Cargando…
Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study
PURPOSE: There is a scarcity of long-term prediction models for severe hypoglycemia (SH) in subjects with type 2 diabetes mellitus (T2DM). In this study, a model was developed and validated to predict the risk of SH in adult patients with T2DM. PATIENTS AND METHODS: Baseline and follow-up data from...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203120/ https://www.ncbi.nlm.nih.gov/pubmed/30425585 http://dx.doi.org/10.2147/CLEP.S169835 |
_version_ | 1783365815744069632 |
---|---|
author | Han, Kyungdo Yun, Jae-Seung Park, Yong-Moon Ahn, Yu-Bae Cho, Jae-Hyoung Cha, Seon-Ah Ko, Seung-Hyun |
author_facet | Han, Kyungdo Yun, Jae-Seung Park, Yong-Moon Ahn, Yu-Bae Cho, Jae-Hyoung Cha, Seon-Ah Ko, Seung-Hyun |
author_sort | Han, Kyungdo |
collection | PubMed |
description | PURPOSE: There is a scarcity of long-term prediction models for severe hypoglycemia (SH) in subjects with type 2 diabetes mellitus (T2DM). In this study, a model was developed and validated to predict the risk of SH in adult patients with T2DM. PATIENTS AND METHODS: Baseline and follow-up data from patients with T2DM who received health evaluations from January 1, 2009, to December 31, 2010 (n=1,676,885) were analyzed as development (n=1,173,820) and validation (n=503,065) cohorts using the National Health Insurance Database (DB) in Korea. New SH episodes were identified using ICD-10 codes. A Cox proportional hazards regression model and Cox model coefficients were used to derive a risk scoring system, and 14 predictive variables were selected. A risk score nomogram based on the risk prediction model was created to estimate the 1-year risk of SH. RESULTS: In the development cohort, a total of 5,325 (0.45%) patients experienced SH episodes during the follow-up period. After multivariable adjustment, older age, female sex, current smoker, drinking, low body mass index, lack of exercise, previous SH events, insulin or multiple oral hypoglycemic agent use, presence of hypertension or chronic kidney disease, longer duration of diabetes, low or high glucose level, and high Charlson Comorbidity Index score were found to be significant risk factors for the development of SH and were incorporated into the risk model. The concordance indices were 0.871 (95% confidence interval, 0.863–0.881) in development cohort and 0.866 (95% CI, 0.856–0.879) in the validation cohort. The calibration plot showed a nearly 45° line, which indicates that this model predicts well an absolute SH event. CONCLUSION: This 14-variable prediction model for SH events may be a useful tool to identify high-risk patients and guide prevention of SH in adult patients with T2DM. |
format | Online Article Text |
id | pubmed-6203120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-62031202018-11-13 Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study Han, Kyungdo Yun, Jae-Seung Park, Yong-Moon Ahn, Yu-Bae Cho, Jae-Hyoung Cha, Seon-Ah Ko, Seung-Hyun Clin Epidemiol Original Research PURPOSE: There is a scarcity of long-term prediction models for severe hypoglycemia (SH) in subjects with type 2 diabetes mellitus (T2DM). In this study, a model was developed and validated to predict the risk of SH in adult patients with T2DM. PATIENTS AND METHODS: Baseline and follow-up data from patients with T2DM who received health evaluations from January 1, 2009, to December 31, 2010 (n=1,676,885) were analyzed as development (n=1,173,820) and validation (n=503,065) cohorts using the National Health Insurance Database (DB) in Korea. New SH episodes were identified using ICD-10 codes. A Cox proportional hazards regression model and Cox model coefficients were used to derive a risk scoring system, and 14 predictive variables were selected. A risk score nomogram based on the risk prediction model was created to estimate the 1-year risk of SH. RESULTS: In the development cohort, a total of 5,325 (0.45%) patients experienced SH episodes during the follow-up period. After multivariable adjustment, older age, female sex, current smoker, drinking, low body mass index, lack of exercise, previous SH events, insulin or multiple oral hypoglycemic agent use, presence of hypertension or chronic kidney disease, longer duration of diabetes, low or high glucose level, and high Charlson Comorbidity Index score were found to be significant risk factors for the development of SH and were incorporated into the risk model. The concordance indices were 0.871 (95% confidence interval, 0.863–0.881) in development cohort and 0.866 (95% CI, 0.856–0.879) in the validation cohort. The calibration plot showed a nearly 45° line, which indicates that this model predicts well an absolute SH event. CONCLUSION: This 14-variable prediction model for SH events may be a useful tool to identify high-risk patients and guide prevention of SH in adult patients with T2DM. Dove Medical Press 2018-10-23 /pmc/articles/PMC6203120/ /pubmed/30425585 http://dx.doi.org/10.2147/CLEP.S169835 Text en © 2018 Han et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Han, Kyungdo Yun, Jae-Seung Park, Yong-Moon Ahn, Yu-Bae Cho, Jae-Hyoung Cha, Seon-Ah Ko, Seung-Hyun Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study |
title | Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study |
title_full | Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study |
title_fullStr | Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study |
title_full_unstemmed | Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study |
title_short | Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study |
title_sort | development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203120/ https://www.ncbi.nlm.nih.gov/pubmed/30425585 http://dx.doi.org/10.2147/CLEP.S169835 |
work_keys_str_mv | AT hankyungdo developmentandvalidationofariskpredictionmodelforseverehypoglycemiainadultpatientswithtype2diabetesanationwidepopulationbasedcohortstudy AT yunjaeseung developmentandvalidationofariskpredictionmodelforseverehypoglycemiainadultpatientswithtype2diabetesanationwidepopulationbasedcohortstudy AT parkyongmoon developmentandvalidationofariskpredictionmodelforseverehypoglycemiainadultpatientswithtype2diabetesanationwidepopulationbasedcohortstudy AT ahnyubae developmentandvalidationofariskpredictionmodelforseverehypoglycemiainadultpatientswithtype2diabetesanationwidepopulationbasedcohortstudy AT chojaehyoung developmentandvalidationofariskpredictionmodelforseverehypoglycemiainadultpatientswithtype2diabetesanationwidepopulationbasedcohortstudy AT chaseonah developmentandvalidationofariskpredictionmodelforseverehypoglycemiainadultpatientswithtype2diabetesanationwidepopulationbasedcohortstudy AT koseunghyun developmentandvalidationofariskpredictionmodelforseverehypoglycemiainadultpatientswithtype2diabetesanationwidepopulationbasedcohortstudy |