Heart Institute, Hillel Yaffe Medical Center, Hadera, Israel,
The Ruth and Bruce Rappaport Faculty of Medicine, Technion, Haifa, Israel,
Cardiology. 2021;146(1):49-59. doi: 10.1159/000510073. Epub 2020 Oct 28.
Prediction of readmission and death after hospitalization for heart failure (HF) is an unmet need.
We evaluated the ability of clinical parameters, NT-proBNP level and noninvasive lung impedance (LI), to predict time to readmission (TTR) and time to death (TTD).
The present study is a post hoc analysis of the IMPEDANCE-HF extended trial comprising 290 patients with LVEF ≤45% and New York Heart Association functional class II-IV, randomized 1:1 to LI-guided or conventional therapy. Of all patients, 206 were admitted 766 times for HF during a follow-up of 57 ± 39 months. The normal LI (NLI), representing the "dry" lung status, was calculated for each patient at study entry. The current degree of pulmonary congestion (PC) compared with its dry status was represented by ΔLIR = ([measured LI/NLI] - 1) × 100%. Twenty-six parameters recorded during HF admission were used to predict TTR and TTD. To determine the parameter which mainly impacted TTR and TTD, variables were standardized, and effect size (ES) was calculated. Multivariate analysis by the Andersen-Gill model demonstrated that ΔLIRadmission (ES = 0.72), ΔLIRdischarge (ES = -3.14), group assignment (ES = 0.2), maximal troponin during HF admission (ES = 0.19), LVEF related to admission (ES = -0.22) and arterial hypertension (ES = 0.12) are independent predictors of TTR (p < 0.01, χ2 = 1,206). Analysis of ES showed that residual PC assessed by ∆LIRdischarge was the most prominent predictor of TTR. One percent improvement in predischarge PC, assessed by ∆LIRdischarge, was associated with a likelihood of TTR increase by 14% (hazard ratio [HR] 1.14, 95% confidence interval [CI] 1.13-1.15, p < 0.01) and TTD increase by 8% (HR 1.08, 95% CI 1.07-1.09, p < 0.01).
The degree of predischarge PC assessed by ∆LIR is the most dominant predictor of TTR and TTD.
预测心力衰竭（HF）患者住院后的再入院和死亡是一个未满足的需求。
我们评估了临床参数、NT-proBNP 水平和无创肺阻抗（LI）预测再入院时间（TTR）和死亡时间（TTD）的能力。
本研究是 IMPEDANCE-HF 扩展试验的事后分析，该试验纳入了 290 名 LVEF≤45%和纽约心脏协会功能 II-IV 级的患者，按 1:1 随机分为 LI 指导治疗组或常规治疗组。在 57±39 个月的随访期间，所有患者中有 206 人因 HF 住院 766 次。在研究入组时，为每位患者计算了正常 LI（NLI），代表“干燥”的肺部状态。当前的肺充血程度（PC）与干燥状态的差异用ΔLIR=[（测量的 LI/NLI）-1]×100%表示。在 HF 入院期间记录的 26 个参数用于预测 TTR 和 TTD。为了确定主要影响 TTR 和 TTD 的参数，对变量进行了标准化，并计算了效应大小（ES）。通过 Andersen-Gill 模型进行的多变量分析表明，入院时的ΔLIR（ES=0.72）、出院时的ΔLIR（ES=-3.14）、分组（ES=0.2）、HF 入院时最大肌钙蛋白（ES=0.19）、与入院时相关的 LVEF（ES=-0.22）和动脉高血压（ES=0.12）是 TTR 的独立预测因子（p<0.01，χ2=1206）。ES 分析表明，出院时评估的残留 PC 通过 ΔLIRdischarge 是 TTR 的最主要预测因子。出院时 PC 改善 1%，通过ΔLIRdischarge 评估，TTR 增加的可能性增加 14%（危险比[HR]1.14，95%置信区间[CI]1.13-1.15，p<0.01）和 TTD 增加 8%（HR 1.08，95%CI 1.07-1.09，p<0.01）。
出院时通过ΔLIR 评估的 PC 程度是 TTR 和 TTD 的最主要预测因子。
