Exploration and Validation of the Performance of Hemoglobin A1c in Detecting Diabetes in CommunityDwellers With Hypertension
Annals of Laboratory Medicine
; : 457-465, 2020.
Artículo
| WPRIM (Pacífico Occidental)
| ID: wpr-830421
Biblioteca responsable:
WPRO
ABSTRACT
Background@#Diabetes can complicate hypertension management by increasing the risk of cardiovascular disease (CVD) and all-cause mortality. Studies targeting diabetes detection in hypertensive individuals demonstrating an increased risk of diabetes are lacking.We aimed to assess the performance of hemoglobin A1c (HbA1c) and its cut-off point in detecting diabetes in the abovementioned population. @*Methods@#Data from 4,096 community-dwellers with hypertension but without known diabetes were obtained from the Study on Evaluation of iNnovated Screening tools and determInation of optimal diagnostic cut-off points for type 2 diaBetes in Chinese muLti-Ethnic (SENSIBLE) study; these data were randomly split into exploration (70% of the sample) and internal validation (the remaining 30%) datasets. The optimal HbA1c cut-off point was derived from the exploration dataset and externally validated using another dataset from 2,431 hypertensive individuals. The oral glucose tolerance test was considered the goldstandard for confirming diabetes. @*Results@#The areas under the ROC curves for HbA1c to detect diabetes were 0.842, 0.832, and 0.829 for the exploration, internal validation, and external validation datasets, respectively. An optimal HbA1c cut-off point of 5.8% (40 mmol/mol) yielded a sensitivity of 76.2% and a specificity of 74.5%. Individuals who were not diagnosed as having diabetes by HbA1c at 5.8% (40 mmol/mol) had a lower 10-year CVD risk score than those diagnosed as having diabetes (P = 0.01). HbA1c ≤ 5.1% (32 mmol/mol) and ≥ 6.4% (46 mmol/mol) could indicate the absence and presence of diabetes, respectively. @*Conclusions@#HbA1c could detect diabetes effectively in community-dwellers with hypertension.
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Base de datos:
WPRIM (Pacífico Occidental)
Revista:
Annals of Laboratory Medicine
Año:
2020
Tipo del documento:
Artículo