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Developing a risk score for undiagnosed prediabetes or type 2 diabetes among Saharawi refugees in Algeria

AIMS: To prevent type 2 diabetes mellitus (T2D) and reduce the risk of complications, early identification of people at risk of developing T2D, preferably through simple diabetes risk scores, is essential. The aim of this study was to create a risk score for identifying subjects with undiagnosed pre...

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Autores principales: Henjum, Sigrun, Hjellset, Victoria Telle, Andersen, Eivind, Flaaten, Merete Øyaland, Morseth, Marianne S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9004169/
https://www.ncbi.nlm.nih.gov/pubmed/35410198
http://dx.doi.org/10.1186/s12889-022-13007-0
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author Henjum, Sigrun
Hjellset, Victoria Telle
Andersen, Eivind
Flaaten, Merete Øyaland
Morseth, Marianne S.
author_facet Henjum, Sigrun
Hjellset, Victoria Telle
Andersen, Eivind
Flaaten, Merete Øyaland
Morseth, Marianne S.
author_sort Henjum, Sigrun
collection PubMed
description AIMS: To prevent type 2 diabetes mellitus (T2D) and reduce the risk of complications, early identification of people at risk of developing T2D, preferably through simple diabetes risk scores, is essential. The aim of this study was to create a risk score for identifying subjects with undiagnosed prediabetes or T2D among Saharawi refugees in Algeria and compare the performance of this score to the Finnish diabetes risk score (FINDRISC). METHODS: A cross-sectional survey was carried out in five Saharawi refugee camps in Algeria in 2014. A total of 180 women and 175 men were included. HbA1c and cut-offs proposed by the American Diabetes Association (ADA) were used to define cases. Variables to include in the risk score were determined by backwards elimination in logistic regression. Simplified scores were created based on beta coefficients from the multivariable model after internal validation with bootstrapping and shrinkage. The empirical cut-off value for the simplified score and FINDRISC was determined by Area Under the Receiver Operating Curve (AUROC) analysis. RESULTS: Variables included in the final risk score were age, body mass index (BMI), and waist circumference. The area under the curve (AUC) (C.I) was 0.82 (0.76, 0.88). The sensitivity, specificity, and positive and negative predictive values were 89, 65, 28, and 97%, respectively. AUC and sensitivity were slightly higher and specificity somewhat lower than for FINDRISC. CONCLUSIONS: The risk score developed is a helpful tool to decide who should be screened for prediabetes or T2D by blood sample analysis. The performance of the risk score was adequate based on internal validation with bootstrap analyses, but should be confirmed in external validation studies.
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spelling pubmed-90041692022-04-13 Developing a risk score for undiagnosed prediabetes or type 2 diabetes among Saharawi refugees in Algeria Henjum, Sigrun Hjellset, Victoria Telle Andersen, Eivind Flaaten, Merete Øyaland Morseth, Marianne S. BMC Public Health Research AIMS: To prevent type 2 diabetes mellitus (T2D) and reduce the risk of complications, early identification of people at risk of developing T2D, preferably through simple diabetes risk scores, is essential. The aim of this study was to create a risk score for identifying subjects with undiagnosed prediabetes or T2D among Saharawi refugees in Algeria and compare the performance of this score to the Finnish diabetes risk score (FINDRISC). METHODS: A cross-sectional survey was carried out in five Saharawi refugee camps in Algeria in 2014. A total of 180 women and 175 men were included. HbA1c and cut-offs proposed by the American Diabetes Association (ADA) were used to define cases. Variables to include in the risk score were determined by backwards elimination in logistic regression. Simplified scores were created based on beta coefficients from the multivariable model after internal validation with bootstrapping and shrinkage. The empirical cut-off value for the simplified score and FINDRISC was determined by Area Under the Receiver Operating Curve (AUROC) analysis. RESULTS: Variables included in the final risk score were age, body mass index (BMI), and waist circumference. The area under the curve (AUC) (C.I) was 0.82 (0.76, 0.88). The sensitivity, specificity, and positive and negative predictive values were 89, 65, 28, and 97%, respectively. AUC and sensitivity were slightly higher and specificity somewhat lower than for FINDRISC. CONCLUSIONS: The risk score developed is a helpful tool to decide who should be screened for prediabetes or T2D by blood sample analysis. The performance of the risk score was adequate based on internal validation with bootstrap analyses, but should be confirmed in external validation studies. BioMed Central 2022-04-11 /pmc/articles/PMC9004169/ /pubmed/35410198 http://dx.doi.org/10.1186/s12889-022-13007-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Henjum, Sigrun
Hjellset, Victoria Telle
Andersen, Eivind
Flaaten, Merete Øyaland
Morseth, Marianne S.
Developing a risk score for undiagnosed prediabetes or type 2 diabetes among Saharawi refugees in Algeria
title Developing a risk score for undiagnosed prediabetes or type 2 diabetes among Saharawi refugees in Algeria
title_full Developing a risk score for undiagnosed prediabetes or type 2 diabetes among Saharawi refugees in Algeria
title_fullStr Developing a risk score for undiagnosed prediabetes or type 2 diabetes among Saharawi refugees in Algeria
title_full_unstemmed Developing a risk score for undiagnosed prediabetes or type 2 diabetes among Saharawi refugees in Algeria
title_short Developing a risk score for undiagnosed prediabetes or type 2 diabetes among Saharawi refugees in Algeria
title_sort developing a risk score for undiagnosed prediabetes or type 2 diabetes among saharawi refugees in algeria
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9004169/
https://www.ncbi.nlm.nih.gov/pubmed/35410198
http://dx.doi.org/10.1186/s12889-022-13007-0
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