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Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry

BMJ Supportive and Palliative Care, ISSN: 2045-4368, Vol: 12, Issue: 1
2024
  • 1
    Citations
  • 0
    Usage
  • 12
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    1
  • Captures
    12
  • Mentions
    1
    • News Mentions
      1
      • News
        1

Most Recent News

Chinese University of Hong Kong Researchers Publish New Study Findings on Diabetes Research (Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry)

2024 MAR 05 (NewsRx) -- By a News Reporter-Staff News Editor at Disease Prevention Daily -- New research on diabetes research is the subject of

Article Description

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 noninvasive 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 (χ=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.

Bibliographic Details

He, Jie; Fan, Baoqi; Lau, Eric S H; Chu, Natural; Ng, Noel Yat Hey; Leung, Kathy Ho Ting; Poon, Emily W M; Kong, Alice Pik Shan; Ma, Ronald Ching Wan; Luk, Andrea O Y; Chan, Juliana C N; Chow, Elaine

BMJ

Medicine; Nursing

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