ArticleJournal of diabetes and metabolic disorders2024
Development of type 2 diabetes risk assessment model for Turkish society.
Article in Journal of diabetes and metabolic disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Central adiposity outperforms disordered eating behavior in predicting type 2 diabetes risk in young adults: an explainable machine learning approach.Frontiers in public health · 2026Article
- The Effect and Mechanism of Regular Exercise on Improving Insulin Impedance: Based on the Perspective of Cellular and Molecular Levels.International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: The study was conducted to develop a risk assessment tool to determine the Turkish population's risk of undiagnosed type 2 diabetes. Methods: The study was carried out in a methodological design. A total of 610 individuals, including those diagnosed with diabetes (321) and not diagnosed with diabetes (289), who applied to the internal medicine and diabetes outpatient clinics of a public hospital, were included in the study. The sample of patients with diabetes was created with the individuals who applied to diabetes outpatient clinics, were 40 years of age and older, and had the values of FPG ≥ 126 mg/dl and HbA1C ≥ 6.5%. The sample of healthy individuals consisted of people over the age of 40 who were not diagnosed with diabetes or prediabetes. Logistic regression and random forest algorithms were used to evaluate the diabetes risk of individuals. The performance of the models was evaluated with sensitivity, specificity, accuracy, and area under the ROC (AUC). Result: In the study, the variables of exercise in daily routines, presence of prediabetes, getting angry, feeling hungry frequently, and excessive thirst formed the diabetes risk assessment model with Sensitivity 0.983 and Specificity 0.984 according to the logistic regression model obtained. Body mass index, physical activity, age, gender, and family history of diabetes were not found to be significant in differentiating cases with diabetes (0.05 < p). Conclusion: This diabetes risk assessment tool is a reliable tool for Turkish society to identify individuals at high risk for diabetes and to raise awareness of the importance of modifiable risk factors.
Indexed as
Identifiers
What OpenQuestion holds
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.