A prediction model for 5-year cardiac mortality in patients with chronic heart failure using 123I-metaiodobenzylguanidine imaging
A prediction model for 5-year cardiac mortality in patients with chronic heart failure using 123I-metaiodobenzylguanidine imaging
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DOI：
10.1007/s00259-014-2759-x
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发表时间：
2014-09-01
影响因子：
9.1
通讯作者：
Jacobson, Arnold F.
中科院分区：
文献类型：
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作者：
Nakajima, Kenichi;Nakata, Tomoaki;Jacobson, Arnold F.
目的死亡风险的预测在慢性心力衰竭(CHF)的治疗中具有重要意义。这项研究的目的是利用日本一项多中心队列研究的数据，建立一个包括心脏交感神经支配评估在内的5年心源性死亡预测模型。方法最初的汇集数据库包括来自日本6个地点的队列研究。从该数据库中选择了933名接受I-123-间碘苯甲基胍(MIBG)显像的CHF患者，这些患者的5年预后已知。晚期MIBG心脏与纵隔的比率(HMR)用于量化心脏摄取。使用COX比例风险和Logistic回归分析来选择合适的变量来预测5年的心脏死亡率。结果5年随访期间，2 0 5例(2 2%)患者死于心脏事件，包括心力衰竭死亡、心脏性猝死和致死性急性心肌梗死(分别为30%和6%)。多因素Logistic分析选择了4个参数，包括纽约心脏协会(NYHA)功能分级、年龄、性别和左心室射血分数，没有HMR的(模型1)和有HMR的5个参数(模型2)。包括HMR在内的所有受试者的净重新分类改善分析为13.8%(p<；0.0001)，并且它的纳入在低风险患者的向下重新分类中最有效。结论心脏MIBG显像对心脏死亡率的预测具有显著的附加价值。预测公式和诺模图可用于CHF患者的危险分层。
Purpose Prediction of mortality risk is important in the management of chronic heart failure (CHF). The aim of this study was to create a prediction model for 5-year cardiac death including assessment of cardiac sympathetic innervation using data from a multicenter cohort study in Japan.Methods The original pooled database consisted of cohort studies from six sites in Japan. A total of 933 CHF patients who underwent I-123-metaiodobenzylguanidine (MIBG) imaging and whose 5-year outcomes were known were selected from this database. The late MIBG heart-to-mediastinum ratio (HMR) was used for quantification of cardiac uptake. Cox proportional hazard and logistic regression analyses were used to select appropriate variables for predicting 5-year cardiac mortality. The formula for predicting 5-year mortality was created using a logistic regression model.Results During the 5-year follow-up, 205 patients (22 %) died of a cardiac event including heart failure death, sudden cardiac death and fatal acute myocardial infarction (64 %, 30 % and 6 %, respectively). Multivariate logistic analysis selected four parameters, including New York Heart Association (NYHA) functional class, age, gender and left ventricular ejection fraction, without HMR (model 1) and five parameters with the addition of HMR (model 2). The net reclassification improvement analysis for all subjects was 13.8 % (p < 0.0001) by including HMR and its inclusion was most effective in the downward reclassification of low-risk patients. Nomograms for predicting 5-year cardiac mortality were created from the five-parameter regression model.Conclusion Cardiac MIBG imaging had a significant additive value for predicting cardiac mortality. The prediction formula and nomograms can be used for risk stratifying in patients with CHF.