Evidence map›Paper›PMID 30803451›Full record

ArticleBMC medicine2019

Advances in the clinical management of type 2 diabetes: a brief history of the past 15 years and challenges for the future.

Naveed Sattar

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Big data and machine learning to tackle diabetes management.European journal of clinical investigation · 2023
    Review
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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

1 author.

Naveed SattarInstitute of Cardiovascular and Medical Sciences, University of Glasgow, 126 University Place, Glasgow, G12 8TA, UK. Naveed.sattar@glasgow.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Remarkable progress has been made in some aspects of diabetes care over the last 15 years, but there have also been a rising number of challenges that differ between high and low-income countries. In high-income countries, a substantial increase in the use of preventative drugs for cardiovascular disease has lowered vascular complications and improved diabetes survival. More recently, new classes of diabetes drugs have emerged that can variably lower cardiovascular outcomes, new-onset heart failure and slow renal decline, thereby meaningfully increasing the diabetes armoury that should help patients to live even longer lives and with fewer complications. At the other end of the disease spectrum, we can now better prevent diabetes in people who are at elevated risk of developing it, whereas other new research has shown that diabetes remission is possible when lifestyle changes are made in the early years after diagnosis. The downside is that more people than ever before have type 2 diabetes, so despite such progress in high-income countries, the absolute burden of disease is rising. Furthermore, it is rising even faster in low and middle-income countries, where rising adiposity is driving a tidal wave of new diabetes cases; yet, healthcare systems are less able to cope, lacking sufficient drugs, trained personnel and integrated care systems. Thus, despite advances, the future challenges from rising diabetes rates worldwide are daunting.

Indexed as

Diabetes Mellitus, Type 2ForecastingHumansTime FactorsAdiposityCardiovascular diseaseGlycaemiaHeart failurePrevalencePreventionRemissionRisk factors

Identifiers

PMID30803451
PMCPMC6390346

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.