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Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations
Most studies on the prediction of venous thromboembolism (VTE) focused on hospitalized, surgery, and cancer patients or women receiving hormonal contraceptives or menopausal hormone therapy. No study considered diabetic and general populations to establish a VTE prediction model, especially in Asia....
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8483831/ https://www.ncbi.nlm.nih.gov/pubmed/34596150 http://dx.doi.org/10.1097/MD.0000000000027367 |
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author | Lin, Cheng-Chieh Chen, Ching-Chu Li, Chia-Ing Liu, Chiu-Shong Lin, Wen-Yuan Lin, Chih-Hsueh Yang, Shing-Yu Li, Tsai-Chung |
author_facet | Lin, Cheng-Chieh Chen, Ching-Chu Li, Chia-Ing Liu, Chiu-Shong Lin, Wen-Yuan Lin, Chih-Hsueh Yang, Shing-Yu Li, Tsai-Chung |
author_sort | Lin, Cheng-Chieh |
collection | PubMed |
description | Most studies on the prediction of venous thromboembolism (VTE) focused on hospitalized, surgery, and cancer patients or women receiving hormonal contraceptives or menopausal hormone therapy. No study considered diabetic and general populations to establish a VTE prediction model, especially in Asia. We developed a predictive model for VTE among type 2 diabetic patients and the general population. This study considered 2 nationwide retrospective cohort studies consisting of 52,427 diabetic participants and 508,664 participants from the general population aged 30 to 85 years during 2001 to 2004 in Taiwan. All participants were followed up until VTE event, death, or December 2011. The outcome event was VTE, including deep venous thrombosis and pulmonary embolism. Candidate predictors consisted of socio-demographic factors, diabetes-related factors and biomarkers, comorbidities, and medicine use. Our study followed the procedures proposed by the Framingham Heart Study to develop prediction models by using a Cox regression model. The predictive accuracy and performance characteristics were assessed using the area under curve of receiver operating characteristics curve and calibration of a risk score were performed by Hosmer–Lemeshow goodness-of-fit test. The common factors for persons with type 2 diabetes and general population included age, hospitalization status 1 year before the baseline, hypertension, chronic kidney disease, chronic obstructive pulmonary disease, and anti-diabetes medications; the specific factors for persons with type 2 diabetes consisted of body mass index, glycosylated hemoglobin A1C, and creatinine; and the factors for general population included gender, peripheral vascular disease, cancer, hypertension medication, cardiovascular medication, and non-steroidal anti-inflammatory drug. The area under curve of 3-, 5-, and 8-year VTE prediction models were 0.74, 0.71, and 0.69 in the diabetic population and 0.77, 0.76, and 0.75 in the general population, respectively. The new clinical prediction models can help identify a high risk of VTE and provide medical intervention in diabetic and general populations. |
format | Online Article Text |
id | pubmed-8483831 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-84838312021-10-04 Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations Lin, Cheng-Chieh Chen, Ching-Chu Li, Chia-Ing Liu, Chiu-Shong Lin, Wen-Yuan Lin, Chih-Hsueh Yang, Shing-Yu Li, Tsai-Chung Medicine (Baltimore) 4400 Most studies on the prediction of venous thromboembolism (VTE) focused on hospitalized, surgery, and cancer patients or women receiving hormonal contraceptives or menopausal hormone therapy. No study considered diabetic and general populations to establish a VTE prediction model, especially in Asia. We developed a predictive model for VTE among type 2 diabetic patients and the general population. This study considered 2 nationwide retrospective cohort studies consisting of 52,427 diabetic participants and 508,664 participants from the general population aged 30 to 85 years during 2001 to 2004 in Taiwan. All participants were followed up until VTE event, death, or December 2011. The outcome event was VTE, including deep venous thrombosis and pulmonary embolism. Candidate predictors consisted of socio-demographic factors, diabetes-related factors and biomarkers, comorbidities, and medicine use. Our study followed the procedures proposed by the Framingham Heart Study to develop prediction models by using a Cox regression model. The predictive accuracy and performance characteristics were assessed using the area under curve of receiver operating characteristics curve and calibration of a risk score were performed by Hosmer–Lemeshow goodness-of-fit test. The common factors for persons with type 2 diabetes and general population included age, hospitalization status 1 year before the baseline, hypertension, chronic kidney disease, chronic obstructive pulmonary disease, and anti-diabetes medications; the specific factors for persons with type 2 diabetes consisted of body mass index, glycosylated hemoglobin A1C, and creatinine; and the factors for general population included gender, peripheral vascular disease, cancer, hypertension medication, cardiovascular medication, and non-steroidal anti-inflammatory drug. The area under curve of 3-, 5-, and 8-year VTE prediction models were 0.74, 0.71, and 0.69 in the diabetic population and 0.77, 0.76, and 0.75 in the general population, respectively. The new clinical prediction models can help identify a high risk of VTE and provide medical intervention in diabetic and general populations. Lippincott Williams & Wilkins 2021-10-01 /pmc/articles/PMC8483831/ /pubmed/34596150 http://dx.doi.org/10.1097/MD.0000000000027367 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | 4400 Lin, Cheng-Chieh Chen, Ching-Chu Li, Chia-Ing Liu, Chiu-Shong Lin, Wen-Yuan Lin, Chih-Hsueh Yang, Shing-Yu Li, Tsai-Chung Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations |
title | Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations |
title_full | Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations |
title_fullStr | Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations |
title_full_unstemmed | Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations |
title_short | Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations |
title_sort | derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations |
topic | 4400 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8483831/ https://www.ncbi.nlm.nih.gov/pubmed/34596150 http://dx.doi.org/10.1097/MD.0000000000027367 |
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