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Combination of Body Mass Index and Fasting Blood Glucose Improved Predictive Value of New-Onset Prediabetes or Diabetes After Acute Pancreatitis: A Retrospective Cohort Study

We sought to evaluate whether combining body mass index (BMI) and fasting blood glucose (FBG) can refine the predictive value of new-onset prediabetes/diabetes after acute pancreatitis (NODAP). METHODS: In this retrospective cohort study, we used Kaplan–Meier analysis to compare differences in the N...

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Detalles Bibliográficos
Autores principales: Guo, Shao-Yan, Yang, Hai-Yun, Ning, Xiao-Yan, Guo, Wan-Wei, Chen, Xiao-Wu, Xiong, Man
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9257058/
https://www.ncbi.nlm.nih.gov/pubmed/35695791
http://dx.doi.org/10.1097/MPA.0000000000002025
Descripción
Sumario:We sought to evaluate whether combining body mass index (BMI) and fasting blood glucose (FBG) can refine the predictive value of new-onset prediabetes/diabetes after acute pancreatitis (NODAP). METHODS: In this retrospective cohort study, we used Kaplan–Meier analysis to compare differences in the NODAP rate among 492 patients with different BMI or FBG levels, or with the combination of these 2 factors mentioned above. RESULTS: In all, 153 of 492 (31.1%) eligible patients finally developed NODAP. According to univariate and multivariate analyses, BMI (hazard ratio, 2.075; 95% confidence interval, 1.408–3.060; P < 0.001) and FBG (hazard ratio, 2.544; 95% confidence interval, 1.748–3.710; P < 0.001) were important predictors of the incidence of NODAP. Subsequently, we divided 492 eligible patients into 3 groups according to the median BMI and FBG values, and found that the NODAP rate in the high-risk group was significantly higher than that in the medium-risk group (P = 0.018) or the low-risk group (P < 0.001). CONCLUSIONS: Body mass index and FBG are independent predictors of NODAP. The combination of BMI and FBG can refine the prediction of NODAP and identify candidates for clinical prevention.