Development and Validation of a Nomogram to Predict the Future Risk of Cardiovascular Disease
Background: Early identification of individuals at a high risk of cardiovascular disease (CVD) is crucial. This study aimed to construct a nomogram for CVD risk prediction in the general population. Methods: This retrospective study analyzed the data between January 2012 and September 2020 at the Ph...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IMR Press
2023-01-01
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| Series: | Reviews in Cardiovascular Medicine |
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| Online Access: | https://www.imrpress.com/journal/RCM/24/2/10.31083/j.rcm2402035 |
| _version_ | 1828002985178824704 |
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| author | Xuechun Shen Wei He Jinyu Sun Zuhong Zhang Qiushuang Li Haiyan Zhang Mingzhi Long |
| author_facet | Xuechun Shen Wei He Jinyu Sun Zuhong Zhang Qiushuang Li Haiyan Zhang Mingzhi Long |
| author_sort | Xuechun Shen |
| collection | DOAJ |
| description | Background: Early identification of individuals at a high risk of cardiovascular disease (CVD) is crucial. This study aimed to construct a nomogram for CVD risk prediction in the general population. Methods: This retrospective study analyzed the data between January 2012 and September 2020 at the Physical Examination Center of the Second Affiliated Hospital of Nanjing Medical University (randomized 7:3 to the training and validation cohorts). The outcome was the occurrence of CVD events, which were defined as sudden cardiac death or any death related to myocardial infarction, acute exacerbation of heart failure, or stroke. The least absolute shrinkage and selection operator (LASSO) method and multivariate logistic regression were applied to screen the significant variables related to CVD. Results: Among the 537 patients, 54 had CVD (10.1%). The median cardiac myosin-binding protein-C (cMyBP-C) level in the CVD group was higher than in the no-CVD group (42.25 pg/mL VS 25.00 pg/mL, p = 0.001). After LASSO selection and multivariable analysis, cMyBP-C (Odds ratio [OR] = 1.004, 95% CI [CI, confidence interval]: 1.000–1.008, p = 0.035), age (OR = 1.023, 95% CI: 0.999–1.048, p = 0.062), diastolic blood pressure (OR = 1.025, 95% CI: 0.995–1.058, p = 0.103), cigarettes per day (OR = 1.066, 95% CI: 1.021–1.113, p = 0.003), and family history of CVD (OR = 2.219, 95% CI: 1.003–4.893, p = 0.047) were associated with future CVD events (p < 0.200). The model, including cMyBP-C, age, diastolic blood pressure, cigarettes per day, and family history of CVD, displayed a high predictive ability with an area under the curve (AUC) of 0.816 (95% CI: 0.714–0.918) in the training cohort (specificity and negative predictive value of 0.92 and 0.96) and 0.774 (95% CI: 0.703–0.845) in the validation cohort. Conclusions: A nomogram based on cMyBP-C, age, diastolic blood pressure, cigarettes per day, and family history of CVD was constructed. The model displayed a high predictive ability. |
| first_indexed | 2024-04-10T06:52:01Z |
| format | Article |
| id | doaj.art-a7517c99a4ad4020a4ff88d891bc0ade |
| institution | Directory Open Access Journal |
| issn | 1530-6550 |
| language | English |
| last_indexed | 2024-04-10T06:52:01Z |
| publishDate | 2023-01-01 |
| publisher | IMR Press |
| record_format | Article |
| series | Reviews in Cardiovascular Medicine |
| spelling | doaj.art-a7517c99a4ad4020a4ff88d891bc0ade2023-02-28T08:09:00ZengIMR PressReviews in Cardiovascular Medicine1530-65502023-01-012423510.31083/j.rcm2402035S1530-6550(22)00782-7Development and Validation of a Nomogram to Predict the Future Risk of Cardiovascular DiseaseXuechun Shen0Wei He1Jinyu Sun2Zuhong Zhang3Qiushuang Li4Haiyan Zhang5Mingzhi Long6Department of Cardiology, The Second Affiliated Hospital of Nanjing Medical University, 210011 Nanjing, Jiangsu, ChinaDepartment of Geriatrics, The Second Affiliated Hospital of Nanjing Medical University, 210011 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The Second Affiliated Hospital of Nanjing Medical University, 210011 Nanjing, Jiangsu, ChinaDepartment of Technology, Nanjing Bottests Biotechnology Co, Ltd, 211112 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The Second Affiliated Hospital of Nanjing Medical University, 210011 Nanjing, Jiangsu, ChinaDepartment of Cardiology, The Second Affiliated Hospital of Nanjing Medical University, 210011 Nanjing, Jiangsu, ChinaBackground: Early identification of individuals at a high risk of cardiovascular disease (CVD) is crucial. This study aimed to construct a nomogram for CVD risk prediction in the general population. Methods: This retrospective study analyzed the data between January 2012 and September 2020 at the Physical Examination Center of the Second Affiliated Hospital of Nanjing Medical University (randomized 7:3 to the training and validation cohorts). The outcome was the occurrence of CVD events, which were defined as sudden cardiac death or any death related to myocardial infarction, acute exacerbation of heart failure, or stroke. The least absolute shrinkage and selection operator (LASSO) method and multivariate logistic regression were applied to screen the significant variables related to CVD. Results: Among the 537 patients, 54 had CVD (10.1%). The median cardiac myosin-binding protein-C (cMyBP-C) level in the CVD group was higher than in the no-CVD group (42.25 pg/mL VS 25.00 pg/mL, p = 0.001). After LASSO selection and multivariable analysis, cMyBP-C (Odds ratio [OR] = 1.004, 95% CI [CI, confidence interval]: 1.000–1.008, p = 0.035), age (OR = 1.023, 95% CI: 0.999–1.048, p = 0.062), diastolic blood pressure (OR = 1.025, 95% CI: 0.995–1.058, p = 0.103), cigarettes per day (OR = 1.066, 95% CI: 1.021–1.113, p = 0.003), and family history of CVD (OR = 2.219, 95% CI: 1.003–4.893, p = 0.047) were associated with future CVD events (p < 0.200). The model, including cMyBP-C, age, diastolic blood pressure, cigarettes per day, and family history of CVD, displayed a high predictive ability with an area under the curve (AUC) of 0.816 (95% CI: 0.714–0.918) in the training cohort (specificity and negative predictive value of 0.92 and 0.96) and 0.774 (95% CI: 0.703–0.845) in the validation cohort. Conclusions: A nomogram based on cMyBP-C, age, diastolic blood pressure, cigarettes per day, and family history of CVD was constructed. The model displayed a high predictive ability.https://www.imrpress.com/journal/RCM/24/2/10.31083/j.rcm2402035biomarkercardiac myosin-binding protein-ccardiovascular diseasenomogramrisk prediction |
| spellingShingle | Xuechun Shen Wei He Jinyu Sun Zuhong Zhang Qiushuang Li Haiyan Zhang Mingzhi Long Development and Validation of a Nomogram to Predict the Future Risk of Cardiovascular Disease Reviews in Cardiovascular Medicine biomarker cardiac myosin-binding protein-c cardiovascular disease nomogram risk prediction |
| title | Development and Validation of a Nomogram to Predict the Future Risk of Cardiovascular Disease |
| title_full | Development and Validation of a Nomogram to Predict the Future Risk of Cardiovascular Disease |
| title_fullStr | Development and Validation of a Nomogram to Predict the Future Risk of Cardiovascular Disease |
| title_full_unstemmed | Development and Validation of a Nomogram to Predict the Future Risk of Cardiovascular Disease |
| title_short | Development and Validation of a Nomogram to Predict the Future Risk of Cardiovascular Disease |
| title_sort | development and validation of a nomogram to predict the future risk of cardiovascular disease |
| topic | biomarker cardiac myosin-binding protein-c cardiovascular disease nomogram risk prediction |
| url | https://www.imrpress.com/journal/RCM/24/2/10.31083/j.rcm2402035 |
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