Evidence map›Paper›PMID 36307139›Full record

ArticleBMJ open diabetes research & care2022

Global diabetes burden: analysis of regional differences to improve diabetes care.

Charline Bour, Adrian Ahne, Gloria Aguayo, Aurélie Fischer, David Marcic, Philippe Kayser, Guy Fagherazzi

Abstract read
In one paragraph

Article in BMJ open diabetes research & care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

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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

7 authors.

Charline BourDepartment of Precision Health, Deep Digital Phenotyping Research Unit, Luxembourg Institute of Health, Strassen, Luxembourg.
Adrian AhneCenter for Research in Epidemiology and Population Health (CESP), INSERM, Villejuif (Paris), Île-de-France, France.
Gloria AguayoDepartment of Precision Health, Deep Digital Phenotyping Research Unit, Luxembourg Institute of Health, Strassen, Luxembourg.ORCID 0000-0002-5625-1664
Aurélie FischerDepartment of Precision Health, Deep Digital Phenotyping Research Unit, Luxembourg Institute of Health, Strassen, Luxembourg.
David MarcicDepartment of Precision Health, Data Integration and Analysis Unit, Luxembourg Institute of Health, Strassen, Luxembourg.
Philippe KayserDepartment of Precision Health, Data Integration and Analysis Unit, Luxembourg Institute of Health, Strassen, Luxembourg.
Guy FagherazziDepartment of Precision Health, Deep Digital Phenotyping Research Unit, Luxembourg Institute of Health, Strassen, Luxembourg Guy.Fagherazzi@lih.lu.ORCID 0000-0001-5033-5966

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe current evaluation processes of the burden of diabetes are incomplete and subject to bias. This study aimed to identify regional differences in the diabetes burden on a universal level from the perspective of people with diabetes. RESEARCH DESIGN AND

methodsWe developed a worldwide online diabetes observatory based on 34 million diabetes-related tweets from 172 countries covering 41 languages, spanning from 2017 to 2021. After translating all tweets to English, we used machine learning algorithms to remove institutional tweets and jokes, geolocate users, identify topics of interest and quantify associated sentiments and emotions across the seven World Bank regions.

resultsWe identified four topics of interest for people with diabetes (PWD) in the Middle East and North Africa and another 18 topics in North America. Topics related to glycemic control and food are shared among six regions of the world. These topics were mainly associated with sadness (35% and 39% on average compared with levels of sadness in other topics). We also revealed several region-specific concerns (eg, insulin pricing in North America or the burden of daily diabetes management in Europe and Central Asia).

conclusionsThe needs and concerns of PWD vary significantly worldwide, and the burden of diabetes is perceived differently. Our results will support better integration of these regional differences into diabetes programs to improve patient-centric diabetes research and care, focused on the most relevant concerns to enhance personalized medicine and self-management of PWD.

Indexed as

Diabetes MellitusMachine LearningEuropeHumansMiddle EastNorth Americaalgorithmspatient-centered carepatient reported outcome measurespopulation health

Identifiers

PMID36307139
PMCPMC9621169

What OpenQuestion holds

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Registered trials

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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.