Jie He, Baoqi Fan, Eric S H Lau, Natural Chu, Noel Yat Hey Ng, Kathy Ho Ting Leung, Emily W M Poon, Alice Pik Shan Kong, Ronald Ching Wan Ma, Andrea O Y Luk, Juliana C N Chan, Elaine Chow
{"title":"使用包含常规肾脏生化指标的扩展无创风险评分,加强对糖耐量异常的预测。","authors":"Jie He, Baoqi Fan, Eric S H Lau, Natural Chu, Noel Yat Hey Ng, Kathy Ho Ting Leung, Emily W M Poon, Alice Pik Shan Kong, Ronald Ching Wan Ma, Andrea O Y Luk, Juliana C N Chan, Elaine Chow","doi":"10.1136/bmjdrc-2023-003768","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Type 2 diabetes is preventable in subjects with impaired glucose tolerance based on 2-hour plasma glucose (2hPG) during 75 g oral glucose tolerance test (OGTT). We incorporated routine biochemistry to improve the performance of a non-invasive diabetes risk score to identify individuals with abnormal glucose tolerance (AGT) defined by 2hPG≥7.8 mmol/L during OGTT.</p><p><strong>Research design and methods: </strong>We used baseline data of 1938 individuals from the community-based \"Better Health for Better Hong Kong - Hong Kong Family Diabetes Study (BHBHK-HKFDS) Cohort\" recruited in 1998-2003. We incorporated routine biochemistry in a validated non-invasive diabetes risk score, and evaluated its performance using area under receiver operating characteristics (AUROC) with internal and external validation.</p><p><strong>Results: </strong>The AUROC of the original non-invasive risk score to predict AGT was 0.698 (95% CI, 0.662 to 0.733). Following additional inclusion of fasting plasma glucose, serum potassium, creatinine, and urea, the AUROC increased to 0.778 (95% CI, 0.744 to 0.809, p<0.001). Net reclassification improved by 31.9% (p<0.001) overall, by 30.8% among people with AGT and 1.1% among people without AGT. The extended model showed good calibration (χ<sup>2</sup>=11.315, p=0.1845) and performance on external validation using an independent data set (AUROC=0.722, 95% CI, 0.680 to 0.764).</p><p><strong>Conclusions: </strong>The extended risk score incorporating clinical and routine biochemistry can be integrated into an electronic health records system to select high-risk subjects for evaluation of AGT using OGTT for prevention of diabetes.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":"12 1","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10882282/pdf/","citationCount":"0","resultStr":"{\"title\":\"Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry.\",\"authors\":\"Jie He, Baoqi Fan, Eric S H Lau, Natural Chu, Noel Yat Hey Ng, Kathy Ho Ting Leung, Emily W M Poon, Alice Pik Shan Kong, Ronald Ching Wan Ma, Andrea O Y Luk, Juliana C N Chan, Elaine Chow\",\"doi\":\"10.1136/bmjdrc-2023-003768\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Type 2 diabetes is preventable in subjects with impaired glucose tolerance based on 2-hour plasma glucose (2hPG) during 75 g oral glucose tolerance test (OGTT). We incorporated routine biochemistry to improve the performance of a non-invasive diabetes risk score to identify individuals with abnormal glucose tolerance (AGT) defined by 2hPG≥7.8 mmol/L during OGTT.</p><p><strong>Research design and methods: </strong>We used baseline data of 1938 individuals from the community-based \\\"Better Health for Better Hong Kong - Hong Kong Family Diabetes Study (BHBHK-HKFDS) Cohort\\\" recruited in 1998-2003. We incorporated routine biochemistry in a validated non-invasive diabetes risk score, and evaluated its performance using area under receiver operating characteristics (AUROC) with internal and external validation.</p><p><strong>Results: </strong>The AUROC of the original non-invasive risk score to predict AGT was 0.698 (95% CI, 0.662 to 0.733). Following additional inclusion of fasting plasma glucose, serum potassium, creatinine, and urea, the AUROC increased to 0.778 (95% CI, 0.744 to 0.809, p<0.001). 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Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry.
Introduction: Type 2 diabetes is preventable in subjects with impaired glucose tolerance based on 2-hour plasma glucose (2hPG) during 75 g oral glucose tolerance test (OGTT). We incorporated routine biochemistry to improve the performance of a non-invasive diabetes risk score to identify individuals with abnormal glucose tolerance (AGT) defined by 2hPG≥7.8 mmol/L during OGTT.
Research design and methods: We used baseline data of 1938 individuals from the community-based "Better Health for Better Hong Kong - Hong Kong Family Diabetes Study (BHBHK-HKFDS) Cohort" recruited in 1998-2003. We incorporated routine biochemistry in a validated non-invasive diabetes risk score, and evaluated its performance using area under receiver operating characteristics (AUROC) with internal and external validation.
Results: The AUROC of the original non-invasive risk score to predict AGT was 0.698 (95% CI, 0.662 to 0.733). Following additional inclusion of fasting plasma glucose, serum potassium, creatinine, and urea, the AUROC increased to 0.778 (95% CI, 0.744 to 0.809, p<0.001). Net reclassification improved by 31.9% (p<0.001) overall, by 30.8% among people with AGT and 1.1% among people without AGT. The extended model showed good calibration (χ2=11.315, p=0.1845) and performance on external validation using an independent data set (AUROC=0.722, 95% CI, 0.680 to 0.764).
Conclusions: The extended risk score incorporating clinical and routine biochemistry can be integrated into an electronic health records system to select high-risk subjects for evaluation of AGT using OGTT for prevention of diabetes.
期刊介绍:
BMJ Open Diabetes Research & Care is an open access journal committed to publishing high-quality, basic and clinical research articles regarding type 1 and type 2 diabetes, and associated complications. Only original content will be accepted, and submissions are subject to rigorous peer review to ensure the publication of
high-quality — and evidence-based — original research articles.