Evaluation of risk factors and correlation in large sample from the perspective of hypoglycemia

Chao, Guanqun; Zhu, Yimin; Chen, Liying

doi:10.1002/fsn3.2608

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…Although large abdominal circumference is harmful to physical health, a small abdominal circumference can increase the risk of hypoglycemia. A large-sample study on risk factors for hypoglycemia in patients with T2DM showed that, for every 3cm increases in abdominal circumference, the risk of hypoglycemia decreases by 7.1% [31] . An RCT showed that for every 1 cm decrease in abdominal circumference, the risk of severe hypoglycemia in older adults with T2DM increased 7% [32] .…”

Section: Discussionmentioning

confidence: 99%

Predicting Hypoglycemia in Elderly Inpatients with Type 2 Diabetes: The ADOCHBIU Model

Zhang,

Liu,

Sun

et al. 2024

Preprint

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Background Hypoglycemic 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.Methods From 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.Results The 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 2.097ཞ2.469), urinary microalbumin(OR = 0.864, 95%CI 0.798ཞ0.935), oral hypoglycemic agents (OR = 1.345, 95%CI 1.243ཞ1.452), cognitive impairment (OR = 1.226, 95%CI 1.178ཞ1.276), insulin usage (OR = 1.002, 95%CI 0.948ཞ1.060), hypertension (OR = 1.113, 95%CI 1.103ཞ1.124), blood glucose monitoring (OR = 1.909, 95%CI 1.791ཞ2.036), and abdominal circumference (OR = 2.998, 95%CI 2.972ཞ3.024). 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.Conclusions The 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 registration ChiCTR2200062277. Registered on 31 July 2022.

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Section: Discussionmentioning

confidence: 99%

Predicting Hypoglycemia in Elderly Inpatients with Type 2 Diabetes: The ADOCHBIU Model

Zhang,

Liu,

Sun

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Predicting hypoglycemia in elderly inpatients with type 2 diabetes: the ADOCHBIU model

Zhang,

Liu,

Sun

et al. 2024

Front. Endocrinol.

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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.

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Evaluation of risk factors and correlation in large sample from the perspective of hypoglycemia

Cited by 2 publications

References 19 publications

Predicting Hypoglycemia in Elderly Inpatients with Type 2 Diabetes: The ADOCHBIU Model

Predicting Hypoglycemia in Elderly Inpatients with Type 2 Diabetes: The ADOCHBIU Model

Predicting hypoglycemia in elderly inpatients with type 2 diabetes: the ADOCHBIU model

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