Evidence map›Paper›PMID 24843455›Full record

ReviewJournal of diabetes investigation2011

What can we learn from the recent blood glucose lowering megatrials?

Juliana Cn Chan

Open access · bronzeAbstract readReview
In one paragraph

Review in Journal of diabetes investigation, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
  5. Diabetes and its comorbidities--where East meets West.Nature reviews. Endocrinology · 2013
    Review
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 at 1 institution in 2 countries.

Juliana Cn ChanDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong, China.
Chinese University of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the past two decades, we have acquired an enormous amount of knowledge regarding the epidemiology, diagnosis, pathophysiology and treatment of type 2 diabetes and its comorbidities. In addition to the earlier landmark blood lipid and blood pressure lowering trials, the latest blood glucose lowering megatrials represent the zenith of this global effort to prevent and control diabetes, and its devastating consequences. Although many of these latter trials have yielded negative results and have shown the narrow risk-benefit ratio of intensive treatment in patients with advanced disease, the exceedingly low event rates in these high-risk patients who were carefully monitored and intensively managed made possible in these clinical trial settings have not been emphasized enough. The heterogeneity of the clinical outcomes in these studies further highlight the complexity of diabetes, which is more than managing a disease, but the multiple needs of a patient with multisystem dysfunction. In the final analysis, what transpires from these megatrials is the need to translate the key components of these studies, namely, protocol, team, documentation and monitoring, into our daily clinical practice to enable the care team to stratify risk, define needs, individualize therapy, monitor progress and reinforce compliance in order to achieve positive outcomes. (J Diabetes Invest, doi: 10.1111/j.2040-1124.2010.00063.x, 2010).

Indexed as

DiabetesDisease managementRandomized clinical trials

Identifiers

PMID24843455
PMCPMC4008009
OpenAlexW1618055289

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.