Literature DB >> 29896313

Diabetes care in figures: current pitfalls and future scenario.

Alexandre Assuane Duarte1, Shahriar Mohsin2, Olga Golubnitschaja3,4,5.   

Abstract

Diabetes mellitus (DM) epidemic-on a global scale-is a major and snowballing threat to public health, healthcare systems and economy, due to the cascade of pathologies triggered in a long-term manner after the DM manifestation. There are remarkable differences in the geographic disease spread and acceleration of an increasing DM prevalence recorded. Specifically, the highest initial prevalence of DM was recorded in the Eastern-Mediterranean region in 1980 followed by the highest acceleration of the epidemic characterised by 0.23% of an annual increase resulted in 2.3 times higher prevalence in the year 2014. In contrast, while the European region in 1980 demonstrated the second highest prevalence, the DM epidemic developments were kept much better under control compared to all other regions in the world. Although both non-modifiable and modifiable risk factors play a role in DM predisposition, cross-sectional investigations recently conducted amongst elderly individuals demonstrate that ageing as a non-modifiable risk factor is directly linked to unhealthy lifestyle as a well-acknowledged modifiable risk factor which, in turn, may strongly promote ageing process related to DM even in young populations. Consequently, specifically modifiable risk factors should receive a particular attention in the context of currently observed DM epidemic prognosed to expand significantly over 600 million of diabetes-diseased people by the year 2045. The article analyses demographic profiles of DM patient cohorts as well as the economic component of the DM-related crisis and provides prognosis for future scenarios on a global scale. The innovative approach by predictive diagnostics, targeted prevention and treatments tailored to the person in a suboptimal health condition (before clinical onset of the disease), as the medicine of the future is the most prominent option to reverse currently persisting disastrous trends in diabetes care. The key role of biomedical sciences in the future developments of diabetes care is discussed.

Entities:  

Keywords:  Adolescence; Comorbidities; Costs; Diabetes mellitus; Economy; Epidemic; Health policy; Medical care; Pitfalls; Predictive preventive personalised medicine; Prevalence; Prognose

Year:  2018        PMID: 29896313      PMCID: PMC5972141          DOI: 10.1007/s13167-018-0133-y

Source DB:  PubMed          Journal:  EPMA J        ISSN: 1878-5077            Impact factor:   6.543


  13 in total

1.  Risk factors for diabetic peripheral sensory neuropathy. Results of the Seattle Prospective Diabetic Foot Study.

Authors:  A I Adler; E J Boyko; J H Ahroni; V Stensel; R C Forsberg; D G Smith
Journal:  Diabetes Care       Date:  1997-07       Impact factor: 19.112

Review 2.  Impaired wound healing: facts and hypotheses for multi-professional considerations in predictive, preventive and personalised medicine.

Authors:  Eden Avishai; Kristina Yeghiazaryan; Olga Golubnitschaja
Journal:  EPMA J       Date:  2017-03-03       Impact factor: 6.543

3.  Human skin wounds: a major and snowballing threat to public health and the economy.

Authors:  Chandan K Sen; Gayle M Gordillo; Sashwati Roy; Robert Kirsner; Lynn Lambert; Thomas K Hunt; Finn Gottrup; Geoffrey C Gurtner; Michael T Longaker
Journal:  Wound Repair Regen       Date:  2009 Nov-Dec       Impact factor: 3.617

Review 4.  Advanced Diabetes care: three levels of prediction, prevention & personalized treatment.

Authors:  Olga Golubnitschaja
Journal:  Curr Diabetes Rev       Date:  2010-01

Review 5.  The Economic Costs of Type 2 Diabetes: A Global Systematic Review.

Authors:  Till Seuring; Olga Archangelidi; Marc Suhrcke
Journal:  Pharmacoeconomics       Date:  2015-08       Impact factor: 4.981

Review 6.  Medicine in the early twenty-first century: paradigm and anticipation - EPMA position paper 2016.

Authors:  Olga Golubnitschaja; Babak Baban; Giovanni Boniolo; Wei Wang; Rostyslav Bubnov; Marko Kapalla; Kurt Krapfenbauer; Mahmood S Mozaffari; Vincenzo Costigliola
Journal:  EPMA J       Date:  2016-10-25       Impact factor: 6.543

7.  HLA and non-HLA genes and familial predisposition to autoimmune diseases in families with a child affected by type 1 diabetes.

Authors:  Anna Parkkola; Antti-Pekka Laine; Markku Karhunen; Taina Härkönen; Samppa J Ryhänen; Jorma Ilonen; Mikael Knip
Journal:  PLoS One       Date:  2017-11-28       Impact factor: 3.240

8.  Cancer predisposition in diabetics: risk factors considered for predictive diagnostics and targeted preventive measures.

Authors:  Melanie Cebioglu; Hans H Schild; Olga Golubnitschaja
Journal:  EPMA J       Date:  2010-03-11       Impact factor: 6.543

9.  A human model of small fiber neuropathy to study wound healing.

Authors:  Ben M W Illigens; Christopher H Gibbons
Journal:  PLoS One       Date:  2013-01-31       Impact factor: 3.240

10.  Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants.

Authors: 
Journal:  Lancet       Date:  2016-04-06       Impact factor: 79.321

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  21 in total

Review 1.  Risks associated with the stroke predisposition at young age: facts and hypotheses in light of individualized predictive and preventive approach.

Authors:  Jiri Polivka; Jiri Polivka; Martin Pesta; Vladimir Rohan; Libuse Celedova; Smit Mahajani; Ondrej Topolcan; Olga Golubnitschaja
Journal:  EPMA J       Date:  2019-02-20       Impact factor: 6.543

Review 2.  Salivary Biomarkers Associated with Psychological Alterations in Patients with Diabetes: A Systematic Review.

Authors:  Guillermo Bargues-Navarro; Vanessa Ibáñez-Del Valle; Nisrin El Mlili; Omar Cauli
Journal:  Medicina (Kaunas)       Date:  2022-08-12       Impact factor: 2.948

3.  The predictive potential of altered spontaneous brain activity patterns in diabetic retinopathy and nephropathy.

Authors:  Yu Wang; Yi Shao; Wen-Qing Shi; Lei Jiang; Xiao-Yu Wang; Pei-Wen Zhu; Qing Yuan; Ge Gao; Jin-Lei Lv; Gong-Xian Wang
Journal:  EPMA J       Date:  2019-07-05       Impact factor: 6.543

4.  The potential role of angiopoietin-like protein-8 in type 2 diabetes mellitus: a possibility for predictive diagnosis and targeted preventive measures?

Authors:  Yasmine Amr Issa; Samar Samy Abd ElHafeez; Noha Gaber Amin
Journal:  EPMA J       Date:  2019-08-06       Impact factor: 6.543

5.  Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China.

Authors:  Yushan Wang; Yushan Zhang; Kai Wang; Yinxia Su; Jinhui Zhuge; Wenli Li; Shuxia Wang; Hua Yao
Journal:  Diabetes Metab Syndr Obes       Date:  2021-08-07       Impact factor: 3.168

Review 6.  Cancer Biology and Prevention in Diabetes.

Authors:  Swayam Prakash Srivastava; Julie E Goodwin
Journal:  Cells       Date:  2020-06-02       Impact factor: 6.600

7.  Can tailored nanoceria act as a prebiotic? Report on improved lipid profile and gut microbiota in obese mice.

Authors:  Rostyslav Bubnov; Lidiia Babenko; Liudmyla Lazarenko; Maryna Kryvtsova; Oleksandr Shcherbakov; Nadiya Zholobak; Olga Golubnitschaja; Mykola Spivak
Journal:  EPMA J       Date:  2019-10-29       Impact factor: 6.543

8.  Association of IL-16 rs11556218 T/G polymorphism with the risk of developing type 2 diabetes mellitus.

Authors:  Dalia Ghareeb Mohammad; Hamdy Omar; Taghrid B El-Abaseri; Wafaa Omar; Shaymaa Abdelraheem
Journal:  J Diabetes Metab Disord       Date:  2021-04-10

9.  Profile of Podocyte Translatome During Development of Type 2 and Type 1 Diabetic Nephropathy Using Podocyte-Specific TRAP mRNA RNA-seq.

Authors:  Yinqiu Wang; Aolei Niu; Yu Pan; Shirong Cao; Andrew S Terker; Suwan Wang; Xiaofeng Fan; Cynthia L Toth; Marisol A Ramirez Solano; Danielle L Michell; Danielle Contreras; Ryan M Allen; Wanying Zhu; Quanhu Sheng; Agnes B Fogo; Kasey C Vickers; Ming-Zhi Zhang; Raymond C Harris
Journal:  Diabetes       Date:  2021-07-07       Impact factor: 9.337

10.  Positive influence of gut microbiota on the effects of Korean red ginseng in metabolic syndrome: a randomized, double-blind, placebo-controlled clinical trial.

Authors:  Eunhak Seong; Shambhunath Bose; Song-Yi Han; Eun-Ji Song; Myeongjong Lee; Young-Do Nam; Hojun Kim
Journal:  EPMA J       Date:  2021-06-03       Impact factor: 8.836

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