Evidence map›Paper›PMID 34634866›Full record

ArticleAnnals of pediatric endocrinology & metabolism2022

Demographic and diagnostic markers in new onset pediatric type 1 and type 2 diabetes: differences and overlaps.

Teresa Nieto, Beatriz Castillo, Jacobo Nieto, Maria J Redondo

Open access · diamondAbstract read
In one paragraph

Article in Annals of pediatric endocrinology & metabolism, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.7field-weighted citation impact, top 14% 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

9 citing papers in PubMed, 16 citations in OpenAlex.

  1. Biological and Social Risk Factors for Predicting Type 2 Diabetes in Youth with Prediabetes: Review of Existing Prediction Models.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2026
    Review
  2. Classification ofJCEM case reports · 2026
    Article
  3. Article
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  8. Development and Validation of a Distress Measurement Related to Glucose Monitoring of Diabetes Patients.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2023
    Article
  9. Data Mining Framework for Discovering and Clustering Phenotypes of Atypical Diabetes.The Journal of clinical endocrinology and metabolism · 2023
    Article
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

4 authors at 3 institutions in 1 country.

Teresa NietoSt. Agnes Academy, Houston, TX, USA.
Beatriz CastilloBaylor College of Medicine, School of Medicine, Houston, TX, USA.
Jacobo NietoRice University, Houston, TX, USA.
Maria J RedondoBaylor College of Medicine, Texas Children's Hospital, Houston, TX, USA.
Baylor College of Medicine · USRice University · USSt. Albans School · US

Funding

Type 1 diabetes genetic risk scores for the diagnosis of diabetes type in children of diverse racial and ethnic backgroundR01DK124395 · NIDDK · BAYLOR COLLEGE OF MEDICINE · PI REDONDO, MARIA JOSE · 2021 to 2024
$2.6M
Type 1 Diabetes Genetic Risk Score in TrialNetR01DK121843 · NIDDK · BAYLOR COLLEGE OF MEDICINE · PI REDONDO, MARIA JOSE · 2019 to 2023
$2.4M
NIDDK NIH HHS R01 DK121843NIDDK NIH HHS R01 DK124395
6 · The paper itself

Abstract

purposeType 1 diabetes (T1D) is the most common type of diabetes in children, but the frequency of type 2 diabetes (T2D) is increasing rapidly. Classification of diabetes is based on a constellation of features that vary by type. We aimed to compare demographic, clinical, and laboratory characteristics at diagnosis of pediatric T1D and T2D.

methodsWe studied children who visited a large academic hospital in Houston, Texas (USA) with a new diagnosis of T2D (n=753) or T1D (n=758). We compared age, sex, race/ethnicity, presence of obesity, glucose, hemoglobin A1c, islet autoantibody positivity, C-peptide, and presence of diabetic ketoacidosis (DKA) at diabetes diagnosis.

resultsAt diagnosis, children with T2D, compared with those with T1D, were older (13.6 years vs. 9.7 years), more likely female (63.2% vs. 47.8%), of racial/ethnic minority (91.1% vs. 42.3%), and obese (90.9% vs. 19.4%) and were less likely to have DKA (7.8% vs. 35.0%) and diabetes autoantibodies (5.5% vs. 95.4%). Children with T2D also had significantly lower glucose, lower hemoglobin A1c and lower C-peptide level (all comparisons, p<0.0001). In multiple logistic regression analysis, older age, racial/ethnic minority, obesity, higher C-peptide, and negative islet autoantibodies were independently associated with T2D (all, p<0.05), while sex, glucose, hemoglobin A1c, and DKA were not (model p<0.0001).

conclusionThere are important demographic, clinical, and laboratory differences between T1D and T2D in children. However, none of the characteristics were unique to either diabetes type, which poses challenges to diabetes classification at diagnosis.

Indexed as

AutoimmunityClassificationDiagnosisOverlapPediatricType 1 diabetesType 2 diabetes

Identifiers

PMID34634866
PMCPMC9260368
OpenAlexW3205436207

What OpenQuestion holds

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LicenceCC BY-NC
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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.