Evidence map›Paper›PMID 29309270›Full record

Observational studyThe Permanente journal2018

A Simple Model for Predicting Two-Year Risk of Diabetes Development in Individuals with Prediabetes.

Harry Glauber, William M Vollmer, Gregory A Nichols

Abstract readObservational Study
In one paragraph

Observational study in The Permanente journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 16% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

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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.

Harry GlauberRetired Endocrinologist, formerly at the Sunnyside Medical Center in Clackamas, OR, and the Center for Health Research in Portland, OR, and former Visiting Scientist at the Galil Center for Telemedicine, Medical Informatics and Personalized Medicine at RB Rappaport Faculty of Medicine, Technion Israel Institute of Technology in Haifa. harryg123123@gmail.com.
William M VollmerSenior Investigator at the Center for Health Research in Portland, OR. william.vollmer@kpchr.org.
Gregory A NicholsSenior Investigator at the Center for Health Research in Portland, OR. greg.nichols@kpchr.org.
Oregon Health & Science University · USRappaport Family Institute for Research in the Medical Sciences · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextGiven the dramatic rise in the incidence of type 2 diabetes mellitus (T2DM) in recent decades, identifying individuals at increased risk of T2DM and validating methods to reduce their risk of disease progression is important. With more than one-third of US adults having prediabetes, a more precise stratification of absolute risk of T2DM incidence would help in prioritizing prevention efforts.

objectiveTo develop a simple and clinically useful schema to stratify short-term (2-year) absolute risk of T2DM.

designObservational study of more than 77,000 adult members (age 18-75 years) from 3 Regions of the Kaiser Foundation Health Plan with prediabetes (hemoglobin A

main outcome measuresThe 2-year probability for development of diabetes as a function of baseline HbA

resultsThe 2-year risk of diabetes diagnosis varied widely by HbA

conclusionUsing HbA

Indexed as

AdolescentAdultAgedAlgorithmsBody Mass IndexChildDiabetes Mellitus, Type 2Disease ProgressionFemaleGlycated HemoglobinHumansIncidenceMaleMiddle AgedPrediabetic StateRisk FactorsGlycated Hemoglobin

Identifiers

PMID29309270
PMCPMC5760055
OpenAlexW2781641520

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.