Kim Ho Jin, Kim Joon Bum, Kim Seon-Ok, Yun Sung-Cheol, Lee Sak, Lim Cheong, Choi Jae Woong, Hwang Ho Young, Kim Kyung Hwan, Lee Seung Hyun, Yoo Jae Suk, Sung Kiick, Je Hyung Gon, Hong Soon Chang, Kim Yun Jung, Kim Sung-Hyun, Chang Byung-Chul
Department of Thoracic and Cardiovascular Surgery, Seoul, Korea.
Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
J Chest Surg. 2021 Apr 5;54(2):88-98. doi: 10.5090/jcs.20.102.
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.
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.
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%.
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.
本研究旨在利用韩国心脏瓣膜手术登记数据库（KHVSR）开发一种针对韩国接受心脏瓣膜手术队列患者手术死亡率的新型风险预测模型。
我们分析了2017年至2018年间在9家机构接受心脏瓣膜手术并登记在KHVSR中的4742例患者的数据。开发了一种针对手术死亡率的风险预测模型，手术死亡率定义为术后30天内或同一住院期间死亡。通过多元逻辑回归分析生成了一个带有评分系统的统计模型。通过其区分能力和校准能力对模型性能进行评估。
142例患者发生手术死亡。最终回归模型确定了13个风险变量。风险预测模型显示出良好的区分能力，c统计量为0.805，校准的Hosmer-Lemeshow拟合优度p值为0.630。风险评分范围为-1至15，且与预测死亡率增加相关。各风险评分的预测死亡率范围为0.3%至80.6%。
该风险预测模型是利用KHVSR数据库开发的一种针对心脏瓣膜手术的特定评分系统。该风险预测模型表明在韩国队列中可以很好地预测手术死亡率。
