K Inoue1, M Inoue, M Matsumoto, K Akimoto. 1. Department of Community Medicine, Chiba Medical Center, Teikyo University School of Medicine, Chiba, Japan.
Abstract
AIMS: We investigated the value of persistent fasting hyperglycaemia as assessed by repeated elevated fasting plasma glucose in predicting the progression to diabetes. METHODS: A retrospective cohort study was conducted from 1998 to 2006 inclusive among 7929 persons (37,742 person-years), with a mean age of 53.0 years at baseline. The cumulative incidence of diabetes was measured. A baseline and follow-up fasting plasma glucose were categorized as normal fasting glucose (< 5.56 mmol/l), or impaired fasting glucose (5.56-6.94 mmol/l). RESULTS: The cumulative incidence and incidence density of diabetes were 3.5% (275 cases) and 7.3 per 1000 person-years over a mean follow-up period of 4.8 years. The cumulative incidence of diabetes among subjects with impaired fasting glucose at both previous examinations (persistent impaired fasting glucose) was 30.4% (222/1518) compared with 0.6% (15/5063) of those with normal fasting glucose at both baseline and initial follow-up. The hazard ratios to develop diabetes, adjusted for possible confounders, was 37.10 (95% CI, 21.6-63.7) for persistent impaired fasting glucose versus persistent normal fasting glucose. Persistent impaired fasting glucose predicted diabetes at 80.7% (222/275) sensitivity and 83.1% (6358/7654) specificity, whereas first baseline impaired fasting glucose only predicted diabetes at 86.9% (239/275) sensitivity and 74.9% (5730/7654) specificity. The model using both previous fasting plasma glucose levels had a greater AUROC (area under receiver operating characteristic) than that using first baseline fasting plasma glucose only (0.92 vs. 0.88; P < 0.001). CONCLUSIONS: Repeated measurements of fasting plasma glucose better predicts incidence of diabetes than a single test. In particular, persistent fasting hyperglycaemia adds more substantial precision to the prediction of future diabetes than transient impaired fasting glucose. This combination is cost efficient and may be practical for early detection of high-risk individuals.
AIMS: We investigated the value of persistent fasting hyperglycaemia as assessed by repeated elevated fasting plasma glucose in predicting the progression to diabetes. METHODS: A retrospective cohort study was conducted from 1998 to 2006 inclusive among 7929 persons (37,742 person-years), with a mean age of 53.0 years at baseline. The cumulative incidence of diabetes was measured. A baseline and follow-up fasting plasma glucose were categorized as normal fasting glucose (< 5.56 mmol/l), or impaired fasting glucose (5.56-6.94 mmol/l). RESULTS: The cumulative incidence and incidence density of diabetes were 3.5% (275 cases) and 7.3 per 1000 person-years over a mean follow-up period of 4.8 years. The cumulative incidence of diabetes among subjects with impaired fasting glucose at both previous examinations (persistent impaired fasting glucose) was 30.4% (222/1518) compared with 0.6% (15/5063) of those with normal fasting glucose at both baseline and initial follow-up. The hazard ratios to develop diabetes, adjusted for possible confounders, was 37.10 (95% CI, 21.6-63.7) for persistent impaired fasting glucose versus persistent normal fasting glucose. Persistent impaired fasting glucose predicted diabetes at 80.7% (222/275) sensitivity and 83.1% (6358/7654) specificity, whereas first baseline impaired fasting glucose only predicted diabetes at 86.9% (239/275) sensitivity and 74.9% (5730/7654) specificity. The model using both previous fasting plasma glucose levels had a greater AUROC (area under receiver operating characteristic) than that using first baseline fasting plasma glucose only (0.92 vs. 0.88; P < 0.001). CONCLUSIONS: Repeated measurements of fasting plasma glucose better predicts incidence of diabetes than a single test. In particular, persistent fasting hyperglycaemia adds more substantial precision to the prediction of future diabetes than transient impaired fasting glucose. This combination is cost efficient and may be practical for early detection of high-risk individuals.
Authors: Mike Sampson; Tim Elwell-Sutton; Max O Bachmann; Allan Clark; Ketan K Dhatariya; Clare Ferns; Amanda Howe; W Garry John; Gerry Rayman; Leyla Swafe; Jeremy Turner; Melanie Pascale Journal: Sci Rep Date: 2018-04-19 Impact factor: 4.379