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: |
| Summary: | 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. |
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| ISSN: | 2765-1606 2765-1614 |