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Nomgram model for individual prediction of coronary heart disease with pulmonary hypertension / 公共卫生与预防医学
Article en Zh | WPRIM | ID: wpr-1005913
Biblioteca responsable: WPRO
ABSTRACT
Objective To establish an individual Nomgram model for predicting the risk of coronary heart disease complicated with pulmonary hypertension. Methods From January 2017 to December 2021 , 352 patients with coronary heart disease (CHD) complicated with pulmonary hypertension in our hospital were selected, and 352 patients with coronary heart disease but without pulmonary hypertension were selected as the control group. The clinical baseline data of the two groups were analyzed first, and then logistics multivariate analysis was performed. To explore the risk factors of coronary heart disease complicated with pulmonary hypertension, the Nomgram model was established to predict the risk, and the predictive value of the model was tested by receiver characteristic curve (ROC). Results Logistics multivariate analysis showed that alcoholism, smoking, stroke history, hypertension course, CHD course, PASP, HCT, PaCO2, D-dimer, NIHSS score and low PaO2 were all independent risk factors for CHD complicated with pulmonary hypertension. Nomgram model prediction results for patients with coronary heart disease showed that Alcohol abuse, smoking, stroke history, duration of hypertension (5.66 years), duration of coronary heart disease (2.12 years), NIHSS (12.33 points), PASP (75.22mmHg), HCT (33.22%), PaCO2 (56.11mmHg), D-dimer (255.12μg/L), PaO2 (56.22mmHg) is a risk factor for coronary heart disease complicated with pulmonary hypertension. ROC curve showed that the area under the prediction curve of Nomgram model for coronary heart disease complicated with pulmonary hypertension was 0.675. Conclusion Nomgram model can predict pulmonary hypertension in patients with coronary heart disease to a certain extent.
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Índice: WPRIM Idioma: Zh Revista: Journal of Public Health and Preventive Medicine Año: 2024 Tipo del documento: Article
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Índice: WPRIM Idioma: Zh Revista: Journal of Public Health and Preventive Medicine Año: 2024 Tipo del documento: Article