[1]柴晓利 张臣 丰庆春.老年重症心脏瓣膜疾病患者术后发生低心排血量综合征危险因素分析[J].心血管病学进展,2022,(11):1043.[doi:10.16806/j.cnki.issn.1004-3934.2022.11.018]
　CHAI Xiaoli,ZHANG Chen,FENG Qingchun.Risk Factors for Low Cardiac Output Syndrome?n Elderly Patients with Severe Valvular Heart Disease After Surgery[J].Advances in Cardiovascular Diseases,2022,(11):1043.[doi:10.16806/j.cnki.issn.1004-3934.2022.11.018]
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老年重症心脏瓣膜疾病患者术后发生低心排血量综合征危险因素分析()
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《心血管病学进展》[ISSN:51-1187/R/CN:1004-3934]

卷:
期数:
2022年11期
页码:
1043
栏目:
论著
出版日期:
2022-11-25

文章信息/Info

Title:
Risk Factors for Low Cardiac Output Syndrome?n Elderly Patients with Severe Valvular Heart Disease After Surgery
作者:
柴晓利 张臣 丰庆春
(湖南省脑科医院心血管内科,湖南 长沙 410015)
Author(s):
CHAI Xiaoli; ZHANG Chen; FENG Qingchun
Department of Cardiology,Hunan Brain Hospital,Changsha 410015,Hunan,China)
关键词:
老年重症心脏瓣膜疾病; 低心排血量综合征; 危险因素
Keywords:
Elderly severe valvular heart disease; Low cardiac output syndrome; Risk factors
DOI:
10.16806/j.cnki.issn.1004-3934.2022.11.018
摘要:
目的 探讨老年重症心脏瓣膜疾病患者术后发生低心排血量综合征（LCOS）的相关危险因素。方法 选取2015年7月—2022年1月于湖南省脑科医院行心脏瓣膜手术的重症心脏瓣膜疾病患者251例作为研究对象，采用计算机产生随机数法以2∶1的比例分为训练集（167例）和测试集（84例），对患者进行心脏瓣膜置换术，依据训练集患者术后是否发生LCOS将其分为LCOS组（n＝45）和非LCOS组（n＝122）。采用单因素分析和多因素逻辑回归分析对两组患者的临床资料进行统计分析。根据多因素分析结果利用R 3.6.0软件建立模型，并采用受试者操作特征（ROC）曲线、一致性指数（consistency index,CI）以及CNN对预测模型进行验证。结果 术后45例患者发生LCOS，单因素和多因素 逻辑回归分析表明：患者年龄、术前纽约心功能分级Ⅳ级、体外循环时间和失血比是术后发生LCOS的独立危险因素。根据多因素分析结果构建列线图预测模型并对模型进行验证，训练集列线图模型的ROC曲线下面积（AUC）为0.743（95% CI 0.692～0.817） ，测试集的AUC为0.712（95% CI 0.684～0.823），模型的区分度良好；训练集的 CI为0.736（95% CI 0.683～0.865），测试集 CI为0.745（95% CI 0.640～0.812）， CNN显示在300个周期后错误率逐渐稳定，模型准确性良好，预测能力较强。结论 老年重症患者的脏器功能处于代偿边缘，属高危人群，为降低老年重症患者心脏瓣膜手术后出现LCOS的概率，术前准备充分，尽量缩短外循环时间和主动脉阻断时间，减少术中出血量，加强心肌保护等措施十分必要。
Abstract:
Objective To explore the risk factors of low cardiac output syndrome(LCOS) in elderly patients with severe valvular heart disease after surgery. Methods A total of 251 patients with severe heart valve disease who underwent heart valve surgery in our hospital from July 2015 to January 2022 were selected as the research objects. The computer-generated random number method was used to divide them into training set(167 cases) and test set(84 cases) in the ratio of 2:1. According to whether the patients in the training set had LCOS after operation,they were divided into LCOS group(n＝45) and non-LCOS group (n＝122). The clinical data of the two groups were statistically analyzed by univariate analysis and multivariate logistic regression analysis. According to the results of multivariate analysis,the model was established by R 3.6.0 software,and the prediction model was verified by receiver operating characteristic curve,consistency index (c-index) and CNN. Results 45 patients developed LCOS after operation. Univariate and multivariate logistic regression analysis showed that age,preoperative New York Heart function assessment grade Ⅳ,cardiopulmonary bypass time and blood loss ratio were independent risk factors for LCOS after operation. According to the results of multi-factor analysis,the nomograph prediction model was constructed and verified. The area under curve(AUC) of the nomograph model in the training set was 0.743(95% CI 0.692～0.817),and the AUC of the test set was 0.712( 95% CI 0.684～0.823). The discrimination of the model was good . The consistency index(c-index) value of the training set was 0.736( 95% CI 0.683～0.865),and the c-index value of the test set was 0.745( 95% CI 0.640～0.812). CNN showed that the error rate gradually stabilizes after 300 cycles. The model has good accuracy and strong prediction ability. Conclusion The organ function of elderly critically ill patients is at the edge of compensation and is a high-risk group. In order to reduce the probability of LCOS after cardiac valve surgery in elderly critically ill patients,adequate preoperative preparations should be made to shorten the time of external circulation and aortic occlusion as much as possible to reduce surgery. It is very necessary to strengthen myocardial protection and other measures in the amount of bleeding.

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更新日期/Last Update: 2023-01-31