Tags

Type your tag names separated by a space and hit enter

Random plasma glucose predicts the diagnosis of diabetes.
PLoS One 2019; 14(7):e0219964Plos

Abstract

AIMS/HYPOTHESIS

Early recognition of those at high risk for diabetes as well as diabetes itself can permit preventive management, but many Americans with diabetes are undiagnosed. We sought to determine whether routinely available outpatient random plasma glucose (RPG) would be useful to facilitate the diagnosis of diabetes.

METHODS

Retrospective cohort study of 942,446 U.S. Veterans without diagnosed diabetes, ≥3 RPG in a baseline year, and ≥1 primary care visit/year during 5-year follow-up. The primary outcome was incident diabetes (defined by diagnostic codes and outpatient prescription of a diabetes drug).

RESULTS

Over 5 years, 94,599 were diagnosed with diabetes [DIAB] while 847,847 were not [NONDIAB]. Baseline demographics of DIAB and NONDIAB were clinically similar, except DIAB had higher BMI (32 vs. 28 kg/m2) and RPG (150 vs. 107 mg/dl), and were more likely to have Black race (18% vs. 15%), all p<0.001. ROC area for prediction of DIAB diagnosis within 1 year by demographic factors was 0.701, and 0.708 with addition of SBP, non-HDL cholesterol, and smoking. These were significantly less than that for prediction by baseline RPG alone (≥2 RPGs at/above a given level, ROC 0.878, p<0.001), which improved slightly when other factors were added (ROC 0.900, p<0.001). Having ≥2 RPGs ≥115 mg/dl had specificity 77% and sensitivity 87%, and ≥2 RPGs ≥130 mg/dl had specificity 93% and sensitivity 59%. For predicting diagnosis within 3 and 5 years by RPG alone, ROC was reduced but remained substantial (ROC 0.839 and 0.803, respectively).

CONCLUSIONS

RPG levels below the diabetes "diagnostic" range (≥200 mg/dl) provide good discrimination for follow-up diagnosis. Use of such levels-obtained opportunistically, during outpatient visits-could signal the need for further testing, allow preventive intervention in high risk individuals before onset of disease, and lead to earlier identification of diabetes.

Authors+Show Affiliations

Atlanta VA Health Care System, Decatur, Georgia, United States of America. Department of Medicine, Division of Endocrinology and Metabolism, Emory University School of Medicine, Atlanta, Georgia, United States of America.MAVERIC VA Boston Healthcare System, Boston, Massachusetts, United States of America.VA Eastern Colorado Healthcare System, Aurora, Colorado, United States of America. Department of Medicine, Division of Hospital Medicine, University of Colorado School of Medicine, Aurora, Colorado, United States of America.MAVERIC VA Boston Healthcare System, Boston, Massachusetts, United States of America. Department of Medicine, Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America. Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America.MAVERIC VA Boston Healthcare System, Boston, Massachusetts, United States of America. Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America. Department of Medicine, Department of General Aging, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.MAVERIC VA Boston Healthcare System, Boston, Massachusetts, United States of America. Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America.Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.Atlanta VA Health Care System, Decatur, Georgia, United States of America. Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, Georgia, United States of America.Atlanta VA Health Care System, Decatur, Georgia, United States of America. Department of Medicine, Division of Endocrinology and Metabolism, Emory University School of Medicine, Atlanta, Georgia, United States of America.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31323063

Citation

Rhee, Mary K., et al. "Random Plasma Glucose Predicts the Diagnosis of Diabetes." PloS One, vol. 14, no. 7, 2019, pp. e0219964.
Rhee MK, Ho YL, Raghavan S, et al. Random plasma glucose predicts the diagnosis of diabetes. PLoS ONE. 2019;14(7):e0219964.
Rhee, M. K., Ho, Y. L., Raghavan, S., Vassy, J. L., Cho, K., Gagnon, D., ... Phillips, L. S. (2019). Random plasma glucose predicts the diagnosis of diabetes. PloS One, 14(7), pp. e0219964. doi:10.1371/journal.pone.0219964.
Rhee MK, et al. Random Plasma Glucose Predicts the Diagnosis of Diabetes. PLoS ONE. 2019;14(7):e0219964. PubMed PMID: 31323063.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Random plasma glucose predicts the diagnosis of diabetes. AU - Rhee,Mary K, AU - Ho,Yuk-Lam, AU - Raghavan,Sridharan, AU - Vassy,Jason L, AU - Cho,Kelly, AU - Gagnon,David, AU - Staimez,Lisa R, AU - Ford,Christopher N, AU - Wilson,Peter W F, AU - Phillips,Lawrence S, Y1 - 2019/07/19/ PY - 2019/01/30/received PY - 2019/07/06/accepted PY - 2019/7/20/entrez PY - 2019/7/20/pubmed PY - 2019/7/20/medline SP - e0219964 EP - e0219964 JF - PloS one JO - PLoS ONE VL - 14 IS - 7 N2 - AIMS/HYPOTHESIS: Early recognition of those at high risk for diabetes as well as diabetes itself can permit preventive management, but many Americans with diabetes are undiagnosed. We sought to determine whether routinely available outpatient random plasma glucose (RPG) would be useful to facilitate the diagnosis of diabetes. METHODS: Retrospective cohort study of 942,446 U.S. Veterans without diagnosed diabetes, ≥3 RPG in a baseline year, and ≥1 primary care visit/year during 5-year follow-up. The primary outcome was incident diabetes (defined by diagnostic codes and outpatient prescription of a diabetes drug). RESULTS: Over 5 years, 94,599 were diagnosed with diabetes [DIAB] while 847,847 were not [NONDIAB]. Baseline demographics of DIAB and NONDIAB were clinically similar, except DIAB had higher BMI (32 vs. 28 kg/m2) and RPG (150 vs. 107 mg/dl), and were more likely to have Black race (18% vs. 15%), all p<0.001. ROC area for prediction of DIAB diagnosis within 1 year by demographic factors was 0.701, and 0.708 with addition of SBP, non-HDL cholesterol, and smoking. These were significantly less than that for prediction by baseline RPG alone (≥2 RPGs at/above a given level, ROC 0.878, p<0.001), which improved slightly when other factors were added (ROC 0.900, p<0.001). Having ≥2 RPGs ≥115 mg/dl had specificity 77% and sensitivity 87%, and ≥2 RPGs ≥130 mg/dl had specificity 93% and sensitivity 59%. For predicting diagnosis within 3 and 5 years by RPG alone, ROC was reduced but remained substantial (ROC 0.839 and 0.803, respectively). CONCLUSIONS: RPG levels below the diabetes "diagnostic" range (≥200 mg/dl) provide good discrimination for follow-up diagnosis. Use of such levels-obtained opportunistically, during outpatient visits-could signal the need for further testing, allow preventive intervention in high risk individuals before onset of disease, and lead to earlier identification of diabetes. SN - 1932-6203 UR - https://www.unboundmedicine.com/medline/citation/31323063/Random_plasma_glucose_predicts_the_diagnosis_of_diabetes L2 - http://dx.plos.org/10.1371/journal.pone.0219964 DB - PRIME DP - Unbound Medicine ER -