Predicting hypoglycemia in elderly inpatients with type 2 diabetes: the ADOCHBIU model
BackgroundHypoglycemic episodes cause varying degrees of damage in the functional system of elderly inpatients with type 2 diabetes mellitus (T2DM). The purpose of the study is to construct a nomogram prediction model for the risk of hypoglycemia in elderly inpatients with T2DM and to evaluate the p...
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2024.1366184/full |
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| author | Rui-Ting Zhang Yu Liu Chao Sun Quan-Ying Wu Hong Guo Gong-Ming Wang Ke-Ke Lin Jing Wang Xiao-Yan Bai |
| author_facet | Rui-Ting Zhang Yu Liu Chao Sun Quan-Ying Wu Hong Guo Gong-Ming Wang Ke-Ke Lin Jing Wang Xiao-Yan Bai |
| author_sort | Rui-Ting Zhang |
| collection | DOAJ |
| description | BackgroundHypoglycemic episodes cause varying degrees of damage in the functional system of elderly inpatients with type 2 diabetes mellitus (T2DM). The purpose of the study is to construct a nomogram prediction model for the risk of hypoglycemia in elderly inpatients with T2DM and to evaluate the predictive performance of the model.MethodsFrom August 2022 to April 2023, 546 elderly inpatients with T2DM were recruited in seven tertiary-level general hospitals in Beijing and Inner Mongolia province, China. Medical history and clinical data of the inpatients were collected with a self-designed questionnaire, with follow up on the occurrence of hypoglycemia within one week. Factors related to the occurrence of hypoglycemia were screened using regularized logistic analysis(r-LR), and a nomogram prediction visual model of hypoglycemia was constructed. AUROC, Hosmer-Lemeshow, and DCA were used to analyze the prediction performance of the model.ResultsThe incidence of hypoglycemia of elderly inpatients with T2DM was 41.21% (225/546). The risk prediction model included 8 predictors as follows(named ADOCHBIU): duration of diabetes (OR=2.276, 95%CI 2.097˜2.469), urinary microalbumin(OR=0.864, 95%CI 0.798˜0.935), oral hypoglycemic agents (OR=1.345, 95%CI 1.243˜1.452), cognitive impairment (OR=1.226, 95%CI 1.178˜1.276), insulin usage (OR=1.002, 95%CI 0.948˜1.060), hypertension (OR=1.113, 95%CI 1.103˜1.124), blood glucose monitoring (OR=1.909, 95%CI 1.791˜2.036), and abdominal circumference (OR=2.998, 95%CI 2.972˜3.024). The AUROC of the prediction model was 0.871, with sensitivity of 0.889 and specificity of 0.737, which indicated that the nomogram model has good discrimination. The Hosmer-Lemeshow was χ2 = 2.147 (P=0.75), which meant that the prediction model is well calibrated. DCA curve is consistently higher than all the positive line and all the negative line, which indicated that the nomogram prediction model has good clinical utility.ConclusionsThe nomogram hypoglycemia prediction model constructed in this study had good prediction effect. It is used for early detection of high-risk individuals with hypoglycemia in elderly inpatients with T2DM, so as to take targeted measures to prevent hypoglycemia.Trial registrationChiCTR2200062277. Registered on 31 July 2022. |
| format | Article |
| id | doaj-art-33aa1945f0654f1f9c352c9d61d3ba68 |
| institution | Kabale University |
| issn | 1664-2392 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Endocrinology |
| spelling | doaj-art-33aa1945f0654f1f9c352c9d61d3ba682024-11-14T04:40:08ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922024-11-011510.3389/fendo.2024.13661841366184Predicting hypoglycemia in elderly inpatients with type 2 diabetes: the ADOCHBIU modelRui-Ting Zhang0Yu Liu1Chao Sun2Quan-Ying Wu3Hong Guo4Gong-Ming Wang5Ke-Ke Lin6Jing Wang7Xiao-Yan Bai8School of Nursing, Beijing University of Chinese Medicine, Beijing, ChinaSchool of Nursing, Beijing University of Chinese Medicine, Beijing, ChinaNursing Department, Beijing Hospital, Beijing, ChinaNursing Department, Beijing Hospital, Beijing, ChinaSchool of Nursing, Beijing University of Chinese Medicine, Beijing, ChinaNursing Department, Beijing Hospital, Beijing, ChinaSchool of Nursing, Beijing University of Chinese Medicine, Beijing, ChinaSchool of Nursing, Beijing University of Chinese Medicine, Beijing, ChinaSchool of Nursing, Beijing University of Chinese Medicine, Beijing, ChinaBackgroundHypoglycemic episodes cause varying degrees of damage in the functional system of elderly inpatients with type 2 diabetes mellitus (T2DM). The purpose of the study is to construct a nomogram prediction model for the risk of hypoglycemia in elderly inpatients with T2DM and to evaluate the predictive performance of the model.MethodsFrom August 2022 to April 2023, 546 elderly inpatients with T2DM were recruited in seven tertiary-level general hospitals in Beijing and Inner Mongolia province, China. Medical history and clinical data of the inpatients were collected with a self-designed questionnaire, with follow up on the occurrence of hypoglycemia within one week. Factors related to the occurrence of hypoglycemia were screened using regularized logistic analysis(r-LR), and a nomogram prediction visual model of hypoglycemia was constructed. AUROC, Hosmer-Lemeshow, and DCA were used to analyze the prediction performance of the model.ResultsThe incidence of hypoglycemia of elderly inpatients with T2DM was 41.21% (225/546). The risk prediction model included 8 predictors as follows(named ADOCHBIU): duration of diabetes (OR=2.276, 95%CI 2.097˜2.469), urinary microalbumin(OR=0.864, 95%CI 0.798˜0.935), oral hypoglycemic agents (OR=1.345, 95%CI 1.243˜1.452), cognitive impairment (OR=1.226, 95%CI 1.178˜1.276), insulin usage (OR=1.002, 95%CI 0.948˜1.060), hypertension (OR=1.113, 95%CI 1.103˜1.124), blood glucose monitoring (OR=1.909, 95%CI 1.791˜2.036), and abdominal circumference (OR=2.998, 95%CI 2.972˜3.024). The AUROC of the prediction model was 0.871, with sensitivity of 0.889 and specificity of 0.737, which indicated that the nomogram model has good discrimination. The Hosmer-Lemeshow was χ2 = 2.147 (P=0.75), which meant that the prediction model is well calibrated. DCA curve is consistently higher than all the positive line and all the negative line, which indicated that the nomogram prediction model has good clinical utility.ConclusionsThe nomogram hypoglycemia prediction model constructed in this study had good prediction effect. It is used for early detection of high-risk individuals with hypoglycemia in elderly inpatients with T2DM, so as to take targeted measures to prevent hypoglycemia.Trial registrationChiCTR2200062277. Registered on 31 July 2022.https://www.frontiersin.org/articles/10.3389/fendo.2024.1366184/fulltype 2 diabeteshypoglycemialogistic modelpredictionnomogram |
| spellingShingle | Rui-Ting Zhang Yu Liu Chao Sun Quan-Ying Wu Hong Guo Gong-Ming Wang Ke-Ke Lin Jing Wang Xiao-Yan Bai Predicting hypoglycemia in elderly inpatients with type 2 diabetes: the ADOCHBIU model Frontiers in Endocrinology type 2 diabetes hypoglycemia logistic model prediction nomogram |
| title | Predicting hypoglycemia in elderly inpatients with type 2 diabetes: the ADOCHBIU model |
| title_full | Predicting hypoglycemia in elderly inpatients with type 2 diabetes: the ADOCHBIU model |
| title_fullStr | Predicting hypoglycemia in elderly inpatients with type 2 diabetes: the ADOCHBIU model |
| title_full_unstemmed | Predicting hypoglycemia in elderly inpatients with type 2 diabetes: the ADOCHBIU model |
| title_short | Predicting hypoglycemia in elderly inpatients with type 2 diabetes: the ADOCHBIU model |
| title_sort | predicting hypoglycemia in elderly inpatients with type 2 diabetes the adochbiu model |
| topic | type 2 diabetes hypoglycemia logistic model prediction nomogram |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2024.1366184/full |
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