scholarly journals Lifetime risk and years lost to type 1 and type 2 diabetes in Denmark, 1996–2016

2021 ◽  
Vol 9 (1) ◽  
pp. e001065
Author(s):  
Bendix Carstensen ◽  
Pernille Falberg Rønn ◽  
Marit Eika Jørgensen
Keyword(s):  
Type 2 Diabetes ◽  
Population Level ◽  
Lifetime Risk ◽  
Individual Level ◽  
Number Of Patients ◽  
Incidence And Mortality ◽  
The Difference ◽  
The Individual

IntroductionLifetime risk and lifetime lost to diabetes are measures of current diabetes burden in a population. We aimed at quantifying these measures in the Danish population.Research design and methodsWe modeled incidence and mortality of type 1 diabetes (T1D) and type 2 diabetes (T2D) and non-diabetes mortality based on complete follow-up of the entire population of Denmark in 1996–2016. A multistate model with these transition rates was used to assess the lifetime risk of diabetes, as well as the difference in expected lifetime between persons with type 1 and T2D and persons without.ResultsIn 2016, the lifetime risk of T1D was 1.1% and that for T2D 24%, the latter a 50% increase from 1996. For 50-year-old persons, the lifetime lost was 6.6 years for T1D and 4.8 years for T2D. These figures have been declining over the study period.At 2016, the total foreseeable lives lost in Denmark among patients with T1D were 182 000 years, and those among patients with T2D were 766 000 years, corresponding to 6.6 and 3.0 years per person, respectively.ConclusionAt the individual level, improvements in the disease burden for both T1D and T2D have occurred. At the population level, the increasing number of patients with T2D has contributed to a large increase in the total loss of lifetime.

Diabetic Retinopathy In Patients With Type 2 Diabetes: Aspects Of Early Diagnosis, Treatment And Prediction Of The Outcome Of The Disease

2021 ◽  
Vol 03 (07) ◽  
pp. 53-65
Author(s):  
Fazilat Arifovna Bakhritdinova ◽  
◽  
Urmanova Firuza Makhkamovna ◽  
Nabiyeva Iroda Fayzullayevna ◽  
◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Hong Kong ◽  
Early Diagnosis ◽  
Research Group ◽  
Black Population ◽  
The Past ◽  
Number Of Patients

In this review, the authors performed an overview of the literature on early diagnosis, treatment and methods for predicting the outcomes of the disease. According to regional endocrinological dispensaries, for 2020 registered SD for RUZ 277 926., Of these, type 1 type 18178, SD 2 type 259,748 patients. At the same time, the number of patients with DR was 2020 g of 83,632 persons, of which 73690 persons with di type 2. The real number of patients exceeds a registered 10 times, over the past 18 years, the number of patients with a rope in Uzbekistan increased by 2.4 times (according to the Ministry of Health of RUZ). The prevalence of others among patients of the CD is 10-90%, according to some specialists, up to 97-98.5%. For example, the frequency of development dr in India is lower than among Europeans and Americans, and among the black population more frequent than among the white. According to the WHO research group, it was revealed that the highest frequency of DR was detected in Oklahoma (76.4%), Zagreb (73.1%) and Hong Kong (58.1%). The lowest frequency was observed in Tokyo (29.7%). The prevalence of DR in patients in China amounted to 47.4%, and the frequency of DR in Poland was 31.4%.

scholarly journals Resistance to Acetaminophen Interference in a Novel Continuous Glucose Monitoring System

2018 ◽  
Vol 12 (2) ◽  
pp. 393-396 ◽  
Author(s):  
Peter Calhoun ◽  
Terri Kang Johnson ◽  
Jonathan Hughes ◽  
David Price ◽  
Andrew K. Balo
Keyword(s):  
Type 2 Diabetes ◽  
Real Time ◽  
Monitoring System ◽  
Continuous Glucose Monitoring ◽  
Interference Effect ◽  
Glucose Monitoring ◽  
Post Dose ◽  
The Difference

Acetaminophen (APAP) can cause erroneously high readings in real-time continuous glucose monitoring (rtCGM) systems. APAP-associated bias in an investigational rtCGM system (G6) was evaluated by taking the difference in glucose measurements between rtCGM and YSI from 1 hour before to 6 hours after a 1-g oral APAP dose in 66 subjects with type 1 or type 2 diabetes. The interference effect was defined as the average post-dose (30-90 minutes) bias minus the average baseline bias for each subject. The clinically meaningful interference effect was defined as 10 mg/dL. The G6 system’s overall mean (±SD) interference effect was 3.1 ± 4.8 mg/dL (one-sided upper 95% CI = 4.1 mg/dL), significantly lower than 10 mg/dL. The G6 system’s resistance to APAP interference should provide reassurance to those using the drug.

scholarly journals The future of Diabetic Kidney Disease management: reducing the unmet need

2020 ◽  
Vol 33 (6) ◽  
pp. 1163-1169
Author(s):  
Dick de Zeeuw
Keyword(s):  
Type 2 Diabetes ◽  
Renal Function ◽  
Unmet Need ◽  
Renal Tissue ◽  
Efficacy And Safety ◽  
Investigational Drugs ◽  
Number Of Patients ◽  
Function Loss ◽  
The Individual

AbstractPatients with type 2 diabetes run a high risk for progressive renal function loss. Many interventions have been tested to reduce the risk, but we are nowadays still confronted with a high unmet need. To improve on this unmet need, we will have to change the current strategies in drug discovery, clinical trials and clinical practice. Target finding and the search for new interventions has to change to include more individual mechanistic approaches. Drugs will be selected on basis of finding the “individual” mechanism of renal function loss by looking at renal tissue biopsies or new biomarkers in urine or plasma. To test the promising drugs for clinical efficacy and safety and reduce the unmet need, trial design in type 2 diabetes will have to alter. First, selection of patients at risk for progression of renal function loss will need to be more specific. True progressors need to be identified by switching from classical risk determinants (low eGFR and high albuminuria) to new surrogates like steep eGFR slopes. In addition, the investigational drugs should only continue into registration trials in responder populations: patients that show a good response in the target/surrogate risk marker and no bad responses. This way we will improve the success of hard outcome trials, which has been poor in the past decade. We will reduce the unmet need and reduce the number of patients that are exposed to long term trial treatments without any benefit or even harm. Platform design and basket trials will catch the non-responders and switch them to other investigational drugs with different mechanism of action.Drug registration will be much more directed to the individual patients and will lead to improved individual patient medication advices and improved individual efficacy and safety. We are entering the era of precision medicine in nephrology.

Cardivascular Risk Profile in Patients with Diabetes and Acromegaly or Cushing’s Disease – Analysis from the DPV Database

2018 ◽  
Vol 128 (02) ◽  
pp. 104-110 ◽  
Author(s):  
Katharina Warncke ◽  
Sebastian Kummer ◽  
Peter Herbert Kann ◽  
Dominik Bergis ◽  
Esther Bollow ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Cushing’S Disease ◽  
Cushing's Disease ◽  
Dipeptidyl Peptidase 4 ◽  
Number Of Patients ◽  
Dipeptidyl Peptidase 4 Inhibitors ◽  
Patients With Diabetes

Abstract Background Although diabetes is a common complication of acromegaly or Cushing´s disease, there are only few detailed studies with a focus on cardiovascular risk, metabolic control or diabetes therapy. Here, we provide a comprehensive characterization from the longitudinal DPV (Diabetes Patienten Verlaufsdokumentation) registry. Methods Patients from the registry≥18 years of age with diabetes and acromegaly or Cushing´s disease were compared to patients with type 1 diabetes or type 2 diabetes using the statistical software SAS 9.4. Results Patients with diabetes and acromegaly (n=52) or Cushing’s disease (n=15) were significantly younger at diabetes onset (median age 50.1 and 45.0 vs. 59.0 years in type 2 diabetes; both p<0.05). Dyslipidemia was common in both diseases (71.0% and 88.9% vs. 71.8% in type 2 diabetes; n.s.), while hypertension was most frequent in acromegaly (56.8% vs. 20.9% in type 1 diabetes, p<0.00001). 36.5% of patients with acromegaly and 46.7% with Cushing´s disease receive insulin, compared to 50.4% with type 2 diabetes. Oral antidiabetic drugs were used in 36.5% of patients with acromegaly and 40% with Cushing´s disease, with a predominance of biguanides and dipeptidyl peptidase-4 inhibitors. HbA1c was well controlled in both groups (median 7.0% and 6.5%; vs. 7.2% in type 2 diabetes). Conclusion Patients with acromegaly are at a high risk for cardiovascular disease, reflected by dyslipidemia and hypertension. A high proportion of patients with diabetes in acromegaly or Cushing´s disease receives insulin. Based on a multicenter register, a sufficient number of patients with rare forms of diabetes can be analyzed.

Optimality analysis of Th1/Th2 immune responses during microparasite-macroparasite co-infection, with epidemiological feedbacks

Parasitology ◽  
2008 ◽  
Vol 135 (7) ◽  
pp. 841-853 ◽  
Author(s):  
ANDY FENTON ◽  
TRACEY LAMB ◽  
ANDREA L. GRAHAM
Keyword(s):  
Immune Responses ◽  
Population Level ◽  
Parasite Abundance ◽  
Individual Level ◽  
Host Immune Responses ◽  
Individual Host ◽  
Diverse Community ◽  
The Individual ◽  
Optimality Models

SUMMARYIndividuals are typically co-infected by a diverse community of microparasites (e.g. viruses or protozoa) and macroparasites (e.g. helminths). Vertebrates respond to these parasites differently, typically mounting T helper type 1 (Th1) responses against microparasites and Th2 responses against macroparasites. These two responses may be antagonistic such that hosts face a ‘decision’ of how to allocate potentially limiting resources. Such decisions at the individual host level will influence parasite abundance at the population level which, in turn, will feed back upon the individual level. We take a first step towards a complete theoretical framework by placing an analysis of optimal immune responses under microparasite-macroparasite co-infection within an epidemiological framework. We show that the optimal immune allocation is quantitatively sensitive to the shape of the trade-off curve and qualitatively sensitive to life-history traits of the host, microparasite and macroparasite. This model represents an important first step in placing optimality models of the immune response to co-infection into an epidemiological framework. Ultimately, however, a more complete framework is needed to bring together the optimal strategy at the individual level and the population-level consequences of those responses, before we can truly understand the evolution of host immune responses under parasite co-infection.

scholarly journals Type 2 diabetes in children in the Netherlands: the need for diagnostic protocols

2007 ◽  
Vol 157 (2) ◽  
pp. 175-180 ◽  
Author(s):  
Joost Rotteveel ◽  
Eline J Belksma ◽  
Carry M Renders ◽  
Remy A Hirasing ◽  
Henriette A Delemarre-Van de Waal
Keyword(s):  
Type 2 Diabetes ◽  
The Netherlands ◽  
Clinical Characteristics ◽  
Daily Practice ◽  
Number Of Children ◽  
Number Of Patients ◽  
Diagnosis And Classification ◽  
Overweight Or Obesity

Objective: The worldwide trend towards obesity in childhood is also observed in the Netherlands and one of the consequences may be type 2 diabetes. In this study, we assessed the number of children with type 2 diabetes, diagnosed by paediatricians, in the Netherlands. Methods: In 2003 and 2004 the Dutch Paediatric Surveillance Unit, a nationwide paediatric register, was used to assess new cases of diabetes mellitus. Data on socio-demographic and clinical characteristics were collected by means of a questionnaire. A second questionnaire was sent to the reporting paediatrician if the diagnosis was inconclusive or if the diagnosis was type 1 diabetes in combination with overweight or obesity, according to international criteria. Results: During the 24 months of registration, the paediatricians reported 1142 new cases of diabetes, 943 of which were eligible for analysis. Initially, 14 patients (1.5%) were reported with type 2 diabetes. Only seven of these patients were classified as type 2 diabetes according to the ADA criteria, as information on C-peptides or antibodies was often missing. Based on clinical characteristics, the other seven patients were very likely to have type 2 diabetes. After the second questionnaire, six more patients met the ADA criteria and two were very likely to have type 2 diabetes. Most of the patients were female (95%), 14% were of Turkish and 18% of Moroccan origin. Conclusion: This study shows a discrepancy between the number of patients with type 2 diabetes diagnosed by paediatricians in daily practice and diagnosed according to the ADA criteria. Moreover, a considerable amount of reported patients were misclassified. Finally, 2.4% patients were classified as (very likely) type 2 diabetes. The development of programmes and protocols for prevention, diagnosis and classification applicable in daily practice is warranted.

scholarly journals Which Green Space Metric Best Predicts a Lowered Odds of Type 2 Diabetes?

2021 ◽  
Vol 18 (8) ◽  
pp. 4088
Author(s):  
Soumya Mazumdar ◽  
Shanley Chong ◽  
Thomas Astell-Burt ◽  
Xiaoqi Feng ◽  
Geoffrey Morgan ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Road Network ◽  
Green Space ◽  
Estimating Equation ◽  
The Novel ◽  
Individual Level ◽  
Circular Buffer ◽  
Area Metric ◽  
The Individual

The choice of a green space metric may affect what relationship is found with health outcomes. In this research, we investigated the relationship between percent green space area, a novel metric developed by us (based on the average contiguous green space area a spatial buffer has contact with), in three different types of buffers and type 2 diabetes (T2D). We obtained information about diagnosed T2D and relevant covariates at the individual level from the large and representative 45 and Up Study. Average contiguous green space and the percentage of green space within 500 m, 1 km, and 2 km of circular buffer, line-based road network (LBRN) buffers, and polygon-based road network (PBRN) buffers around participants’ residences were used as proxies for geographic access to green space. Generalized estimating equation regression models were used to determine associations between access to green space and T2D status of individuals. It was found that 30%–40% green space within 500 m LBRN or PBRN buffers, and 2 km PBRN buffers, but not within circular buffers, significantly reduced the risk of T2D. The novel average green space area metric did not appear to be particularly effective at measuring reductions in T2D. This study complements an existing research body on optimal buffers for green space measurement.

scholarly journals Risk Factors For Diabetic Retinopathy Progression

2015 ◽  
Vol 22 (2) ◽  
pp. 159-165
Author(s):  
Mónika Deák ◽  
Monica Lasca ◽  
Ioan Andrei Vereşiu
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Proliferative Diabetic Retinopathy ◽  
Smoking Status ◽  
Diabetes Duration ◽  
Diabetes Diagnosis ◽  
Number Of Patients

AbstractBackground and Aims. There is no unanimous opinion regarding the risk factors associated with progression of diabetic retinopathy (DR). We have done a retrospective analysis of risk factors and clinical features associated with DR progression.Material and Methods. This analysis included consecutive patients with moderate non-proliferative or severe retinopathy between December 1, 2013 and May 31, 2014 who had at least two eye examinations before that period. We have collected demographic, clinical and lab data.Results. 51.28% of patients were diagnosed with moderate non-proliferative diabetic retinopathy (NPDR), 24.68% with severe NPDR and 21.05% with proliferative diabetic retinopathy. In 82.16% of cases, DR had progressed. The risk factor correlated with DR progression in the whole group was anemia; hypertension, anemia and diabetes duration were risk factors in type 1 and smoking status at diabetes diagnosis in type 2 diabetes. Total cholesterol, triglycerides, diabetes control and presence of diabetic renal disease were positively but not statistically significant correlated with DR progression.Conclusions. In our study the risk factors correlated with DR progression were hypertension, anemia and diabetes duration in type 1, respectively smoking at diabetes diagnosis in type 2 diabetes. Glycemic goals were achieved in a small number of patients.

scholarly journals Sex-Gender Awareness in Diabetes

Diabetology ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 117-122
Author(s):  
Giancarlo Tonolo
Keyword(s):  
Type 2 Diabetes ◽  
Gender Differences ◽  
Type 1 Diabetes ◽  
Quality Of Care ◽  
Sex And Gender ◽  
And Gender ◽  
The Individual

Sex and gender can affect incidence, prevalence, symptoms, course and response to drug therapy in many illnesses, being sex (the biological side) and gender (the social-cultural one), variously interconnected. Indeed, women have greater longevity; however, this is accompanied by worse health than men, particularly when obesity is present. Sex-gender differences are fundamental also in both type 1 and type 2 diabetes. Just for example in the prediabetes situation impaired fasting glucose (expression of increased insulin resistance) is more common in men, while impaired glucose tolerance (expression of beta cell deficiency) is more common in female, indicating a possible different genesis of type 2 diabetes in the two sexes. In type 1 diabetes male and female are equivalent as incidence of the disease since puberty, while estrogens act as protective and reduce the incidence of type 1 diabetes in female after puberty. Considering macrovascular complications, diabetic women have a 3.5 fold higher increased cardiovascular risk than non diabetic women, against an observed increase of “only” 2.1 fold in male. Thus it is clear, although not fully explained, that sex-gender differences do exist in diabetes. Another less studied aspect is that also physician gender influences quality of care in patients with type 2 diabetes, female physicians providing an overall better quality of care, especially in risk management. The goal of this short commentary is to open the special issue of Diabetology: “Gender Difference in Diabetes” leaving to the individual articles to deepen differences in genesis, psychologists aspects and complications of the disease.

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