Nomogram Based on Risk Factors for Type 2 Diabetes Mellitus Patients with Coronary Heart Disease

Rong Shi, Birong Wu, Zheyun Niu, Hui Sun, Fan Hu School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of ChinaCorrespondence: Fan HuSchool of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, People’...

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Autores principales:	Shi R, Wu B, Niu Z, Sun H, Hu F
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2020
Materias:	prediction model coronary heart disease type 2 diabetes mellitus Specialties of internal medicine RC581-951
Acceso en línea:	https://doaj.org/article/b87f2f9dfc7b4da8b7285ed4fd6b12fe
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spelling	oai:doaj.org-article:b87f2f9dfc7b4da8b7285ed4fd6b12fe2021-12-02T13:58:31ZNomogram Based on Risk Factors for Type 2 Diabetes Mellitus Patients with Coronary Heart Disease1178-7007https://doaj.org/article/b87f2f9dfc7b4da8b7285ed4fd6b12fe2020-12-01T00:00:00Zhttps://www.dovepress.com/nomogram-based-on-risk-factors-for-type-2-diabetes-mellitus-patients-w-peer-reviewed-article-DMSOhttps://doaj.org/toc/1178-7007Rong Shi, Birong Wu, Zheyun Niu, Hui Sun, Fan Hu School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of ChinaCorrespondence: Fan HuSchool of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of ChinaTel/Fax +862151322466Email Joyking2003@163.comIntroduction: This study aimed to study risk factors for coronary heart disease (CHD) in type 2 diabetes mellitus (T2DM) patients and establish a clinical prediction model.Research Design and Methods: A total of 3402 T2DM patients were diagnosed by clinical doctors and recorded in the electronic medical record system (EMRS) of six Community Health Center Hospitals from 2015 to 2017, including the communities of Huamu, Jinyang, Yinhang, Siping, Sanlin and Daqiao. From September 2018 to September 2019, 3361 patients (41 patients were missing) were investigated using a questionnaire, physical examination, and biochemical index test. After excluding the uncompleted data, 3214 participants were included in the study and randomly divided into a training set (n = 2252) and a validation set (n = 962) at a ratio of 3:1. Through lead absolute shrinkage and selection operator (LASSO) regression analysis and logistic regression analysis of the training set, risk factors were determined and included in a nomogram. The C-index, receiver operating characteristic (ROC) curve, calibration plot and decision curve analysis (DCA) were used to validate the distinction, calibration and clinical practicality of the model.Results: Age, T2DM duration, hypertension (HTN), hyperuricaemia (HUA), body mass index (BMI), glycosylated haemoglobin A1c (HbA1c), high-density lipoprotein (HDL-C) and low-density lipoprotein (LDL-C) were significant factors in this study. The C-index was 0.750 (0.724– 0.776) based on the training set and 0.767 (0.726– 0.808) based on the validation set. Through ROC analysis, the set area was 0.750 for the training set and 0.755 for the validation set. The calibration test indicated that the S:P of the prediction model was 0.982 in the training set and 0.499 in the validation set. The decision curve analysis showed that the threshold probability of the model was 16– 69% in the training set and 16– 73% in the validation set.Conclusion: Based on community surveys and data analysis, a prediction model of CHD in T2DM patients was established.Keywords: prediction model, coronary heart disease, type 2 diabetes mellitusShi RWu BNiu ZSun HHu FDove Medical Pressarticleprediction modelcoronary heart diseasetype 2 diabetes mellitusSpecialties of internal medicineRC581-951ENDiabetes, Metabolic Syndrome and Obesity: Targets and Therapy, Vol Volume 13, Pp 5025-5036 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	prediction model coronary heart disease type 2 diabetes mellitus Specialties of internal medicine RC581-951
spellingShingle	prediction model coronary heart disease type 2 diabetes mellitus Specialties of internal medicine RC581-951 Shi R Wu B Niu Z Sun H Hu F Nomogram Based on Risk Factors for Type 2 Diabetes Mellitus Patients with Coronary Heart Disease
description	Rong Shi, Birong Wu, Zheyun Niu, Hui Sun, Fan Hu School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of ChinaCorrespondence: Fan HuSchool of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of ChinaTel/Fax +862151322466Email Joyking2003@163.comIntroduction: This study aimed to study risk factors for coronary heart disease (CHD) in type 2 diabetes mellitus (T2DM) patients and establish a clinical prediction model.Research Design and Methods: A total of 3402 T2DM patients were diagnosed by clinical doctors and recorded in the electronic medical record system (EMRS) of six Community Health Center Hospitals from 2015 to 2017, including the communities of Huamu, Jinyang, Yinhang, Siping, Sanlin and Daqiao. From September 2018 to September 2019, 3361 patients (41 patients were missing) were investigated using a questionnaire, physical examination, and biochemical index test. After excluding the uncompleted data, 3214 participants were included in the study and randomly divided into a training set (n = 2252) and a validation set (n = 962) at a ratio of 3:1. Through lead absolute shrinkage and selection operator (LASSO) regression analysis and logistic regression analysis of the training set, risk factors were determined and included in a nomogram. The C-index, receiver operating characteristic (ROC) curve, calibration plot and decision curve analysis (DCA) were used to validate the distinction, calibration and clinical practicality of the model.Results: Age, T2DM duration, hypertension (HTN), hyperuricaemia (HUA), body mass index (BMI), glycosylated haemoglobin A1c (HbA1c), high-density lipoprotein (HDL-C) and low-density lipoprotein (LDL-C) were significant factors in this study. The C-index was 0.750 (0.724– 0.776) based on the training set and 0.767 (0.726– 0.808) based on the validation set. Through ROC analysis, the set area was 0.750 for the training set and 0.755 for the validation set. The calibration test indicated that the S:P of the prediction model was 0.982 in the training set and 0.499 in the validation set. The decision curve analysis showed that the threshold probability of the model was 16– 69% in the training set and 16– 73% in the validation set.Conclusion: Based on community surveys and data analysis, a prediction model of CHD in T2DM patients was established.Keywords: prediction model, coronary heart disease, type 2 diabetes mellitus
format	article
author	Shi R Wu B Niu Z Sun H Hu F
author_facet	Shi R Wu B Niu Z Sun H Hu F
author_sort	Shi R
title	Nomogram Based on Risk Factors for Type 2 Diabetes Mellitus Patients with Coronary Heart Disease
title_short	Nomogram Based on Risk Factors for Type 2 Diabetes Mellitus Patients with Coronary Heart Disease
title_full	Nomogram Based on Risk Factors for Type 2 Diabetes Mellitus Patients with Coronary Heart Disease
title_fullStr	Nomogram Based on Risk Factors for Type 2 Diabetes Mellitus Patients with Coronary Heart Disease
title_full_unstemmed	Nomogram Based on Risk Factors for Type 2 Diabetes Mellitus Patients with Coronary Heart Disease
title_sort	nomogram based on risk factors for type 2 diabetes mellitus patients with coronary heart disease
publisher	Dove Medical Press
publishDate	2020
url	https://doaj.org/article/b87f2f9dfc7b4da8b7285ed4fd6b12fe
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_version_	1718392223594184704

Nomogram Based on Risk Factors for Type 2 Diabetes Mellitus Patients with Coronary Heart Disease

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