGP was higher at 7 a.m. with [6-(3)H]glucose than at 3 a.m. with [6,6-(2)H2]glucose during both nights. The data demonstrate a consistent overnight rise in glucose concentrations through increased EGP, mediated likely by rising cortisol concentrations. The observations with the dual tracer approach imply significant tracer recycling leading to underestimation of EGP measured by longer-duration tracer infusion.
    Diabetes Technology &amp Therapeutics 06/2015; DOI:10.1089/dia.2015.0011
  • Diabetes Technology &amp Therapeutics 06/2015; 17(6):370-372. DOI:10.1089/dia.2015.0155
  • Diabetes Technology &amp Therapeutics 06/2015; 17(6):367-369. DOI:10.1089/dia.2015.0148
  • Diabetes Technology &amp Therapeutics 05/2015; DOI:10.1089/dia.2015.0158
  • Diabetes Technology &amp Therapeutics 05/2015; DOI:10.1089/dia.2015.0169
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    ABSTRACT: Systems for self-monitoring of blood glucose (SMBG) are expected to be accurate enough to provide reliable measurement results. Especially in the low glycemic range, adequate therapeutic decisions based on reliable results can alleviate complications associated with hypoglycemia. The accuracy of four SMBG systems (system 1 was the ACCU-CHEK(®) Aviva [Roche Diagnostics GmbH, Mannheim, Germany], system 2 was the Contour(®) XT [Bayer Consumer Care AG, Basel, Switzerland], system 3 was the GlucoCheck XL [aktivmed GmbH, Augsberg, Germany], and system 4 was the GlucoMen(®) LX PLUS [A. Menarini Diagnostics S.r.l., Florence, Italy]) with three test-strip lots each was evaluated by calculating mean absolute relative differences (MARDs). Two datasets were evaluated: (1) 100 samples with blood glucose concentrations <70 mg/dL and (2) 100 samples distributed following International Organization for Standardization (ISO) standard 15197. Each sample was measured twice with each test-strip lot of each SMBG system. Comparison measurement results were obtained with a glucose oxidase method and a hexokinase method, both traceable according to ISO 17511. Analysis of variance of the MARD between the SMBG system and the comparison method was performed. MARD values ranged from 4.4% to 13.4% (<70 mg/dL) and 4.8% to 8.9% (ISO 15197-distributed) and differed significantly, with systems 1 and 2 showing lower MARDs than systems 3 and 4. MARD values deviated by up to 2.5% (corresponding to a relative deviation of approximately 40%) between the two comparison methods. The investigated SMBG systems showed a significant variation of accuracy (measured by MARD), especially with higher MARD values in the low glycemic range. The selected comparison method had an impact on the MARD and therefore on the apparent accuracy of the SMBG systems. Sufficient measurement accuracy in the low glycemic range is required to enable users to react adequately to hypoglycemia.
    Diabetes Technology &amp Therapeutics 05/2015; DOI:10.1089/dia.2015.0043
  • Diabetes Technology &amp Therapeutics 05/2015; DOI:10.1089/dia.2015.0164
  • Diabetes Technology &amp Therapeutics 05/2015; DOI:10.1089/dia.2015.0144
  • Diabetes Technology &amp Therapeutics 05/2015; DOI:10.1089/dia.2015.0156
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    ABSTRACT: The aim of this study was to assess the associations of six single nucleotide polymorphisms (SNPs) of three genes (DRD3, COMT, and SCL6A4) with type 2 diabetes mellitus (T2DM) in Southern Chinese. Five hundred ninety-five cases with T2DM and 725 healthy controls of Han origin were recruited from six hospitals in Guangdong Province, Southern China. Fasting serum concentrations of markers of interest (total cholesterol, triglyceride, plasma glucose, etc.) were measured in hospitals. SNP genotyping was performed using a custom-by-design 2-×48-Plex SNPscan™ kit (Genesky Biotechnologies Inc., Shanghai, China). Single-point SNP analysis, haplotype analysis, and SNP-SNP interactions were carried out. SNP rs4646312 in COMT achieved statistical significance in both allelic association and genotypic association and even after adjusting covariates (odds ratio [OR]=1.26; 95% confidence interval [CI], 1.04-1.53; P=0.021). Two haplotypes consisting of rs4646312 and rs4680 were also significantly associated with T2DM, of which C-G was a protective haplotype for T2DM (OR=0.83; 95% CI, 0.70-0.98; P=0.029), whereas T-A was a risk one (OR=1.23, 95% CI, 1.03-1.46; P=0.022). Interaction analysis identified a significant epistatic effect between rs4680 in COMT and rs2066713 in SCL6A4 after adjusting for covariates (OR=3.59, 95% CI, 1.72-7.48; P=0.001 for dominant-dominant model). However, only the interaction between rs4680 and rs2066713 was significant, and haplotype T-A showed a marginally increased risk after Bonferroni correction. The genetic polymorphisms in COMT and SCL6A4 confer significant effects in joint actions to T2DM in Southern Chinese.
    Diabetes Technology &amp Therapeutics 04/2015; DOI:10.1089/dia.2014.0344
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    ABSTRACT: Medical devices have transformed modern health care, and ongoing experimental medical technology trials (such as the artificial pancreas) have the potential to significantly improve the treatment of several chronic conditions, including diabetes mellitus. However, we suggest that, to date, the essential concept of cybersecurity has not been adequately addressed in this field. This article discusses several key issues of cybersecurity in medical devices and proposes some solutions. In addition, it outlines the current requirements and efforts of regulatory agencies to increase awareness of this topic and to improve cybersecurity.
    Diabetes Technology &amp Therapeutics 04/2015; DOI:10.1089/dia.2014.0328
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    ABSTRACT: Many different devices are available to patients to measure glucose levels, but there is no validated method to assess treatment satisfaction with glucose monitoring devices and its impact on quality of life and other patient-reported outcomes. To address this problem, we developed the Glucose Monitoring System Satisfaction Survey (GMSS). We describe the construction and validation of the GMSS and examine how key patient factors are associated with glucose device satisfaction. Items were developed from interviews with 15 adults with either type 1 diabetes (T1D) or type 2 diabetes (T2D) and 10 diabetes healthcare professionals, resulting in an initial pool of 42 items. Separate exploratory factor analyses (EFAs) were conducted with adults with T1D (n=254) and with insulin-using T2D (n=206). Construct validity was established with overall well-being (World Health Organization-5), diabetes distress (Diabetes Distress Scale), attitudes toward glucose monitoring (Self-Monitoring of Blood Glucose Obstacles scale), and the previously validated Blood Glucose Monitoring System Rating Questionnaire. Regression analyses examined associations between total scale satisfaction and demographics, diabetes status, and glucose monitor use. The two EFAs resulted in two 15-item scales, one for T1D and one for T2D, and yielded four coherent and meaningful factors in each sample: three factors with the same items in common for both samples (Emotional Burden, Behavioral Burden, and Openness) and a fourth factor unique to each sample (Trust for T1D, Worthwhileness for T2D). The final EFA accounted for 66.5% of the variance in the T1D sample and 67.0% in the T2D sample. Validity was established by significant correlations with criterion variables. The GMSS is a reliable, valid measure of glucose device satisfaction in its T1D form and in its insulin-using T2D form. It provides a comprehensive profile of sources of device satisfaction for use in clinical care and research.
    Diabetes Technology &amp Therapeutics 04/2015; DOI:10.1089/dia.2014.0417
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    ABSTRACT: Definitions for overweight and obesity are universally applied using body mass index (BMI), based on morbidity and mortality data derived from white populations. However, several studies have shown higher body fat, excess metabolic perturbations, and cardiovascular risk factors at lower value of BMI in Asian versus white populations. Definitive guidelines have been published to classify a BMI of ≥23 kg/m(2) and ≥25 kg/m(2) as overweight and obese, respectively, by the Indian Consensus Group (for Asian Indians residing in India) and a BMI of ≥23 kg/m(2) for screening for diabetes by the National Institute of Health and Care Excellence of the United Kingdom (for migrant south Asians) and, in an encouraging initiative recently (2015), by the American Diabetes Association (for all Asian ethnic groups in the United States). Overall, multiple studies, and now several guidelines, emphasize early intervention with diet and physical activity in Asian ethnic groups for prevention and management of obesity-related noncommunicable diseases. By application of these guidelines, an additional 10-15% of the population in India would be labeled as overweight/obese, and more South Asians/Asians will be diagnosed with diabetes in the United Kingdom and the United States. Additional health resources need to be allocated to deal with increasing numbers of Asians with obesity-related noncommunicable diseases, and research is needed to evolve cost-effective interventions. Finally, consensus based on data is needed so that the World Health Organization and other international agencies could take definitive steps for revision of classification of BMI for Asian populations globally.
    Diabetes Technology &amp Therapeutics 04/2015; DOI:10.1089/dia.2015.0007
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    ABSTRACT: Type 2 diabetes mellitus (T2DM) is a complex disease that is caused by an impairment in the secretion of β-cell insulin and by a peripheral resistance to insulin. Most patients suffering from T2DM and from obesity exhibit insulin resistance in the muscles, liver, and fat, resulting in a reduced response of these tissues to insulin. In healthy individuals, pancreatic islet β-cells secrete insulin to regulate the increase in blood glucose levels. Once these β-cells fail to function, T2DM develops. Despite the progress achieved in this field in recent years, the genetic causes for insulin resistance and for T2DM have not yet been fully discovered. The present study aims to characterize T2DM by comparing its gene expression with that of normal controls, as well as to identify biomarkers for early T2DM. Gene expression profiles were downloaded from the Gene Expression Omnibus, and differentially expressed genes (DEGs) were identified for type 2 diabetes. Furthermore, functional analyses were conducted for the gene ontology and for the pathway enrichment. In total, 781 DEGs were identified in the T2DM samples relative to healthy controls. These genes were found to be involved in several biological processes, including cell communication, cell proliferation, cell shape, and apoptosis. We constructed a protein-protein interaction (PPI) network, and the clusters in the PPI were analyzed by using ClusterONE. Six functional genes that may play important roles in the initiation of T2DM were identified within the network.
    Diabetes Technology &amp Therapeutics 04/2015; DOI:10.1089/dia.2014.0204
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    ABSTRACT: As continuous intraperitoneal insulin infusion (CIPII) results in a more physiologic action of insulin than subcutaneous (SC) insulin administration, we hypothesized that CIPII would result in less glycemic variability (GV) than SC insulin therapy among type 1 diabetes mellitus (T1DM) patients. Data from 5-day blind continuous glucose monitoring (CGM) measurements performed during a 26-week, prospective, observational case-control study were analyzed. The coefficient of variation (CV) was the primary measure of GV. In addition, the SD of the mean glucose level, mean of daily differences, and mean amplitude of glycemic excursions were calculated. In total, 176 patients (36% male; mean age, 49 [SD 13] years; median diabetes duration, 24 [interquartile range, 17, 35] years; glycated hemoglobin level, 63 [10] mmol/mmol), of which 37 used CIPII and 139 SC insulin therapy, were analyzed. CGM data were available for 169 patients at baseline (CIPII, n=35; SC, n=134) and for 164 patients at 26 weeks (CIPII, n=35; SC, n=129). After adjustment for baseline differences, the CV was 4.9% (95% confidence interval, 1.0, 8.8) lower with CIPII- compared with SC-treated patients, irrespective of the use of multiple daily injections or continuous SC insulin infusion. There were no differences in other indices of GV between groups. Despite higher blood glucose, the CV was slightly lower with CIPII compared with SC insulin therapy in T1DM patients, and other measures of GV were identical. Future studies are needed to confirm these findings and investigate whether this results in prevention of hypoglycemia and even perhaps (less) microvascular complications.
    Diabetes Technology &amp Therapeutics 04/2015; 17(6). DOI:10.1089/dia.2015.0001
  • Diabetes Technology &amp Therapeutics 04/2015; 17(5). DOI:10.1089/dia.2015.0055