Evidence map›Paper›PMID 41837708›Full record

ArticleDiabetes care2026

Improving the Algorithm: The Inclusion of a Socioeconomic Status Measure in Predicting Type 2 Diabetes Development in Youth With Prediabetes.

Subin Jang, Yinzhao Wang, Sisi Ma, Daniel S Hsia, Kristina Cossen, David Haynes, Megan O Bensignor

Abstract read
In one paragraph

Article in Diabetes care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Subin JangCenter for Pediatric Obesity Medicine, University of Minnesota, Minneapolis, MN.ORCID 0000-0002-2950-8487
Yinzhao WangInstitute for Health Informatics, University of Minnesota, Minneapolis, MN.
Sisi MaInstitute for Health Informatics, University of Minnesota, Minneapolis, MN.
Daniel S HsiaDivision of Endocrinology, Department of Pediatrics, Emory University, Atlanta, GA.
Kristina CossenDivision of Endocrinology, Department of Pediatrics, Emory University, Atlanta, GA.
David HaynesInstitute for Health Informatics, University of Minnesota, Minneapolis, MN.
Megan O BensignorCenter for Pediatric Obesity Medicine, University of Minnesota, Minneapolis, MN.ORCID 0000-0002-9341-1858

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UM1TR004405 · NCATS · UNIVERSITY OF MINNESOTA · PI Bruce R Blazar, Damien A Fair · 2023 to 2026
$30.8M
Anti-obesity pharmacotherapy to decrease BMI and improve insulin sensitivity in adolescents with obesity and type 2 diabetesK23DK129721 · NIDDK · UNIVERSITY OF MINNESOTA · PI BENSIGNOR, MEGAN O · 2021 to 2025
$1.0M
Division of Diabetes, Endocrinology, and Metabolic Diseases K23DK129721NCATS NIH HHS UM1 TR004405NIDDK NIH HHS K23 DK129721
6 · The paper itself

Abstract

objectiveTo evaluate whether the Area Deprivation Index (ADI) contributes to predicting type 2 diabetes development in youth with prediabetes compared with a machine learning (ML) model built with other data elements. RESEARCH DESIGN AND

methodsPatient encounters (n = 665) from an electronic medical record were used to build supervised ML models to predict type 2 diabetes development within 1 year of prediabetes diagnosis. The ADI was constructed using patients' census block data. Two models, trained on data with and without ADI, were built. The model selection resulted in logistic regressions with 1) HbA1c only and 2) HbA1c + ADI as the best models from each data set.

resultsA total of 181 patient encounters (27.2%) developed type 2 diabetes. The area under the receiver operating characteristic curve of the HbA1c-only model was 0.68 and of the HbA1c + ADI model, 0.73.

conclusionsThe addition of ADI to the model resulted in the best performance in predicting youth-onset type 2 diabetes development.

Indexed as

AlgorithmsDiabetes Mellitus, Type 2Prediabetic StateAdolescentChildClassification AlgorithmsData AnalyticsFemaleGlycated HemoglobinHumansMachine LearningMalePrediction AlgorithmsPredictive Learning ModelsSocial ClassGlycated Hemoglobin

Identifiers

PMID41837708
PMCPMC13094864

What OpenQuestion holds

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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.