Transthoracic Echocardiography-Based Prediction Model of Adverse Event Risk in Patients with COVID-19
Cardiopulmonary disorders cause a significant increase in the risk of adverse events in patients with COVID-19. Therefore, the development of new diagnostic and treatment methods for comorbid disorders in COVID-19 patients is one of the main public health challenges. The aim of the study was to anal...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-04-01
|
| Series: | Pathophysiology |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1873-149X/29/2/14 |
| _version_ | 1797483466129932288 |
|---|---|
| author | Elena Zelikovna Golukhova Inessa Viktorovna Slivneva Maxim Leonidovich Mamalyga Damir Ildarovich Marapov Mikhail Nikolaevich Alekhin Mikhail Mikhailovich Rybka Irina Vasilevna Volkovskaya |
| author_facet | Elena Zelikovna Golukhova Inessa Viktorovna Slivneva Maxim Leonidovich Mamalyga Damir Ildarovich Marapov Mikhail Nikolaevich Alekhin Mikhail Mikhailovich Rybka Irina Vasilevna Volkovskaya |
| author_sort | Elena Zelikovna Golukhova |
| collection | DOAJ |
| description | Cardiopulmonary disorders cause a significant increase in the risk of adverse events in patients with COVID-19. Therefore, the development of new diagnostic and treatment methods for comorbid disorders in COVID-19 patients is one of the main public health challenges. The aim of the study was to analyze patient survival and to develop a predictive model of survival in adults with COVID-19 infection based on transthoracic echocardiography (TTE) parameters. We conducted a prospective, single-center, temporary hospital-based study of 110 patients with moderate to severe COVID-19. All patients underwent TTE evaluation. The predictors of mortality we identified in univariate and multivariable models and the predictive performance of the model were assessed using receiver operating characteristic (ROC) analysis and area under the curve (AUC). The predictive model included three factors: right ventricle (RV)/left ventricle (LV) area (odds ratio (OR) = 1.048 per 1/100 increase, <i>p</i> = 0.03), systolic pulmonary artery pressure (sPAP) (OR = 1.209 per 1 mm Hg increase, <i>p</i> < 0.001), and right ventricle free wall longitudinal strain (RV FW LS) (OR = 0.873 per 1% increase, <i>p</i> = 0.036). The AUC-ROC of the obtained model was 0.925 ± 0.031 (95% confidence interval (95% CI): 0.863–0.986). The sensitivity (Se) and specificity (Sp) measures of the models at the cut-off point of 0.129 were 93.8% and 81.9%, respectively. A binary logistic regression method resulted in the development of a prognostic model of mortality in patients with moderate and severe COVID-19 based on TTE data. It may also have additional implications for early risk stratification and clinical decision making in patients with COVID-19. |
| first_indexed | 2024-03-09T22:48:23Z |
| format | Article |
| id | doaj.art-5f5e9cd8826541aa9361b72a958d51d4 |
| institution | Directory Open Access Journal |
| issn | 1873-149X |
| language | English |
| last_indexed | 2024-03-09T22:48:23Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Pathophysiology |
| spelling | doaj.art-5f5e9cd8826541aa9361b72a958d51d42023-11-23T18:25:42ZengMDPI AGPathophysiology1873-149X2022-04-0129215717210.3390/pathophysiology29020014Transthoracic Echocardiography-Based Prediction Model of Adverse Event Risk in Patients with COVID-19Elena Zelikovna Golukhova0Inessa Viktorovna Slivneva1Maxim Leonidovich Mamalyga2Damir Ildarovich Marapov3Mikhail Nikolaevich Alekhin4Mikhail Mikhailovich Rybka5Irina Vasilevna Volkovskaya6A.N. Bakulev National Medical Scientific Center for Cardiovascular Surgery, Ministry of Health of the Russian Federation, 121552 Moscow, RussiaDepartment of Emergency Ultrasound and Functional Diagnostics, A.N. Bakulev National Medical Scientific Center for Cardiovascular Surgery, Ministry of Health of the Russian Federation, 121552 Moscow, RussiaDepartment of Surgical Treatment of Coronary Heart Disease, A.N. Bakulev National Medical Research Center for Cardiovascular Surgery, Ministry of Health of the Russian Federation, 121552 Moscow, RussiaDepartment of Public Health, Economics and Health Care Management, Kazan State Medical Academy—Branch Campus of the Federal State Budgetary Educational Institution of Further Professional Education «Russian Medical Academy of Continuous Professional Education» of the Ministry of Healthcare of the Russian Federation, 420012 Kazan, RussiaFunctional Diagnostics Department of the Central Clinical Hospital with Polyclinic of the Russian Presidential Administration, 121359 Moscow, RussiaDepartment of Anesthesiology and Intensive Care, A.N. Bakulev National Medical Scientific Center for Cardiovascular Surgery, Ministry of Health of the Russian Federation, 121552 Moscow, RussiaPolyclinic Department of the Institute of Coronary and Vascular Surgery, A.N. Bakulev National Medical Scientific Center for Cardiovascular Surgery, Ministry of Health of the Russian Federation, 121552 Moscow, RussiaCardiopulmonary disorders cause a significant increase in the risk of adverse events in patients with COVID-19. Therefore, the development of new diagnostic and treatment methods for comorbid disorders in COVID-19 patients is one of the main public health challenges. The aim of the study was to analyze patient survival and to develop a predictive model of survival in adults with COVID-19 infection based on transthoracic echocardiography (TTE) parameters. We conducted a prospective, single-center, temporary hospital-based study of 110 patients with moderate to severe COVID-19. All patients underwent TTE evaluation. The predictors of mortality we identified in univariate and multivariable models and the predictive performance of the model were assessed using receiver operating characteristic (ROC) analysis and area under the curve (AUC). The predictive model included three factors: right ventricle (RV)/left ventricle (LV) area (odds ratio (OR) = 1.048 per 1/100 increase, <i>p</i> = 0.03), systolic pulmonary artery pressure (sPAP) (OR = 1.209 per 1 mm Hg increase, <i>p</i> < 0.001), and right ventricle free wall longitudinal strain (RV FW LS) (OR = 0.873 per 1% increase, <i>p</i> = 0.036). The AUC-ROC of the obtained model was 0.925 ± 0.031 (95% confidence interval (95% CI): 0.863–0.986). The sensitivity (Se) and specificity (Sp) measures of the models at the cut-off point of 0.129 were 93.8% and 81.9%, respectively. A binary logistic regression method resulted in the development of a prognostic model of mortality in patients with moderate and severe COVID-19 based on TTE data. It may also have additional implications for early risk stratification and clinical decision making in patients with COVID-19.https://www.mdpi.com/1873-149X/29/2/14COVID-19TTEtransthoracic echocardiographypredictive modelmultivariable modelright ventricle free wall longitudinal strain |
| spellingShingle | Elena Zelikovna Golukhova Inessa Viktorovna Slivneva Maxim Leonidovich Mamalyga Damir Ildarovich Marapov Mikhail Nikolaevich Alekhin Mikhail Mikhailovich Rybka Irina Vasilevna Volkovskaya Transthoracic Echocardiography-Based Prediction Model of Adverse Event Risk in Patients with COVID-19 Pathophysiology COVID-19 TTE transthoracic echocardiography predictive model multivariable model right ventricle free wall longitudinal strain |
| title | Transthoracic Echocardiography-Based Prediction Model of Adverse Event Risk in Patients with COVID-19 |
| title_full | Transthoracic Echocardiography-Based Prediction Model of Adverse Event Risk in Patients with COVID-19 |
| title_fullStr | Transthoracic Echocardiography-Based Prediction Model of Adverse Event Risk in Patients with COVID-19 |
| title_full_unstemmed | Transthoracic Echocardiography-Based Prediction Model of Adverse Event Risk in Patients with COVID-19 |
| title_short | Transthoracic Echocardiography-Based Prediction Model of Adverse Event Risk in Patients with COVID-19 |
| title_sort | transthoracic echocardiography based prediction model of adverse event risk in patients with covid 19 |
| topic | COVID-19 TTE transthoracic echocardiography predictive model multivariable model right ventricle free wall longitudinal strain |
| url | https://www.mdpi.com/1873-149X/29/2/14 |
| work_keys_str_mv | AT elenazelikovnagolukhova transthoracicechocardiographybasedpredictionmodelofadverseeventriskinpatientswithcovid19 AT inessaviktorovnaslivneva transthoracicechocardiographybasedpredictionmodelofadverseeventriskinpatientswithcovid19 AT maximleonidovichmamalyga transthoracicechocardiographybasedpredictionmodelofadverseeventriskinpatientswithcovid19 AT damirildarovichmarapov transthoracicechocardiographybasedpredictionmodelofadverseeventriskinpatientswithcovid19 AT mikhailnikolaevichalekhin transthoracicechocardiographybasedpredictionmodelofadverseeventriskinpatientswithcovid19 AT mikhailmikhailovichrybka transthoracicechocardiographybasedpredictionmodelofadverseeventriskinpatientswithcovid19 AT irinavasilevnavolkovskaya transthoracicechocardiographybasedpredictionmodelofadverseeventriskinpatientswithcovid19 |