The multivariable prognostic models for severe complications after heart valve surgery.
The multivariable prognostic models for severe complications after heart valve surgery.
复制标题
心脏瓣膜术后严重并发症的多变量预后模型
DOI：
10.1186/s12872-021-02268-z
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发表时间：
2021-10-11
影响因子：
2.1
通讯作者：
Wu Z
中科院分区：
文献类型：
--
作者：
Liu Y;Xiao J;Duan X;Lu X;Gong X;Chen J;Xiong M;Yin S;Guo X;Wu Z
为预测心脏瓣膜手术后严重并发症，包括低心排综合征(LCOS)、急性肾损伤血液透析(AKI-Rh)和多器官功能障碍综合征(MODS)提供多变量预后模型。我们以中山大学附属第一医院2014年1月至2015年12月930例心脏瓣膜手术患者为研究对象，建立了预测心脏瓣膜手术严重并发症的多因素Logistic回归模型。验证是使用2016年1月至2017年3月同一家医院的713名患者的回顾数据集进行的。我们考虑了两种预后模型：仅利用术前危险因素建立的PRF模型和同时利用术前和术中危险因素建立的PIRF模型。模型的建立采用最小绝对收缩选择算子。我们通过接收者工作特征(ROC)曲线来评估和比较PRF和PIRF模型的区分能力。与PRF模型相比，PIRF模式选择了额外的术中因素，如辅助体外循环时间和联合三尖瓣置换。预测LCOS、AKI-Rh和MODS的PRF模型的ROC曲线下面积分别为0.565(0.466，0.664)、0.688(0.62，0.757)和0.657(0.563，0.751)。作为比较，PIRF模型预测LOS、AKI-Rh和MODS的AUC值分别为0.821(0.747，0.896)、0.78(0.717，0.843)和0.774(0.7，0.847)。加入术中因素可提高心脏瓣膜手术后严重并发症预测模型的预测能力。
To provide multivariable prognostic models for severe complications prediction after heart valve surgery, including low cardiac output syndrome (LCOS), acute kidney injury requiring hemodialysis (AKI-rH) and multiple organ dysfunction syndrome (MODS). We developed multivariate logistic regression models to predict severe complications after heart valve surgery using 930 patients collected retrospectively from the first affiliated hospital of Sun Yat-Sen University from January 2014 to December 2015. The validation was conducted using a retrospective dataset of 713 patients from the same hospital from January 2016 to March 2017. We considered two kinds of prognostic models: the PRF models which were built by using the preoperative risk factors only, and the PIRF models which were built by using both of the preoperative and intraoperative risk factors. The least absolute shrinkage selector operator was used for developing the models. We assessed and compared the discriminative abilities for both of the PRF and PIRF models via the receiver operating characteristic (ROC) curve. Compared with the PRF models, the PIRF modes selected additional intraoperative factors, such as auxiliary cardiopulmonary bypass time and combined tricuspid valve replacement. Area under the ROC curves (AUCs) of PRF models for predicting LCOS, AKI-rH and MODS are 0.565 (0.466, 0.664), 0.688 (0.62, 0.757) and 0.657 (0.563, 0.751), respectively. As a comparison, the AUCs of the PIRF models for predicting LOCS, AKI-rH and MODS are 0.821 (0.747, 0.896), 0.78 (0.717, 0.843) and 0.774 (0.7, 0.847), respectively. Adding the intraoperative factors can increase the predictive power of the prognostic models for severe complications prediction after heart valve surgery.
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影响因子：
4.6
作者：
Brown, Jeremiah R.;Kramer, Robert S.;Coca, Steven G.;Parikh, Chirag R.
通讯作者：
Parikh, Chirag R.
影响因子：
5.7
作者：
Coffey, Sean;Cairns, Benjamin J.;Iung, Bernard
通讯作者：
Iung, Bernard
影响因子：
5
作者：
Gaede, Luise;Aarberge, Lars;Moellmann, Helge
通讯作者：
Moellmann, Helge
影响因子：
4.6
作者：
HANNAN, EL;KUMAR, D;CHASSIN, MR
通讯作者：
CHASSIN, MR
DOI：
10.1016/j.jtcvs.2012.06.037
发表时间：
2013-07-01
影响因子：
6
作者：
Dhanani, Jayesh;Mullany, Daniel V.;Fraser, John F.
通讯作者：
Fraser, John F.