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1.
Diabet Med. 2019 Feb 7. doi: 10.1111/dme.13929. [Epub ahead of print]

Text-message responsiveness to blood glucose monitoring reminders is associated with HbA1c benefit in teenagers with Type 1 diabetes.

Author information

1
Section on Clinical, Behavioral and Outcomes Research, Pediatric, Adolescent and Young Adult Section, Joslin Diabetes Center, Harvard Medical School, Boston, MA.
2
Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA.

Abstract

AIMS:

To evaluate an 18-month text-messaging intervention in teenagers with Type 1 diabetes and to assess factors associated with text responsiveness and glycaemic benefit.

METHODS:

Teenagers with diabetes (N=147), aged 13-17 years, received two-way text reminders at self-selected times to check blood glucose levels and reply with blood glucose results.

RESULTS:

At baseline, the participants (48% boys, 78% white, 63% pump-treated) had a mean ± sd age of 14.9 ± 1.3 years, diabetes duration of 7.1 ± 3.9 years and HbA1c concentration of 69±12 mmol/mol (8.5±1.1%). The mean proportion of days with ≥1 blood glucose response declined over time (0-6 months, 60±26% of days, 7-12 months, 53±31% of days, 13-18 months, 43±33% of days). Over 18 months, 49% responded with ≥1 blood glucose result on ≥50% of days (high responders). Regression analysis controlling for baseline HbA1c revealed no significant change in HbA1c from baseline to 18 months in high responders (P=0.54) compared with a significant HbA1c increase in low responders (+0.3%, P=0.01). In participants with baseline HbA1c ≥64 mmol/mol (≥8%), high responders were 2.5 times more likely than low responders to have a clinically significant [≥5.5 mmol/mol (≥0.5%)] HbA1c decrease over 18 months (P<0.05). In participants with baseline HbA1c <64 mmol/mol(<8%), high responders were 5.7 times more likely than low responders to have an 18-month HbA1c <58 mmol/mol (<7.5%; P<0.05).

CONCLUSIONS:

Teenagers with Type 1 diabetes who responded to text reminders on ≥50% of days over 18 months experienced clinically significant glycaemic benefit. There remains a need to tailor interventions to maintain teenager engagement and optimize improvements. This article is protected by copyright. All rights reserved.

PMID:
30734361
DOI:
10.1111/dme.13929
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2.
Diabet Med. 2019 Feb 7. doi: 10.1111/dme.13927. [Epub ahead of print]

Reducing risk of Type 2 diabetes in HIV: a mixed-methods investigation of the STOP-Diabetes diet and physical activity intervention.

Author information

1
King's College, London.
2
Guy's and St, Thomas' Hospital NHS Foundation Trust.
3
University College, London, UK.

Abstract

AIM:

To conduct a mixed-methods feasibility study of the effectiveness and acceptability of an individualized diet and physical activity intervention designed to reduce the risk of Type 2 diabetes experienced by people living with HIV.

METHODS:

Participants with impaired fasting glucose and HIV were invited to take part in a 6-month diet and physical activity intervention. Individualized advice to achieve 10 lifestyle goals was delivered monthly. Diabetes risk was assessed pre- and post-intervention by measurement of the glucose and insulin response to a 3-h meal tolerance test. Six-month change was analysed using paired t-tests. Research interviews exploring the acceptability of the intervention and factors influencing behaviour change were conducted with those who participated in the intervention, and those who declined participation.

RESULTS:

The intervention (n=28) significantly reduced the following: glucose and insulin, both fasting and postprandial incremental area under the curve (glucose 7.9% and 17.6%; insulin 22.7% and 31.4%, respectively); weight (4.6%); waist circumference (6.2%); systolic blood pressure (7.4%); and triglycerides (36.7%). Interview data demonstrated the acceptability of the intervention. However, participants expressed concern that deliberate weight loss might lead to disclosure of HIV status or association with AIDS-related illness. The belief that antiretroviral medications drove diabetes risk was associated with declining study participation or achieving fewer goals.

CONCLUSIONS:

We have demonstrated the beneficial effects of a lifestyle intervention in mitigating the increased risk of Type 2 diabetes associated with HIV. Future interventions should be designed to further reduce the unique barriers that prevent successful outcomes in this cohort. This article is protected by copyright. All rights reserved.

PMID:
30734352
DOI:
10.1111/dme.13927
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3.
Diabet Med. 2019 Feb 6. doi: 10.1111/dme.13928. [Epub ahead of print]

History of gestational diabetes mellitus and postpartum maternal retinal microvascular structure and function.

Author information

1
College of Medicine, Nursing& Health Sciences, National University of Ireland (Galway), Galway, Ireland.
2
Health Services Systems Research Programme, Duke-NUS Medical School, Singapore.
3
Division of O&G, KK Women's and Children's Hospital, Singapore.
4
Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA.
5
Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore.
6
Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
7
Centre for Clinician-Scientist Development, Singapore.
8
O&G ACP, Duke-NUS Medical School, Singapore.

Abstract

Gestational diabetes mellitus (GDM) is one of the most common complications in pregnancy. The presence of GDM identifies women with increased risks of long-term health problems after delivery, including Type 2 diabetes and cardiovascular diseases (CVD). Because retinal microcirculation may mirror systemic microcirculation, exploring microvascular changes after delivery among women with or without a history of GDM might be key to better understanding such pathophysiological mechanisms. This article is protected by copyright. All rights reserved.

PMID:
30729567
DOI:
10.1111/dme.13928
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4.
Diabet Med. 2019 Feb 5. doi: 10.1111/dme.13926. [Epub ahead of print]

Women's views on lifestyle changes to reduce the risk of developing Type 2 diabetes after gestational diabetes: a systematic review, qualitative synthesis and recommendations for practice.

Author information

1
Primary Care Unit, Department of Public Health and Primary Care.
2
MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.

Abstract

AIMS:

To synthesize systematically the literature that focuses on the views of women with a history of gestational diabetes on reducing their risk of developing diabetes postpartum through lifestyle and behaviour changes.

METHODS:

We identified qualitative studies that examined the views of women with a history of gestational diabetes towards healthy eating and physical activity, Type 2 diabetes risk management or their experience of a diabetes prevention programme, and conducted a thematic synthesis to develop descriptive and then analytical themes. We evaluated the quality of each study and the confidence that we had in its findings using the Critical Appraisal Skills Programmes criteria and the Grading of Recommendations Assessment, Development and Evaluation-Confidence in Evidence from Reviews of Qualitative Research.

RESULTS:

We included 21 articles after screening 23 160 citations and 129 full texts. We identified six themes of interacting influences on postpartum behaviour: role as mother and priorities; social support; demands of life; personal preferences and experiences; risk perception and information; and finances and resources (plus preferred format of interventions). These factors inhibited many women from addressing their own health, while they motivated others to persevere. We also developed 20 recommendations, most with high or moderate confidence, for effective promotion of healthy lifestyles in this population.

CONCLUSIONS:

Many factors hinder healthy lifestyles after gestational diabetes, yet how women interpret them can motivate or prevent changes that reduce diabetes risk. As our recommendations emphasize, women's experiences and needs should be considered when designing strategies to promote healthier lifestyles in this population. This article is protected by copyright. All rights reserved.

PMID:
30723968
DOI:
10.1111/dme.13926
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5.
Diabet Med. 2019 Feb 5. doi: 10.1111/dme.13925. [Epub ahead of print]

Relationship between fasting plasma glucose and incidence of diabetes in children and adolescents.

Author information

1
Department of Medical Imaging, E-Da Hospital, Kaohsiung.
2
School of Medicine for International Students, I-Shou University, Kaohsiung.
3
Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei.
4
Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei.
5
Institute of Environmental Health China, Medical University College of Public Health, Taichung.
6
National Research Institute of Chinese Medicine, Ministry of Health and Welfare.
7
Institute of Hospital and Health Care Administration, National Yang-Ming University.
8
Chia Nan University of Pharmacy and Science, Tainan.
9
Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan, ROC.

Abstract

AIM:

To investigate the appropriate fasting plasma glucose threshold by which to define prediabetes in children and adolescents, based on its ability to predict incident paediatric diabetes.

METHODS:

In a nationwide survey of diabetes and renal disease conducted between 1992 and 2000 in all school-aged children in Taiwan, those with abnormal results in repeated urine tests received further physical examination and blood tests. Students who had blood tests for at least two time points were selected for the present study (N = 12 119). The incidence of paediatric diabetes, adjusted hazard ratio and predictive power of fasting plasma glucose were analysed.

RESULTS:

The incidence of paediatric diabetes increased with increasing fasting plasma glucose levels. Groups with fasting plasma glucose >5.6 mmol/l had a higher adjusted hazard ratio. The adjusted hazard ratio of incident diabetes for participants with higher fasting plasma glucose rose continuously when using a higher threshold for fasting plasma glucose. The area under the receiver-operating characteristic curve for fasting plasma glucose was 0.628 for predicting paediatric diabetes. The association between fasting plasma glucose and incident paediatric diabetes and the area under the receiver-operating characteristic curve were similar in boys and girls and were higher in the age group 12-18 years. According to receiver-operating characteristic curve analysis, the optimal thresholds, sensitivity and specificity were 4.75 mmol/l, 65% and 51%, respectively, for those aged 6-11 years and 5.19 mmol/l, 60% and 73%, respectively, for those aged 12-18 years.

CONCLUSION:

Fasting plasma glucose is associated with the incidence of paediatric diabetes. The results of the present study can be used as reference data to suggest a cut-off value to define paediatric prediabetes. This article is protected by copyright. All rights reserved.

PMID:
30723961
DOI:
10.1111/dme.13925
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6.
Diabet Med. 2019 Feb 2. doi: 10.1111/dme.13923. [Epub ahead of print]

An Irish National Diabetes in Pregnancy Audit: aiming for best outcomes for women with diabetes.

Author information

1
University Hospital Galway, Galway.
2
South Tipperary General Hospital, Clonmel.
3
Mayo University Hospital, Castlebar.
4
Portiuncla University Hospital, Ballinasloe.
5
St Luke's General Hospital, Kilkenny.
6
Cork University Hospital, Cork.
7
Bon Secours Hospital, Cork.
8
Wexford General Hospital, Wexford.
9
Letterkenny University Hospital, Letterkenny.
10
University Hospital Kerry, Tralee.
11
Midland Regional Hospital, Mullingar.
12
Coombe Women and Infants University Hospital, Dublin.
13
Sligo University Hospital, Sligo.
14
South Infirmary, Victoria University Hospital, Cork.
15
University Hospital Waterford, Waterford, Republic of Ireland.

Abstract

AIMS:

The purpose of this study was to identify the number of pregnancies affected by pre-gestational diabetes in the Republic of Ireland; to report on pregnancy outcomes and to identify areas for improvement in care delivery and clinical outcomes.

METHODS:

Healthcare professionals caring for women with pre-gestational diabetes during pregnancy were invited to participate in this retrospective study. Data pertaining to 185 pregnancies in women attending 15 antenatal centres nationally were collected and analysed. Included pregnancies had an estimated date of delivery between 1 January and 31 December 2015.

RESULTS:

The cohort consisted of 122 (65.9%) women with Type 1 diabetes and 56 (30.3%) women with Type 2 diabetes. The remaining 7 (3.8%) pregnancies were to women with maturity-onset diabetes of the young (MODY) (n = 6) and post-transplant diabetes (n = 1). Overall women were poorly prepared for pregnancy and lapses in specific areas of service delivery including pre-pregnancy care and retinal screening were identified. The majority of pregnancies 156 (84.3%) resulted in a live birth. A total of 103 (65.5%) women had a caesarean delivery and 58 (36.9%) infants were large for gestational age.

CONCLUSIONS:

This audit identifies clear areas for improvement in delivery of care for women with diabetes in the Republic of Ireland before and during pregnancy. This article is protected by copyright. All rights reserved.

PMID:
30710451
DOI:
10.1111/dme.13923
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7.
Diabet Med. 2019 Feb 2. doi: 10.1111/dme.13924. [Epub ahead of print]

A modelling study of the budget impact of improved glycaemic control in adults with Type 1 diabetes in the UK.

Author information

1
King's College London School of Life Course Sciences, London, UK.
2
Medtronic International Trading, Tolochenaz, Switzerland.
3
Medtronic UK, Watford, UK.

Abstract

AIMS:

To develop a novel interactive budget impact model that assesses affordability of diabetes treatments in specific populations, and to test the model in a hypothetical scenario by estimating cost savings resulting from reduction in HbA1c from ≥69 mmol/mol (8.5%) to a target of 53 mmol/mol (7.0%) in adults with Type 1 diabetes in the UK.

METHODS:

A dynamic, interactive model was created using the projected incidence and progression over a 5-year horizon of diabetes-related complications (micro- and macrovascular disease, severe hypoglycaemia and diabetic ketoacidosis) for different HbA1c levels, with flexible input of population size, complications and therapy costs, HbA1c distribution and other variables. The model took a National Health Service and societal perspective.

RESULTS:

The model was developed, and in the proposed hypothetical situation, reductions in complications and expected costs evaluated. Achievement of target HbA1c in individuals with HbA1c ≥69 mmol/mol (8.5%) would reduce expected chronic complications from 6.8 to 1.2 events per 100 person-years, and diabetic ketoacidosis from 14.5 to 1.0 events per 100 person-years. Potential cumulative direct cost savings achievable in the modelled population were estimated at £687 m over 5 years (£5,585/person), with total (direct and indirect) savings of £1,034 m (£8,400/person).

CONCLUSIONS:

Implementation of strategies aimed at achieving target glucose levels in people with Type 1 diabetes in the UK has the potential to drive a significant reduction in complication costs. This estimate may provide insights into the potential for investment in achieving savings through improved diabetes care in the UK. This article is protected by copyright. All rights reserved.

PMID:
30710449
DOI:
10.1111/dme.13924
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8.
Diabet Med. 2019 Feb 1. doi: 10.1111/dme.13920. [Epub ahead of print]

Tissue biopsy in the diagnosis of chronic tuberculous wounds in diabetes mellitus.

Author information

1
Department of Endocrinology, Xinqiao Hospital, Army Medical University, Chongqing, China.

Abstract

A 70-year-old man with Type 2 diabetes mellitus and a history of tuberculosis sought treatment for a dark red mass on his right abdomen of 7 months' duration. A chest X-ray showed increased texture in both lungs but no parenchymal lesions. After informed consent had been obtained, a biopsy of the hypochondriac mass was taken, which revealed intradermal pyogenic granulomatous inflammation; acid-fast staining revealed a few acid-fast bacilli. Thus, the diagnosis of Mycobacterium tuberculosis infection of the wound was considered conclusive. This article is protected by copyright. All rights reserved.

PMID:
30706577
DOI:
10.1111/dme.13920
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9.
Diabet Med. 2019 Feb 1. doi: 10.1111/dme.13921. [Epub ahead of print]

Accumulation of advanced glycation end products in the skin is accelerated in relation to insulin resistance in people with Type 1 diabetes mellitus.

Author information

1
Department of Internal Medicine and Diabetology, Poznan University of Medical Sciences, Poznan, Poland.

Abstract

AIM:

To evaluate the association between skin advanced glycation end products and insulin resistance in Type 1 diabetes.

METHODS:

The study group consisted of 476 people with Type 1 diabetes (247 men) with a median (interquartile range) age of 42 (33-53) years, disease duration of 24 (19-32) years and HbA1c concentration of 63 (55-74) mmol/mol [7.9 (7.2-8.9)%]. Insulin resistance was assessed according to estimated glucose disposal rate. Advanced glycation product accumulation in the skin was measured by autofluorescence using an AGE Reader. The group was divided into three subgroups based on estimated glucose disposal rate tertiles (<5.5, 5.5-9.5 and >9.5 mg/kg/min, respectively). The higher the estimated glucose disposal rate, the lower the insulin resistance.

RESULTS:

Skin autofluoresence level decreased with increasing estimated glucose disposal rate; comparing people below the lower tertile, with those between the first and third tertiles, and with those above the third tertile, the median autofluoresences were, respectively: 2.5 (2.2-2.9) vs 2.3 (2.0-2.7) vs 2.1 (1.9-2.5) AU (P<0.0001). A negative correlation was observed between skin autofluorescence and estimated glucose disposal rate (Spearman's correlation coefficient=-0.31, P <0.001). Multiple logistic regression showed a significant, two-way association of insulin resistance with skin autofluorescence.

CONCLUSION:

The results of this study offer strong evidence for a two-way relationship between insulin resistance and advanced glycation product accumulation in the skin in people with Type 1 diabetes.

PMID:
30706538
DOI:
10.1111/dme.13921
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10.
Diabet Med. 2019 Feb 1. doi: 10.1111/dme.13918. [Epub ahead of print]

A pilot study of an integrated mental health, social and medical model for diabetes care in an inner-city setting: Three Dimensions for Diabetes (3DFD).

Author information

1
Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neurosciences, King's College London.
2
Diabetes Centre, King's College Hospital NHS Foundation Trust, London, UK.

Abstract

AIMS:

We examined the effectiveness of a service innovation, Three Dimensions for Diabetes (3DFD), that consisted of a referral to an integrated mental health, social care and diabetes treatment model, compared with usual care in improving biomedical and health economic outcomes.

METHODS:

Using a non-randomized control design, the 3DFD model was offered in two inner-city boroughs in London, UK, where diabetes health professionals could refer adult residents with diabetes, suboptimal glycaemic control [HbA1c ≥ 75 mmol/mol (≥ 9.0%)] and mental health and/or social problems. In the usual care group, there was no referral pathway and anonymized data on individuals with HbA1c ≥ 75 mmol/mol (≥ 9.0%) were collected from primary care records. Change in HbA1c from baseline to 12 months was the primary outcome, and change in healthcare costs and biomedical variables were secondary outcomes.

RESULTS:

3DFD participants had worse glycaemic control and higher healthcare costs than control participants at baseline. 3DFD participants had greater improvement in glycaemic control compared with control participants [-14 mmol/mol (-1.3%) vs. -6 mmol/mol (-0.6%) respectively, P < 0.001], adjusted for confounding. Total follow-up healthcare costs remained higher in the 3DFD group compared with the control group (mean difference £1715, 95% confidence intervals 591 to 2811), adjusted for confounding. The incremental cost-effectiveness ratio was £398 per mmol/mol unit decrease in HbA1c , indicating the 3DFD intervention was more effective and costed more than usual care.

CONCLUSIONS:

A biomedical, psychological and social criteria-based referral system for identifying and managing high-cost and high-risk individuals with poor glycaemic control can lead to improved health in all three dimensions. This article is protected by copyright. All rights reserved.

PMID:
30706535
DOI:
10.1111/dme.13918
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11.
Diabet Med. 2019 Feb 1. doi: 10.1111/dme.13919. [Epub ahead of print]

Challenges in the management of people with diabetes and cancer.

Author information

1
Department of Diabetes and Metabolism, Barts and the London School of Medicine and Dentistry, London, UK.

Abstract

Although micro- and macrovascular complications of diabetes are the most important cause of mortality and morbidity in people with diabetes, it is increasingly recognized that diabetes increases the risk of developing cancer. Diabetes and cancer commonly co-exist, and outcomes in people with both conditions are poorer than in those who have cancer but no diabetes. There is no randomized trial evidence that treating hyperglycaemia in people with cancer improves outcomes, but therapeutic nihilism should be avoided, and a personalized approach to managing hyperglycaemia in people with cancer is needed. This review aims to outline the link between diabetes therapies and cancer, and discuss the reasons why glucose should be actively managed people with both. In addition, we discuss clinical challenges in the management of hyperglycaemia in cancer, specifically in relation to glucocorticoids, enteral feeding and end-of-life care.

PMID:
30706527
DOI:
10.1111/dme.13919
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12.
Diabetes. 2019 Feb 6. pii: db180912. doi: 10.2337/db18-0912. [Epub ahead of print]

Monosodium Urate Contributes to Retinal Inflammation and Progression of Diabetic Retinopathy.

Author information

1
Department of Ophthalmology, Medical College of Georgia, Augusta, University, Augusta, GA 30912.
2
IRCCS Ospedale Pediatrico "Bambin Gesu'" - Rome - Italy.
3
Department of Biochemistry and Molecular Biology, Medical College of Georgia, Augusta University, Augusta, GA 30912.
4
Department of Experimental Medicine and Pathology, University of Rome "LaSapienza", Rome, Italy.
5
IRCCS Fondazione GB Bietti, Rome, Italy.
6
UOC Vitreoretina Ospedale San Carlo di Nancy, Rome, Italy.
7
Department of Oral Biology, Dental College of Georgia, Augusta, University, Augusta, GA 30912.
8
Department of Oncology and Molecular Medicine Istituto Superiore di Sanita' - Rome, Italy.
9
Department of Ophthalmology, Medical College of Georgia, Augusta, University, Augusta, GA 30912 mbartoli@augusta.edu.

Abstract

We have investigated the contributing role of monosodium urate (MSU) to the pathological processes associated with the induction of diabetic retinopathy (DR). In human postmortem retinas and vitreous from donors with DR, we have found a significant increase in MSU levels which correlated with the presence of inflammatory markers and enhanced expression of xanthine oxidase. Same elevation in MSU levels was also detected in serum and vitreous of streptozotocin-induced diabetic rats (STZ-rats) analyzed at 8 weeks of hyperglycemia. Furthermore, treatments of STZ-rats with the hypouricemic drugs allopurinol (50 mg/kg) and benzbromarone (10 mg/kg) given every other day resulted in a significant decrease of retinal and plasma levels of inflammatory cytokines and adhesion factors, a marked reduction of hyperglycemia-induced retinal leukostasis, and restoration of retinal blood barrier function. These results were associated with effects of the hypouricemic drugs on down-regulating diabetes-induced levels of oxidative stress markers as well as expression of components of the NLRP3 inflammasome such as NLRP3, TLR4 and IL-1β. The outcomes of these studies support a contributing role of MSU in diabetes-induced retinal inflammation and suggest that asymptomatic hyperuricemia should be considered as a risk factor for DR induction and progression.

PMID:
30728185
DOI:
10.2337/db18-0912
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13.
Diabetes Care. 2019 Feb 6. pii: dc182316. doi: 10.2337/dc18-2316. [Epub ahead of print]

International Consensus on Risk Management of Diabetic Ketoacidosis in Patients with Type 1 Diabetes Treated with Sodium-Glucose Cotransporter (SGLT) Inhibitors.

Danne T1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Garg S1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Peters AL1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Buse JB1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Mathieu C1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Pettus JH1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Alexander CM1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Battelino T1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Ampudia-Blasco FJ1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Bode BW1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Cariou B1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Close KL1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Dandona P1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Dutta S1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Ferrannini E1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Fourlanos S1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Grunberger G1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Heller SR1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Henry RR1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Kurian MJ1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Kushner JA1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Oron T1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Parkin CG30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,51, Pieber TR1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Rodbard HW1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Schatz D1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Skyler JS1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Tamborlane WV1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Yokote K1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22, Phillip M1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,22.

Author information

1
Diabetes Centre for Children and Adolescents, AUF DER BULT, Kinder- und Jugendkrankenhaus, Hannover, Germany.
2
University of Colorado Denver and Barbara Davis Center for Diabetes, Aurora, Colorado U.S.A.
3
Keck School of Medicine of the University of Southern California , Los Angeles, CA, USA.
4
University of North Carolina School of Medicine, Chapel Hill, North Carolina. USA.
5
Department of Endocrinology, UZ Gasthuisberg KU Leuven, Leuven, Belgium.
6
Division of Endocrinology, University of California, San Diego, CA, USA.
7
Alexander Associates LLC, Gwynedd Valley, Pennsylvania, USA.
8
Department of Pediatric Endocrinology, Diabetes and Metabolism, University Medical Centre-University Children's Hospital, and Faculty of Medicine, University of Ljubljana, Slovenia.
9
Clinic University Hospital of Valencia, Valencia, Spain.
10
Atlanta Diabetes Associates, Atlanta, Georgia, USA.
11
Clinique d'endocrinologie, L'institut du thorax, CHU Nantes, CIC 1413, INSERM, Nantes, France.
12
The diaTribe Foundation, San Francisco, California, USA.
13
Endocrinology, Diabetes and Metabolism, State University of New York, Buffalo, NY., USA.
14
JDRF International, New York, New York, USA.
15
CNR Institute of Clinical Physiology, 56126 Pisa, Italy.
16
Department of Diabetes and Endocrinology, Royal Melbourne Hospital, Melbourne, Australia.
17
Grunberger Diabetes Institute, Bloomfield Hills, MI, USA.
18
Academic Unit of Diabetes, Endocrinology and Metabolism, University of Sheffield, Sheffield, United Kingdom.
19
Department of Medicine, University of California San Diego, San Diego, California, USA.
20
Close Concerns, San Francisco, California, USA.
21
McNair Interests, Houston, TX, USA.
22
The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, and Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel.
23
CGParkin Communications, Inc., Boulder City, NV, USA.
24
Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria.
25
Endocrine and Metabolic Consultants , Rockville, Maryland, USA.
26
Division of Endocrinology, Department of Pediatrics, University of Florida, Gainesville, FL, USA.
27
Division of Endocrinology, Diabetes and Metabolism, Miller School of Medicine, University of Miami, Miami, FL, USA.
28
Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut, U.S.A.
29
Department of Diabetes, Metabolism and Endocrinology, Chiba University Graduate School of Medicine. Chiba, Japan.
30
Diabetes Centre for Children and Adolescents, AUF DER BULT, Kinder- und Jugendkrankenhaus, Hannover, Germany chris@cgparkin.org.
31
University of Colorado Denver and Barbara Davis Center for Diabetes, Aurora, Colorado U.S.A. chris@cgparkin.org.
32
Keck School of Medicine of the University of Southern California , Los Angeles, CA, USA chris@cgparkin.org.
33
University of North Carolina School of Medicine, Chapel Hill, North Carolina. USA chris@cgparkin.org.
34
Department of Endocrinology, UZ Gasthuisberg KU Leuven, Leuven, Belgium chris@cgparkin.org.
35
Division of Endocrinology, University of California, San Diego, CA, USA chris@cgparkin.org.
36
Alexander Associates LLC, Gwynedd Valley, Pennsylvania, USA chris@cgparkin.org.
37
Department of Pediatric Endocrinology, Diabetes and Metabolism, University Medical Centre-University Children's Hospital, and Faculty of Medicine, University of Ljubljana, Slovenia chris@cgparkin.org.
38
Clinic University Hospital of Valencia, Valencia, Spain chris@cgparkin.org.
39
Atlanta Diabetes Associates, Atlanta, Georgia, USA chris@cgparkin.org.
40
Clinique d'endocrinologie, L'institut du thorax, CHU Nantes, CIC 1413, INSERM, Nantes, France chris@cgparkin.org.
41
The diaTribe Foundation, San Francisco, California, USA chris@cgparkin.org.
42
Endocrinology, Diabetes and Metabolism, State University of New York, Buffalo, NY., USA chris@cgparkin.org.
43
JDRF International, New York, New York, USA chris@cgparkin.org.
44
CNR Institute of Clinical Physiology, 56126 Pisa, Italy. chris@cgparkin.org.
45
Department of Diabetes and Endocrinology, Royal Melbourne Hospital, Melbourne, Australia chris@cgparkin.org.
46
Grunberger Diabetes Institute, Bloomfield Hills, MI, USA. chris@cgparkin.org.
47
Academic Unit of Diabetes, Endocrinology and Metabolism, University of Sheffield, Sheffield, United Kingdom chris@cgparkin.org.
48
Department of Medicine, University of California San Diego, San Diego, California, USA chris@cgparkin.org.
49
Close Concerns, San Francisco, California, USA chris@cgparkin.org.
50
McNair Interests, Houston, TX, USA chris@cgparkin.org.
51
The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, and Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel chris@cgparkin.org.
52
CGParkin Communications, Inc., Boulder City, NV, USA chris@cgparkin.org.
53
Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria chris@cgparkin.org.
54
Endocrine and Metabolic Consultants , Rockville, Maryland, USA chris@cgparkin.org.
55
Division of Endocrinology, Department of Pediatrics, University of Florida, Gainesville, FL, USA chris@cgparkin.org.
56
Division of Endocrinology, Diabetes and Metabolism, Miller School of Medicine, University of Miami, Miami, FL, USA chris@cgparkin.org.
57
Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut, U.S.A. chris@cgparkin.org.
58
Department of Diabetes, Metabolism and Endocrinology, Chiba University Graduate School of Medicine. Chiba, Japan chris@cgparkin.org.

Abstract

Sodium glucose cotransporter (SGLT) inhibitors are new oral antidiabetic medications shown to effectively reduce glycated hemoglobin (A1C) and glycemic variability, blood pressure and body weight without intrinsic properties to cause hypoglycemia in people with type 1 diabetes. However, recent studies, particularly in individuals with type 1 diabetes, have demonstrated increases in the absolute risk of diabetic ketoacidosis (DKA). Some cases presented with near-normal blood glucose levels or mild hyperglycemia, complicating the recognition/diagnosis of DKA and potentially delaying treatment. Several SGLT-inhibitors are currently under review by US Food and Drug Administration (FDA) and European regulatory agencies as an adjunct to insulin therapy in people with type 1 diabetes. Strategies must be developed and disseminated to the medical community to mitigate the associated DKA risk. This consensus report reviews current data regarding SGLT- inhibitor use and provides recommendations to enhance the safety of SGLT-inhibitors in people with type 1 diabetes.

PMID:
30728224
DOI:
10.2337/dc18-2316
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14.
Diabetes Care. 2019 Feb 6. pii: dc182472. doi: 10.2337/dc18-2472. [Epub ahead of print]

Association of Diabetes and Glycated Hemoglobin With the Risk of Intracerebral Hemorrhage: A Population-Based Cohort Study.

Author information

1
Department of Community Medicine and Epidemiology, Lady Davis Carmel Medical Center, Clalit Health Services, Haifa, Israel.
2
Ruth and Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel.
3
Statistical Unit, Lady Davis Carmel Medical Center, Clalit Health Services, Haifa, Israel.
4
Pharmacoepidemiology and Pharmacogenetics Unit, Lady Davis Carmel Medical Center, Clalit Health Services, Haifa, Israel.
5
Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
6
Ruth and Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel eitanman1@gmail.com.
7
Department of Neurology, Lady Davis Carmel Medical Center, Clalit Health Services, Haifa, Israel.

Abstract

OBJECTIVE:

To examine the association of diabetes and glycated hemoglobin (HbA1c) with the risk of intracerebral hemorrhage (ICH) in a large population-based cohort.

RESEARCH DESIGN AND METHODS:

The computerized database of the largest health care provider in Israel was used to identify adult members aged 40 years or older and alive at 1 January 2010 (297,486 with diabetes and 1,167,585 without diabetes). The cohort was followed until 31 December 2017 for incidence of ICH. Multivariable Cox proportional hazards regression models, adjusted for baseline disease risk score, were applied to estimate the hazard ratio (HR) of ICH.

RESULTS:

Overall 4,170 ICH cases occurred during 10,730,915 person-years of follow-up. Diabetes was independently associated with increased ICH risk, with hazard ratio (HR) 1.36 (95% CI 1.27-1.45), and increased with longer diabetes duration: 1.23 (1.12-1.35) and 1.44 (1.34-1.56) for diabetes duration ≤5 years and >5 years, respectively. The increased ICH risk associated with diabetes was more pronounced in patients ≤60 years old (P interaction <0.001). Among patients with diabetes, HbA1c had a nonlinear J-shaped relationship with ICH (P for nonlinearity = 0.0186). Compared to the fourth HbA1c decile 6.5%-6.7% (48-50 mmol/mol), the HR for ICH was 1.27 (1.01-1.59) and 2.19 (1.75-2.73) in the lowest decile ≤ 6.0% (≤42mmol/mol) and highest HbA1c decile >9.3% (>78mmol/mol), respectively.

CONCLUSIONS:

Diabetes is associated with increased risk of ICH that is directly associated with diabetes duration. ICH and HbA1c appear to have a J-shaped relationship, suggesting that both poor control as well as extreme intensive diabetes control might be associated with increased risk.

PMID:
30728223
DOI:
10.2337/dc18-2472
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15.
Diabetes Care. 2019 Feb 6. pii: dc182047. doi: 10.2337/dc18-2047. [Epub ahead of print]

Glycemic Variability Is a Powerful Independent Predictive Factor of Midterm Major Adverse Cardiac Events in Patients With Diabetes With Acute Coronary Syndrome.

Author information

1
Cardiology Intensive Care Unit and Interventional Cardiology, Hôpital Cardiologique du Haut Lévêque, Pessac, France.
2
Bordeaux Cardio-Thoracic Research Centre, U1045, Bordeaux University, Bordeaux, France.
3
Biochemistry Laboratory, Hôpital Cardiologique du Haut-Lévêque, Bordeaux University, Pessac, France.
4
Endocrinology-Nutrition Department, Centre Hospitalier de Périgueux, Périgueux, France.
5
Department of Cardiovascular Medicine, Hôpital Cardiologique du Haut Lévêque, Bordeaux University, Pessac, France.
6
Department of Anaesthesia and Critical Care, Magellan Medico-Surgical Centre, Bordeaux University, Pessac, France.
7
Biology of Cardiovascular Diseases Centre, U1034, Bordeaux University, Pessac, France.
8
Endocrinology-Metabolic Diseases, Hôpital Saint-André, Bordeaux University, Bordeaux, France bogdan.catargi@chu-bordeaux.fr.

Abstract

OBJECTIVE:

Acute glucose fluctuations are associated with hypoglycemia and are emerging risk factors for cardiovascular outcomes. However, the relationship between glycemic variability (GV) and the occurrence of midterm major cardiovascular events (MACE) in patients with diabetes remains unclear. This study investigated the prognostic value of GV in patients with diabetes and acute coronary syndrome (ACS).

RESEARCH DESIGN AND METHODS:

This study included consecutive patients with diabetes and ACS between January 2015 and November 2016. GV was assessed using SD during initial hospitalization. MACE, including new-onset myocardial infarction, acute heart failure, and cardiac death, were recorded. The predictive effects of GV on patient outcomes were analyzed with respect to baseline characteristics and cardiac status.

RESULTS:

A total of 327 patients with diabetes and ACS were enrolled. MACE occurred in 89 patients (27.2%) during a mean follow-up of 16.9 months. During follow-up, 24 patients (7.3%) died of cardiac causes, 35 (10.7%) had new-onset myocardial infarction, and 30 (9.2%) were hospitalized for acute heart failure. Multivariable logistic regression analysis showed that GV >2.70 mmol/L, a Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) score of >34, and reduced left ventricular ejection fraction of <40% were independent predictors of MACE, with odds ratios (ORs) of 2.21 (95% CI 1.64-2.98; P < 0.001), 1.88 (1.26-2.82; P = 0.002), and 1.71 (1.14-2.54; P = 0.009), respectively, whereas a Global Registry of Acute Coronary Events risk score >140 was not (OR 1.07 [0.77-1.49]; P = 0.69).

CONCLUSIONS:

A GV cutoff value of >2.70 mmol/L was the strongest independent predictive factor for midterm MACE in patients with diabetes and ACS.

PMID:
30728222
DOI:
10.2337/dc18-2047
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16.
Diabetes Care. 2019 Feb 6. pii: dc171726. doi: 10.2337/dc17-1726. [Epub ahead of print]

Changes in Screening Practices for Prediabetes and Diabetes Since the Recommendation for Hemoglobin A1c Testing.

Author information

1
Department of Internal Medicine, University of Michigan, Ann Arbor, MI.
2
Department of Epidemiology, University of Michigan, Ann Arbor, MI.
3
Department of Internal Medicine, University of Michigan, Ann Arbor, MI lmattei@umich.edu.

Abstract

OBJECTIVE:

Screening involves the presumptive identification of asymptomatic individuals at increased risk for unrecognized disease. We examined changes in screening practices for prediabetes and diabetes since January 2010, when HbA1c was first recommended as an option for screening and diagnosis.

RESEARCH DESIGN AND METHODS:

We studied members without diabetes of an HMO ≥45 years of age continuously enrolled for ≥3 years and assigned to primary care clinicians affiliated with a large academic health system. We defined screening as the first oral glucose tolerance test, HbA1c, or glucose test performed between 2010 and 2014.

RESULTS:

Of 12,772 eligible patients, 9,941 (78%) were screened at least once over 3 years. HbA1c was the initial screening test 14% of the time and glucose 86% of the time. Of those screened with HbA1c, 63% had abnormal results defined as HbA1c ≥5.7% (≥39 mmol/mol). Of those tested with glucose, 30% had abnormal results defined as glucose ≥100 mg/dL, and 5% had abnormal results defined as glucose ≥126 mg/dL. Patients with abnormal HbA1c levels and those with glucose levels ≥126 mg/dL were equally likely to be scheduled for follow-up appointments (41% vs. 39%), but those with abnormal HbA1c levels were more likely to be diagnosed with prediabetes or diabetes (36% vs. 26%).

CONCLUSIONS:

As we observed in 2004, rates of screening are high. HbA1c is still used less frequently than glucose for screening but is more likely to result in a clinical diagnosis. Evidence to support guidelines to define the role of random glucose screening including definition of appropriate cut points and follow-up is needed.

PMID:
30728220
DOI:
10.2337/dc17-1726
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Diabetes Care. 2019 Feb 6. pii: dc182034. doi: 10.2337/dc18-2034. [Epub ahead of print]

Dairy Product Intake and Risk of Type 2 Diabetes in EPIC-InterAct: A Mendelian Randomization Study.

Author information

1
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
2
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands i.sluijs-2@umcutrecht.nl.
3
MRC Epidemiology Unit, University of Cambridge, Cambridge, U.K.
4
Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, U.K.
5
Navarre Public Health Institute (ISPN), Pamplona, Spain.
6
German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany.
7
Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Institut Catalá d'Oncologia, Barcelona, Spain.
8
Department of Epidemiology, Regional Health Council, IMIB-Arrixaca, University of Murcia, Murcia, Spain.
9
CIBER in Epidemiology and Public Health (CIBERESP), Madrid, Spain.
10
CESP UMR1018, INSERM, Institut Gustave Roussy, Paris South University-Paris-Saclay University, Villejuif, France.
11
Lund University, Malmö, Sweden.
12
Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France.
13
Public Health Directorate, Asturias, Spain.
14
Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark.
15
German Cancer Research Center (DKFZ), Heidelberg, Germany.
16
University of Oxford, Oxford, U.K.
17
Public Health Division of Gipuzkoa, Biodonostia Research Institute, San Sebastian, Spain.
18
Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark.
19
Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
20
Cancer Risk Factors and LifeStyle Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy.
21
Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy.
22
Unit of Cancer Epidemiology, University Hospital "Città della Salute e della Scienza," University of Turin, and Center for Cancer Prevention (CPO), Torino, Italy.
23
National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
24
Danish Cancer Society Research Center, Copenhagen, Denmark.
25
ASP Ragusa, Ragusa, Italy.
26
Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs.GRANADA, Hospitales Universitarios de Granada, Universidad de Granada, Granada, Spain.
27
Umeå University, Umeå, Sweden.
28
School of Public Health, Imperial College London, London, U.K.

Abstract

OBJECTIVE:

To estimate the causal association between intake of dairy products and incident type 2 diabetes.

RESEARCH DESIGN AND METHODS:

The analysis included 21,820 European individuals (9,686 diabetes cases) of the EPIC-InterAct case-cohort study. Participants were genotyped, and rs4988235 (LCT-12910C>T), a SNP for lactase persistence (LP) which enables digestion of dairy sugar, i.e., lactose, was imputed. Baseline dietary intakes were assessed with diet questionnaires. We investigated the associations between imputed SNP dosage for rs4988235 and intake of dairy products and other foods through linear regression. Mendelian randomization (MR) estimates for the milk-diabetes relationship were obtained through a two-stage least squares regression.

RESULTS:

Each additional LP allele was associated with a higher intake of milk (β 17.1 g/day, 95% CI 10.6-23.6) and milk beverages (β 2.8 g/day, 95% CI 1.0-4.5) but not with intake of other dairy products. Other dietary intakes associated with rs4988235 included fruits (β -7.0 g/day, 95% CI -12.4 to -1.7 per additional LP allele), nonalcoholic beverages (β -18.0 g/day, 95% CI -34.4 to -1.6), and wine (β -4.8 g/day, 95% CI -9.1 to -0.6). In instrumental variable analysis, LP-associated milk intake was not associated with diabetes (hazard ratio 0.99per 15 g/day, 95% CI 0.93-1.05).

CONCLUSIONS:

rs4988235 was associated with milk intake but not with intake of other dairy products. This MR study does not suggest that milk intake is associated with diabetes, which is consistent with previous observational and genetic associations. LP may be associated with intake of other foods as well, but owing to the modest associations we consider it unlikely that this has caused the observed null result.

PMID:
30728219
DOI:
10.2337/dc18-2034
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18.
Diabetes Care. 2019 Feb 6. pii: dc181574. doi: 10.2337/dc18-1574. [Epub ahead of print]

Association of Insulin Dose, Cardiometabolic Risk Factors, and Cardiovascular Disease in Type 1 Diabetes During 30 Years of Follow-up in the DCCT/EDIC Study.

Author information

1
Biostatistics Center, The George Washington University, Rockville, MD braffett@bsc.gwu.edu.
2
Division of Endocrinology, Diabetes and Metabolism, University of Tennessee Health Science Center, Memphis, TN.
3
Biostatistics Center, The George Washington University, Rockville, MD.
4
Division of Endocrinology and Metabolism, Department of Internal Medicine, University of Iowa, Iowa City, IA.
5
Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston, MA.
6
University of California, San Diego, La Jolla, CA.

Abstract

OBJECTIVE:

The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study demonstrated the beneficial effects of intensive therapy on atherosclerosis and clinical cardiovascular disease (CVD) outcomes. The current analyses evaluated the relationship between longitudinal changes in insulin dose and CVD risk factors and outcomes.

RESEARCH DESIGN AND METHODS:

A total of 1,441 participants were randomly assigned to intensive or conventional diabetes therapy during the DCCT. After an average of 6.5 years of follow-up, 96% of the surviving cohort enrolled in the EDIC observational study, which included annual visits with detailed medical history, physical examination, and laboratory testing. CVD events were adjudicated by a review committee. Generalized linear mixed models and Cox proportional hazards regression models were used to assess the association between insulin dose and cardiometabolic risk factors and CVD risk, respectively, over a total of 30 years.

RESULTS:

Higher insulin doses were significantly associated with a less favorable cardiometabolic risk profile (higher BMI, pulse rate, triglycerides, and lower HDL cholesterol) with the exception of lower diastolic blood pressure and lower LDL cholesterol. In a minimally adjusted model, a 0.1 unit/kg body wt/day increase in insulin dose was associated with a 6% increased risk of any CVD (95% CI 3, 9). However, the association with insulin dose was no longer significant after adjustment for other CVD risk factors.

CONCLUSIONS:

During DCCT/EDIC, higher insulin doses were associated with adverse trends in several cardiometabolic risk factors, even after multivariable adjustment, but not with incident CVD outcomes.

PMID:
30728218
DOI:
10.2337/dc18-1574
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19.
Diabetes Care. 2019 Jan 31. pii: dc181948. doi: 10.2337/dc18-1948. [Epub ahead of print]

Effect of Glucose Improvement on Spirometric Maneuvers in Patients With Type 2 Diabetes: The Sweet Breath Study.

Author information

1
Endocrinology and Nutrition Department, Hospital Universitari Arnau de Vilanova, Obesity, Diabetes and Metabolism Research Group (ODIM), Institut de Recerca Biomèdica de Lleida (IRBLleida), Universitat de Lleida, Lleida, Catalonia, Spain.
2
Respiratory Department, Hospital Universitari Arnau de Vilanova-Santa María, Translational Research in Respiratory Medicine, Institut de Recerca Biomèdica de Lleida (IRBLleida), Universitat de Lleida, Lleida, Catalonia, Spain.
3
Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
4
Endocrinology and Nutrition Department, Hospital Universitari Vall d'Hebron, Diabetes and Metabolism Research Unit, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain.
5
CIBERDEM, Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
6
Endocrinology and Nutrition Department, Hospital Universitari Vall d'Hebron, Diabetes and Metabolism Research Unit, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain rafael.simo@vhebron.net.
7
Endocrinology and Nutrition Department, Hospital Universitari Arnau de Vilanova, Obesity, Diabetes and Metabolism Research Group (ODIM), Institut de Recerca Biomèdica de Lleida (IRBLleida), Universitat de Lleida, Lleida, Catalonia, Spain alecube@gmail.com.

Abstract

OBJECTIVE:

Type 2 diabetes exerts a deleterious effect on lung function. However, it is unknown whether an improvement in glycemic control ameliorates pulmonary function.

RESEARCH DESIGN AND METHODS:

Prospective interventional study with 60 patients with type 2 diabetes and forced expiratory volume in 1 s (FEV1) ≤90% of predicted. Spirometric maneuvers were evaluated at baseline and after a 3-month period in which antidiabetic therapy was intensified. Those with an HbA1c reduction of ≥0.5% were considered to be good responders (n = 35).

RESULTS:

Good responders exhibited a significant improvement in spirometric values between baseline and the end of the study (forced vital capacity [FVC]: 78.5 ± 12.6% vs. 83.3 ± 14.7%, P = 0.029]; FEV1: 75.6 ± 15.3% vs. 80.9 ± 15.4%, P = 0.010; and peak expiratory flow [PEF]: 80.4 ± 21.6% vs. 89.2 ± 21.0%, P = 0.007). However, no changes were observed in the group of nonresponders when the same parameters were evaluated (P = 0.586, P = 0.987, and P = 0.413, respectively). Similarly, the initial percentage of patients with a nonobstructive ventilatory defect and with an abnormal FEV1 decreased significantly only among good responders. In addition, the absolute change in HbA1c inversely correlated to increases in FEV1 (r = -0.370, P = 0.029) and PEF (r = -0.471, P = 0.004) in the responders group. Finally, stepwise multivariate regression analysis showed that the absolute change in HbA1c independently predicted increased FEV1 (R 2 = 0.175) and PEF (R 2 = 0.323). In contrast, the known duration of type 2 diabetes, but not the amelioration of HbA1c, was related to changes in forced expiratory flow between 25% and 75% of the FVC.

CONCLUSIONS:

In type 2 diabetes, spirometric measurements reflecting central airway obstruction and explosive muscle strength exhibit significant amelioration after a short improvement in glycemic control.

PMID:
30705064
DOI:
10.2337/dc18-1948
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Diabetes Care. 2019 Jan 31. pii: dc181738. doi: 10.2337/dc18-1738. [Epub ahead of print]

The Impact of Obesity on the Incidence of Type 2 Diabetes Among Women With Polycystic Ovary Syndrome.

Author information

1
Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria, Australia.
2
Diabetes and Vascular Medicine Unit, Monash Health, Clayton, Victoria, Australia.
3
Monash Partners Academic Health Sciences Centre, Melbourne, Victoria, Australia.
4
Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria, Australia anju.joham@monash.edu.

Abstract

OBJECTIVE:

The nature of the independent relationship between polycystic ovary syndrome (PCOS) and type 2 diabetes remains unclear. Few studies have aimed to clarify this relationship independent of obesity in longitudinal population-based cohorts.

RESEARCH DESIGN AND METHODS:

We used the Australian Longitudinal Study on Women's Health (ALSWH) (2000-2015) database to estimate nationwide incidence rates and predictors of type 2 diabetes among women aged 18-42 using person-time and survival analysis.

RESULTS:

Over a follow-up of 1,919 person-years (PYs), 186 women developed type 2 diabetes. The incidence rate was 4.19/1,000 and 1.02/1,000 PYs (P < 0.001) in PCOS and control subjects. On subgroup analyses across healthy-weight, overweight, and obese categories of women, the incidence rates for type 2 diabetes were 3.21, 4.67, and 8.80, whereas incidence rate ratios were 4.68, 3.52, and 2.36 (P < 0.005) in PCOS versus age-matched control subjects. PCOS was one of the most influential predictors for type 2 diabetes in the entire cohort (hazard ratio 3.23, 95% CI 2.07-5.05, P < 0.001) adjusting for BMI, education, area of residence, and family history of type 2 diabetes.

CONCLUSIONS:

Women with PCOS are at an increased risk of type 2 diabetes, irrespective of age and BMI. The incidence of type 2 diabetes increases substantially with increasing obesity; yet, PCOS adds a greater relative risk in lean women. Based on the overall moderate absolute clinical risk demonstrated here, guideline recommendations suggest type 2 diabetes screening every 1-3 years in all women with PCOS, across BMI categories and age ranges, with frequency influenced by additional type 2 diabetes risk factors.

PMID:
30705063
DOI:
10.2337/dc18-1738
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