Evidence map›Paper›PMID 29896313›Full record

ReviewThe EPMA journal2018

Diabetes care in figures: current pitfalls and future scenario.

Alexandre Assuane Duarte, Shahriar Mohsin, Olga Golubnitschaja

Open access · bronzeAbstract readReview
In one paragraph

Review in The EPMA journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
6.7field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 65 citations in OpenAlex.

  1. Pooled it
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  18. Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China.Diabetes, metabolic syndrome and obesity : targets and therapy · 2021
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Alexandre Assuane DuarteInstituto Master de Ensino Presidente Antonio Carlos (IMEPAC), Araguari, Minas Gerais Brazil.
Shahriar Mohsin2CEMBIO, Rhinische Friedrich-Wilhelms-University of Bonn, Bonn, Germany.
Olga Golubnitschaja3Radiological Clinic, Rheinische Friedrich-Wilhelms-Universität Bonn, Sigmund-Freud-Str 25, 53105 Bonn, Germany.
University of Bonn · DEUniversidade Presidente Antônio Carlos · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AdolescenceComorbiditiesCostsDiabetes mellitusEconomyEpidemicHealth policyMedical carePitfallsPredictive preventive personalised medicinePrevalencePrognose

Identifiers

PMID29896313
PMCPMC5972141
OpenAlexW2803138390

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.