{"title":"制定有效的糖尿病风险图表,作为预测印度尼西亚茂物糖尿病发病的简单工具。","authors":"Eva Sulistiowati, Julianty Pradono","doi":"10.15605/jafes.037.01.09","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To develop a simple, non-invasive tool for predicting the onset of type 2 diabetes mellitus (T2DM). Methodology. A total of 4418 nondiabetic respondents living in Bogor were included in this cohort study. Their ages ranged from 25 to 60 years old and were followed for 6 years with interviews, physical examinations and laboratory tests. The investigators used logistic regression to create a tool for diabetes risk determination.</p><p><strong>Results: </strong>The cumulative incidence of T2DM was 17.9%. Risk factors significantly associated with T2DM included age, obesity, central obesity, hypertension and lack of physical activity. The Bogor Diabetes Risk Prediction (BDRP) chart had a cut-off of 0.128, with sensitivity of 76.6% and specificity of 50.3%. The Positive Predictive Value (PPV) was 21.6% and Negative Predictive Value (NPV) was 92.3%. The Area under the Curve (AUC) was 0.70 with a 95% confidence interval ranging from 0.675-0.721.</p><p><strong>Conclusion: </strong>The BDRP chart is a simple and non-invasive tool to predict T2DM. In addition, the BDRP chart is reliable and can be easily used in primary health care.</p>","PeriodicalId":41792,"journal":{"name":"Journal of the ASEAN Federation of Endocrine Societies","volume":"37 1","pages":"46-52"},"PeriodicalIF":0.6000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/c0/a8/JAFES-37-1-46.PMC9242663.pdf","citationCount":"0","resultStr":"{\"title\":\"Development of a Validated Diabetes Risk Chart as a Simple Tool to Predict the Onset of Diabetes in Bogor, Indonesia.\",\"authors\":\"Eva Sulistiowati, Julianty Pradono\",\"doi\":\"10.15605/jafes.037.01.09\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To develop a simple, non-invasive tool for predicting the onset of type 2 diabetes mellitus (T2DM). Methodology. A total of 4418 nondiabetic respondents living in Bogor were included in this cohort study. Their ages ranged from 25 to 60 years old and were followed for 6 years with interviews, physical examinations and laboratory tests. The investigators used logistic regression to create a tool for diabetes risk determination.</p><p><strong>Results: </strong>The cumulative incidence of T2DM was 17.9%. Risk factors significantly associated with T2DM included age, obesity, central obesity, hypertension and lack of physical activity. The Bogor Diabetes Risk Prediction (BDRP) chart had a cut-off of 0.128, with sensitivity of 76.6% and specificity of 50.3%. The Positive Predictive Value (PPV) was 21.6% and Negative Predictive Value (NPV) was 92.3%. The Area under the Curve (AUC) was 0.70 with a 95% confidence interval ranging from 0.675-0.721.</p><p><strong>Conclusion: </strong>The BDRP chart is a simple and non-invasive tool to predict T2DM. In addition, the BDRP chart is reliable and can be easily used in primary health care.</p>\",\"PeriodicalId\":41792,\"journal\":{\"name\":\"Journal of the ASEAN Federation of Endocrine Societies\",\"volume\":\"37 1\",\"pages\":\"46-52\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/c0/a8/JAFES-37-1-46.PMC9242663.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the ASEAN Federation of Endocrine Societies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15605/jafes.037.01.09\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the ASEAN Federation of Endocrine Societies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15605/jafes.037.01.09","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Development of a Validated Diabetes Risk Chart as a Simple Tool to Predict the Onset of Diabetes in Bogor, Indonesia.
Objective: To develop a simple, non-invasive tool for predicting the onset of type 2 diabetes mellitus (T2DM). Methodology. A total of 4418 nondiabetic respondents living in Bogor were included in this cohort study. Their ages ranged from 25 to 60 years old and were followed for 6 years with interviews, physical examinations and laboratory tests. The investigators used logistic regression to create a tool for diabetes risk determination.
Results: The cumulative incidence of T2DM was 17.9%. Risk factors significantly associated with T2DM included age, obesity, central obesity, hypertension and lack of physical activity. The Bogor Diabetes Risk Prediction (BDRP) chart had a cut-off of 0.128, with sensitivity of 76.6% and specificity of 50.3%. The Positive Predictive Value (PPV) was 21.6% and Negative Predictive Value (NPV) was 92.3%. The Area under the Curve (AUC) was 0.70 with a 95% confidence interval ranging from 0.675-0.721.
Conclusion: The BDRP chart is a simple and non-invasive tool to predict T2DM. In addition, the BDRP chart is reliable and can be easily used in primary health care.
期刊介绍:
The Journal of the ASEAN Federation of Endocrine Societies (JAFES) is an OPEN ACCESS, internationally peer-reviewed, English language, medical and health science journal that is published in print two times a year by the ASEAN Federation of Endocrine Societies. It shall serve as the endocrine window between the ASEAN region and the world, featuring original papers and publishing key findings from specialists and experts of endocrinology.