ArticleJournal of diabetes investigation2021
Simple risk score to screen for prediabetes: A cross-sectional study from the Qatar Biobank cohort.
Article in Journal of diabetes investigation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.
- Machine learning models for identifying prediabetes: a systematic review of performance, validation, and implications for primary care.Frontiers in medicine · 2026Pooled it
- A dual domain systematic review and meta-analysis of risk tool accuracy to predict cardiovascular morbidity in prehypertension and diabetic morbidity in prediabetes.Frontiers in endocrinology · 2025Pooled it
- Ethnic and Gender Disparities in Risk Factors for Prediabetes-A Retrospective Exploratory Analysis in Southern Israel.Journal of clinical medicine · 2026Article
- Screening Tools for Early Identification of Adults at High Risk of Type 2 Diabetes: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- A point-based laminitis risk scoring system and machine learning framework for prediction of laminitis in horses.Frontiers in veterinary science · 2026Article
- Developing a Simple Non-Laboratory-Based Machine Learning Tool for Prediabetes Screening in a Target Population: A Proof-of-Concept Study.Journal of diabetes science and technology · 2025Article
- Optimizing Feature Selection and Machine Learning Algorithms for Early Detection of Prediabetes Risk: Comparative Study.JMIR bioinformatics and biotechnology · 2025Article
- Usefulness of the Córdoba Equation for Estimating Body Fat When Determining the Level of Risk of Developing Diabetes Type 2 or Prediabetes.Medicina (Kaunas, Lithuania) · 2025Article
- Development and Validation of Machine Learning Models for Identifying Prediabetes and Diabetes in Normoglycemia.Diabetes/metabolism research and reviews · 2024Article
- External validation of the Hong Kong Chinese non-laboratory risk models and scoring algorithm for case finding of prediabetes and diabetes mellitus in primary care.Journal of diabetes investigation · 2024Article
- Real-world clinical validation of the Qatar pre-diabetes risk score: a cross-sectional study.BMJ public health · 2024Article
- An ensemble-based machine learning model for predicting type 2 diabetes and its effect on bone health.BMC medical informatics and decision making · 2024Article
- Review
- Non-Laboratory-Based Risk Prediction Tools for Undiagnosed Pre-Diabetes: A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
- The triglyceride glucose-waist-to-height ratio outperforms obesity and other triglyceride-related parameters in detecting prediabetes in normal-weight Qatari adults: A cross-sectional study.Frontiers in public health · 2023Article
- Prediabetes in Syria and Its Associated Factors: A Single-Center Cross-Sectional Study.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2022Article
- Identifying Glucose Metabolism Status in Nondiabetic Japanese Adults Using Machine Learning Model with Simple Questionnaire.Computational and mathematical methods in medicine · 2022Article
- Simple risk score to screen for prediabetes: A cross-sectional study from the Qatar Biobank cohort.Journal of diabetes investigation · 2021Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
AIMS/
introductionThe progression from prediabetes to type 2 diabetes is preventable by lifestyle intervention and/or pharmacotherapy in a large fraction of individuals with prediabetes. Our objective was to develop a risk score to screen for prediabetes in the Middle East, where diabetes prevalence is one of the highest in the world. MATERIALS AND
methodsIn this cross-sectional, case-control study, we used data of 4,895 controls and 2,373 prediabetic adults obtained from the Qatar Biobank cohort. Significant risk factors were identified by logistic regression and other machine learning methods. The receiver operating characteristic was used to calculate the area under curve, cut-off point, sensitivity, specificity, positive and negative predictive values. The prediabetes risk score was developed from data of Qatari citizens, as well as long-term (≥15 years) residents.
resultsThe significant risk factors for the Prediabetes Risk Score in Qatar were age, sex, body mass index, waist circumference and blood pressure. The risk score ranges from 0 to 45. The area under the curve of the score was 80% (95% confidence interval 78-83%), and the cut-off point of 16 yielded sensitivity and specificity of 86.2% (95% confidence interval 82.7-89.2%) and 57.9% (95% confidence interval 65.5-71.4%), respectively. Prediabetes Risk Score in Qatar performed equally in Qatari nationals and long-term residents.
conclusionsPrediabetes Risk Score in Qatar is the first prediabetes screening score developed in a Middle Eastern population. It only uses risk factors measured non-invasively, is simple, cost-effective, and can be easily understood by the general public and health providers. Prediabetes Risk Score in Qatar is an important tool for early detection of prediabetes, and can help tremendously in curbing the diabetes epidemic in the region.
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Registered trials
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.