Predictive biomarkers for death and rehospitalization in comorbid frail elderly heart failure patients.
Predictive biomarkers for death and rehospitalization in comorbid frail elderly heart failure patients.
复制标题
DOI：
10.1186/s12877-018-0807-2
复制
发表时间：
2018-05-09
期刊：
影响因子：
4.1
通讯作者：
Bayes-Genis A
中科院分区：
文献类型：
--
作者：
Pacho C;Domingo M;Núñez R;Lupón J;Núñez J;Barallat J;Moliner P;de Antonio M;Santesmases J;Cediel G;Roura S;Pastor MC;Tor J;Bayes-Genis A
心力衰竭 (HF) 与出院后 30 天内和次年的高再入院率相关，尤其是体弱的老年患者。这个高危人群的生物标志物数据很少。本研究评估了出院后早期 ST2、NT-proBNP、CA125 和 hs-TnI 循环水平对于预测射血分数 (HFpEF) 合并症衰弱老年心衰患者 30 天和 1 年结果的价值。出院后不久（4.9±2 天）第一次就诊时采集了血样。主要终点是 30 天和 1 年时的全因死亡率或心衰相关再住院率的复合终点。仅一年内的全因死亡率也是一个主要终点。仅与心力衰竭相关的再住院是次要终点。从2014年2月到2016年11月，连续522名就诊于STOP-HF诊所的患者被纳入研究（57.1%为女性，年龄82±8.7岁，平均Barthel指数70±25，平均Charlson合并症指数5.6±2.2）。 8.6% 的患者在 30 天时出现复合终点，38.5% 的患者在 1 年时出现复合终点。在多变量分析中，ST2 [风险比 (HR) 1.53； 95% CI 1.19–1.97； p = 0.001] 是 30 天时唯一的预测生物标志物； 1 年时，ST2（HR 1.34；95% CI 1.15–1.56；p < 0.001）和 NT-proBNP（HR 1.19；95% CI 1.02–1.40；p = 0.03）仍然显着。将 ST2 和 NT-proBNP 添加到临床预测模型中，30 天时 AUC 从 0.70 增加到 0.75 (p = 0.02)，1 年时从 0.71 增加到 0.74 (p < 0.05)。对于 1 年全因死亡，ST2（HR 1.50；95% CI 1.26–1.80；p < 0.001）和 CA125（HR 1.41；95% CI 1.21–1.63；p< 0.001）在多变量分析中仍然是独立预测因子。将 ST2 和 CA125 添加到临床预测模型中，AUC 从 0.74 增加到 0.78 (p = 0.03)。对于心力衰竭相关的住院治疗，ST2 是多变量分析中唯一的预测生物标志物（无论是 30 天还是 1 年）。在合并 HFpEF 的体弱老年人群中，ST2 在预测全因死亡或 HF 相关再住院风险方面优于 NT-proBNP。 ST2 是炎症和纤维化的替代标志物，可能是高危 HFpEF 的更好预测标志物。本文的在线版本 (10.1186/s12877-018-0807-2) 包含补充材料，可供授权用户使用。
Heart failure (HF) is associated with a high rate of readmissions within 30 days post-discharge and in the following year, especially in frail elderly patients. Biomarker data are scarce in this high-risk population. This study assessed the value of early post-discharge circulating levels of ST2, NT-proBNP, CA125, and hs-TnI for predicting 30-day and 1-year outcomes in comorbid frail elderly patients with HF with mainly preserved ejection fraction (HFpEF). Blood samples were obtained at the first visit shortly after discharge (4.9 ± 2 days). The primary endpoint was the composite of all-cause mortality or HF-related rehospitalization at 30 days and at 1 year. All-cause mortality alone at one year was also a major endpoint. HF-related rehospitalizations alone were secondary end-points. From February 2014 to November 2016, 522 consecutive patients attending the STOP-HF Clinic were included (57.1% women, age 82 ± 8.7 years, mean Barthel index 70 ± 25, mean Charlson comorbidity index 5.6 ± 2.2). The composite endpoint occurred in 8.6% patients at 30 days and in 38.5% at 1 year. In multivariable analysis, ST2 [hazard ratio (HR) 1.53; 95% CI 1.19–1.97; p = 0.001] was the only predictive biomarker at 30 days; at 1 year, both ST2 (HR 1.34; 95% CI 1.15–1.56; p < 0.001) and NT-proBNP (HR 1.19; 95% CI 1.02–1.40; p = 0.03) remained significant. The addition of ST2 and NT-proBNP into a clinical predictive model increased the AUC from 0.70 to 0.75 at 30 days (p = 0.02) and from 0.71 to 0.74 at 1 year (p < 0.05). For all-cause death at 1 year, ST2 (HR 1.50; 95% CI 1.26–1.80; p < 0.001), and CA125 (HR 1.41; 95% CI 1.21–1.63; p < 0.001) remained independent predictors in multivariable analysis. The addition of ST2 and CA125 into a clinical predictive model increased the AUC from 0.74 to 0.78 (p = 0.03). For HF-related hospitalizations, ST2 was the only predictive biomarker in multivariable analyses, both at 30 days and at 1 year. In a comorbid frail elderly population with HFpEF, ST2 outperformed NT-proBNP for predicting the risk of all-cause mortality or HF-related rehospitalization. ST2, a surrogate marker of inflammation and fibrosis, may be a better predictive marker in high-risk HFpEF. The online version of this article (10.1186/s12877-018-0807-2) contains supplementary material, which is available to authorized users.
登录
查看更多内容
影响因子：
--
作者：
Dunbar-Yaffe R;Stitt A;Lee JJ;Mohamed S;Lee DS
通讯作者：
Lee DS
影响因子：
9.7
作者：
Jhund, Pardeep S.;Claggett, Brian L.;Solomon, Scott D.
通讯作者：
Solomon, Scott D.
影响因子：
37.8
作者：
Desai, Akshay S.;Stevenson, Lynne W.
通讯作者：
Stevenson, Lynne W.
影响因子：
5.9
作者：
Comin-Colet, Josep;Maria Verdu-Rotellar, Jose;Bruguera, Jordi
通讯作者：
Bruguera, Jordi
影响因子：
4.8
作者：
Au, Anita G.;McAlister, Finlay A.;van Walraven, Carl
通讯作者：
van Walraven, Carl