Feng Jiayu, Huang Liyan, Zhao Xuemei, Li Xinqing, Xin Anran, Wang Chengyi, Zhang Yuhui, Zhang Jian
State Key Laboratory of Cardiovascular Disease, Heart Failure Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, No.167 Beilishi Road, Beijing, 10037, China.
Key Laboratory of Clinical Research for Cardiovascular Medications, National Health Committee, Beijing, China.
Nutr Metab (Lond). 2024 Sep 30;21(1):77. doi: 10.1186/s12986-024-00856-2.
Metabolic disorder, malnutrition and inflammation are involved and interplayed in the mechanisms of heart failure with preserved ejection fraction (HFpEF). We aimed to construct a Metabolism-malnutrition-inflammation score (MIS) to predict the risk of death in patients with HFpEF.
We included patients diagnosed with HFpEF and without infective or systemic disease. 20 biomarkers were filtered by the Least absolute shrinkage and selection operator (Lasso)-Cox regression. 1000 times bootstrapping datasets were generated to select biomarkers that appeared above 95% frequency in repetitions to construct the MIS.
Among 1083 patients diagnosed with HFpEF, 342 patients (31.6%) died during a median follow-up period of 2.5 years. The MIS was finally constructed based on 6 biomarkers, they were albumin (ALB), red blood cell distribution width-standard deviation (RDW-SD), high-sensitivity C-reactive protein (hs-CRP), lymphocytes, triiodothyronine (T3) and uric acid (UA). Incorporating MIS into the basic predictive model significantly increased both discrimination (∆C-index = 0.034, 95% CI 0.013-0.050) and reclassification (IDI, 6.6%, 95% CI 4.0%-9.5%; NRI, 22.2% 95% CI 14.4%-30.2%) in predicting all-cause mortality. In the time-dependent receiver operating characteristic (ROC) analysis, the mean area under the curve (AUC) for the MIS was 0.778, 0.782 and 0.772 at 1, 3, and 5 years after discharge in the cross-validation sets. The MIS was independently associated with all-cause mortality (hazard ratio: 1.98, 95% CI [1.70-2.31], P < 0.001).
A risk score derived from 6 commonly used inflammatory, nutritional, thyroid and uric acid metabolic biomarkers can effectively identify high-risk patients with HFpEF, providing potential individualized management strategies for patients with HFpEF.
代谢紊乱、营养不良和炎症参与射血分数保留的心力衰竭（HFpEF）机制并相互作用。我们旨在构建一个代谢-营养不良-炎症评分（MIS）来预测HFpEF患者的死亡风险。
我们纳入了诊断为HFpEF且无感染性或全身性疾病的患者。通过最小绝对收缩和选择算子（Lasso）-Cox回归筛选出20种生物标志物。生成1000次自抽样数据集，以选择在重复中出现频率高于95%的生物标志物来构建MIS。
在1083例诊断为HFpEF的患者中，342例（31.6%）在中位随访期2.5年期间死亡。MIS最终基于6种生物标志物构建，它们分别是白蛋白（ALB）、红细胞分布宽度标准差（RDW-SD）、高敏C反应蛋白（hs-CRP）、淋巴细胞、三碘甲状腺原氨酸（T3）和尿酸（UA）。将MIS纳入基本预测模型可显著提高预测全因死亡率的辨别力（∆C指数 = 0.034，95%可信区间0.013 - 0.050）和重新分类能力（综合判别改善指数，6.6%，95%可信区间4.0% - 9.5%；净重新分类指数，22.2%，95%可信区间14.4% - 30.2%）。在时间依赖性受试者工作特征（ROC）分析中，交叉验证集中出院后1年、3年和5年时MIS的曲线下平均面积（AUC）分别为0.778、0.782和0.772。MIS与全因死亡率独立相关（风险比：1.98，95%可信区间[1.70 - 2.31]，P < 0.001）。
由6种常用的炎症、营养、甲状腺和尿酸代谢生物标志物得出的风险评分可有效识别HFpEF高危患者，为HFpEF患者提供潜在的个体化管理策略。
