Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry
© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:12 |
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| Enthalten in: |
BMJ open diabetes research & care - 12(2024), 1 vom: 19. Feb. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
He, Jie [VerfasserIn] |
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| Links: |
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| Themen: |
Blood Glucose |
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| Anmerkungen: |
Date Completed 21.02.2024 Date Revised 24.02.2024 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1136/bmjdrc-2023-003768 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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) | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Glucose Tolerance Test | |
| 650 | 4 | |a Kidney Function Tests | |
| 650 | 4 | |a Prediabetic State | |
| 650 | 4 | |a Primary Prevention | |
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| 700 | 1 | |a Fan, Baoqi |e verfasserin |4 aut | |
| 700 | 1 | |a Lau, Eric S H |e verfasserin |4 aut | |
| 700 | 1 | |a Chu, Natural |e verfasserin |4 aut | |
| 700 | 1 | |a Ng, Noel Yat Hey |e verfasserin |4 aut | |
| 700 | 1 | |a Leung, Kathy Ho Ting |e verfasserin |4 aut | |
| 700 | 1 | |a Poon, Emily W M |e verfasserin |4 aut | |
| 700 | 1 | |a Kong, Alice Pik Shan |e verfasserin |4 aut | |
| 700 | 1 | |a Ma, Ronald Ching Wan |e verfasserin |4 aut | |
| 700 | 1 | |a Luk, Andrea O Y |e verfasserin |4 aut | |
| 700 | 1 | |a Chan, Juliana C N |e verfasserin |4 aut | |
| 700 | 1 | |a Chow, Elaine |e verfasserin |4 aut | |
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