A Risk Prediction Model for Operative Mortality after Heart Valve Surgery in a Korean Cohort
Background: This study aimed to develop a new risk prediction model for operative mortality in a Korean cohort undergoing heart valve surgery using the Korea Heart Valve Surgery Registry (KHVSR) database. Methods: We analyzed data from 4,742 patients registered in the KHVSR who underwent heart v...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Korean Society for Thoracic & Cardiovascular Surgery
2021-04-01
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| Series: | Journal of Chest Surgery |
| Subjects: |
| _version_ | 1818855719105986560 |
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| author | Ho Jin Kim Joon Bum Kim Seon-Ok Kim Sung-Cheol Yun Sak Lee Cheong Lim Jae Woong Choi Ho Young Hwang Kyung Hwan Kim Seung Hyun Lee Jae Suk Yoo Kiick Sung Hyung Gon Je Soon Chang Hong Yun Jung Kim Sung-Hyun Kim Byung-Chul Chang |
| author_facet | Ho Jin Kim Joon Bum Kim Seon-Ok Kim Sung-Cheol Yun Sak Lee Cheong Lim Jae Woong Choi Ho Young Hwang Kyung Hwan Kim Seung Hyun Lee Jae Suk Yoo Kiick Sung Hyung Gon Je Soon Chang Hong Yun Jung Kim Sung-Hyun Kim Byung-Chul Chang |
| author_sort | Ho Jin Kim |
| collection | DOAJ |
| description | Background: This study aimed to develop a new risk prediction model for operative
mortality in a Korean cohort undergoing heart valve surgery using the Korea Heart Valve
Surgery Registry (KHVSR) database.
Methods: We analyzed data from 4,742 patients registered in the KHVSR who underwent
heart valve surgery at 9 institutions between 2017 and 2018. A risk prediction model
was developed for operative mortality, defined as death within 30 days after surgery or
during the same hospitalization. A statistical model was generated with a scoring system
by multiple logistic regression analyses. The performance of the model was evaluated by
its discrimination and calibration abilities.
Results: Operative mortality occurred in 142 patients. The final regression models identified
13 risk variables. The risk prediction model showed good discrimination, with a c-statistic
of 0.805 and calibration with Hosmer-Lemeshow goodness-of-fit p-value of 0.630.
The risk scores ranged from -1 to 15, and were associated with an increase in predicted
mortality. The predicted mortality across the risk scores ranged from 0.3% to 80.6%.
Conclusion: This risk prediction model using a scoring system specific to heart valve
surgery was developed from the KHVSR database. The risk prediction model showed that
operative mortality could be predicted well in a Korean cohort. |
| first_indexed | 2024-12-19T08:13:04Z |
| format | Article |
| id | doaj.art-7ce69d7829d944a0b841db614e1a1582 |
| institution | Directory Open Access Journal |
| issn | 2765-1606 2765-1614 |
| language | English |
| last_indexed | 2024-12-19T08:13:04Z |
| publishDate | 2021-04-01 |
| publisher | Korean Society for Thoracic & Cardiovascular Surgery |
| record_format | Article |
| series | Journal of Chest Surgery |
| spelling | doaj.art-7ce69d7829d944a0b841db614e1a15822022-12-21T20:29:35ZengKorean Society for Thoracic & Cardiovascular SurgeryJournal of Chest Surgery2765-16062765-16142021-04-01542889810.5090/jcs.20.102A Risk Prediction Model for Operative Mortality after Heart Valve Surgery in a Korean CohortHo Jin Kim0https://orcid.org/0000-0002-0809-2240Joon Bum Kim1https://orcid.org/0000-0001-5801-2395Seon-Ok Kim2https://orcid.org/0000-0001-9010-5460Sung-Cheol Yun3https://orcid.org/0000-0001-8503-109XSak Lee4https://orcid.org/0000-0001-6130-2342Cheong Lim5https://orcid.org/0000-0003-0913-7014Jae Woong Choi6https://orcid.org/0000-0002-0921-756XHo Young Hwang7https://orcid.org/0000-0002-8935-8118Kyung Hwan Kim8https://orcid.org/0000-0002-2718-8758Seung Hyun Lee9https://orcid.org/0000-0002-0311-6565Jae Suk Yoo10https://orcid.org/0000-0002-7008-054XKiick Sung11https://orcid.org/0000-0003-0768-9587Hyung Gon Je12https://orcid.org/0000-0003-4713-2898Soon Chang Hong13https://orcid.org/0000-0001-6415-8243Yun Jung Kim14https://orcid.org/0000-0002-0449-1279Sung-Hyun Kim15https://orcid.org/0000-0001-9587-674XByung-Chul Chang16https://orcid.org/0000-0001-5005-8217University of Ulsan College of MedicineUniversity of Ulsan College of MedicineUniversity of Ulsan College of MedicineUniversity of Ulsan College of MedicineYonsei University College of MedicineSeoul National University College of MedicineSeoul National University College of MedicineSeoul National University College of MedicineSeoul National University College of MedicineYonsei University College of MedicineSejong General HospitalSungkyunkwan University School of MedicinePusan National University Yangsan HospitalWonju Severance Christian HospitalNational Evidence-based Healthcare Collaborating AgencyNational Evidence-based Healthcare Collaborating AgencyCHA University School of MedicineBackground: This study aimed to develop a new risk prediction model for operative mortality in a Korean cohort undergoing heart valve surgery using the Korea Heart Valve Surgery Registry (KHVSR) database. Methods: We analyzed data from 4,742 patients registered in the KHVSR who underwent heart valve surgery at 9 institutions between 2017 and 2018. A risk prediction model was developed for operative mortality, defined as death within 30 days after surgery or during the same hospitalization. A statistical model was generated with a scoring system by multiple logistic regression analyses. The performance of the model was evaluated by its discrimination and calibration abilities. Results: Operative mortality occurred in 142 patients. The final regression models identified 13 risk variables. The risk prediction model showed good discrimination, with a c-statistic of 0.805 and calibration with Hosmer-Lemeshow goodness-of-fit p-value of 0.630. The risk scores ranged from -1 to 15, and were associated with an increase in predicted mortality. The predicted mortality across the risk scores ranged from 0.3% to 80.6%. Conclusion: This risk prediction model using a scoring system specific to heart valve surgery was developed from the KHVSR database. The risk prediction model showed that operative mortality could be predicted well in a Korean cohort.risk prediction modelmortalityheart valve surgery |
| spellingShingle | Ho Jin Kim Joon Bum Kim Seon-Ok Kim Sung-Cheol Yun Sak Lee Cheong Lim Jae Woong Choi Ho Young Hwang Kyung Hwan Kim Seung Hyun Lee Jae Suk Yoo Kiick Sung Hyung Gon Je Soon Chang Hong Yun Jung Kim Sung-Hyun Kim Byung-Chul Chang A Risk Prediction Model for Operative Mortality after Heart Valve Surgery in a Korean Cohort Journal of Chest Surgery risk prediction model mortality heart valve surgery |
| title | A Risk Prediction Model for Operative Mortality after Heart Valve Surgery in a Korean Cohort |
| title_full | A Risk Prediction Model for Operative Mortality after Heart Valve Surgery in a Korean Cohort |
| title_fullStr | A Risk Prediction Model for Operative Mortality after Heart Valve Surgery in a Korean Cohort |
| title_full_unstemmed | A Risk Prediction Model for Operative Mortality after Heart Valve Surgery in a Korean Cohort |
| title_short | A Risk Prediction Model for Operative Mortality after Heart Valve Surgery in a Korean Cohort |
| title_sort | risk prediction model for operative mortality after heart valve surgery in a korean cohort |
| topic | risk prediction model mortality heart valve surgery |
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