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心脏型脂肪酸结合蛋白(H-FABP)作为脓毒症性心肌病的早期生物标志物:一项前瞻性观察研究。

Heart-type fatty acid binding protein (H-FABP) as an early biomarker in sepsis-induced cardiomyopathy: a prospective observational study.

机构信息

Nanjing Medical University, 101 Longmian Avenue, Nanjing, China.

China Pharmaceutical University, 639 Longmian Avenue, Nanjing, China.

出版信息

Lipids Health Dis. 2024 Sep 4;23(1):283. doi: 10.1186/s12944-024-02264-0.

DOI:10.1186/s12944-024-02264-0
PMID:39232765
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11373395/
Abstract

BACKGROUND

Sepsis-induced cardiomyopathy (SICM) is a common and life-threatening complication of sepsis, significantly contributing to elevated mortality. This study aimed to identify crucial indicators for the prompt and early assessment of SICM.

METHODS

Patients diagnosed with sepsis or SICM within 24 h of intensive care unit (ICU) admission were enrolled in this prospective observational study. Patients were assigned to the training set, validation set and external test set. The primary endpoint was 7-day ICU mortality, and the secondary endpoint was 28-day ICU mortality. Three machine learning algorithms were utilized to identify relevant indicators for diagnosing SICM, incorporating 64 indicators including serum biomarkers associated with cardiac, renal, and liver function, lipid metabolism, coagulation, and inflammation. Internal and external validations were performed on the screening results. Patients were then stratified based on the cut-off value of the most diagnostically effective biomarker identified, and their prognostic outcomes were observed and analyzed.

RESULTS

A total of 270 patients were included in the training and validation set, and 52 patients were included in the external test set. Age, sex, and comorbidities did not significantly differ between the sepsis and SICM groups (P > 0.05). The support vector machine (SVM) algorithm identified six indicators with an accuracy of 84.5%, the random forest (RF) algorithm identified six indicators with an accuracy of 81.9%, and the logistic regression (LR) algorithm screened out seven indicators. Following rigorous selection, a diagnostic model for sepsis-induced cardiomyopathy was established based on heart-type fatty acid binding protein (H-FABP) (OR 1.308, 95% CI 1.170-1.462, P < 0.001) and retinol-binding protein (RBP) (OR 1.020, 95% CI 1.006-1.034, P < 0.05). H-FABP alone exhibited the highest diagnostic performance in both the internal (AUROC 0.689, P < 0.05) and external sets (AUROC 0.845, P < 0.05). Patients with SICM were further stratified based on an H-FABP diagnostic cut-off value of 8.335 ng/mL. Kaplan-Meier curve analysis demonstrated that elevated H-FABP levels at admission were associated with higher 7-day ICU mortality in patients with SICM (P < 0.05).

CONCLUSIONS

This study revealed that H-FABP concentrations measured within 24 h of patient admission could serve as a crucial biomarker for the early and rapid diagnosis and short-term prognostic evaluation of SICM.

摘要

背景

脓毒症相关性心肌病(SICM)是脓毒症的一种常见且危及生命的并发症,显著增加了死亡率。本研究旨在确定用于快速早期评估 SICM 的关键指标。

方法

本前瞻性观察性研究纳入了在入住重症监护病房(ICU)后 24 小时内被诊断为脓毒症或 SICM 的患者。患者被分配到训练集、验证集和外部测试集。主要终点为 7 天 ICU 死亡率,次要终点为 28 天 ICU 死亡率。使用三种机器学习算法来识别诊断 SICM 的相关指标,纳入了与心脏、肾脏和肝功能、脂质代谢、凝血和炎症相关的 64 个血清生物标志物。对筛选结果进行内部和外部验证。根据确定的最具诊断效果的生物标志物的临界值对患者进行分层,并观察和分析其预后结果。

结果

共有 270 名患者纳入训练和验证集,52 名患者纳入外部测试集。脓毒症组和 SICM 组的年龄、性别和合并症无显著差异(P>0.05)。支持向量机(SVM)算法识别出 6 个准确率为 84.5%的指标,随机森林(RF)算法识别出 6 个准确率为 81.9%的指标,逻辑回归(LR)算法筛选出 7 个指标。经过严格选择,基于心脏型脂肪酸结合蛋白(H-FABP)(OR 1.308,95%CI 1.170-1.462,P<0.001)和视黄醇结合蛋白(RBP)(OR 1.020,95%CI 1.006-1.034,P<0.05)建立了脓毒症相关性心肌病的诊断模型。H-FABP 单独在内部(AUROC 0.689,P<0.05)和外部组(AUROC 0.845,P<0.05)均具有最高的诊断性能。根据 H-FABP 的诊断截断值 8.335ng/mL 进一步对 SICM 患者进行分层。Kaplan-Meier 曲线分析表明,SICM 患者入院时 H-FABP 水平升高与 7 天 ICU 死亡率升高相关(P<0.05)。

结论

本研究表明,患者入院后 24 小时内测量的 H-FABP 浓度可作为 SICM 早期快速诊断和短期预后评估的关键生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf71/11373395/4d8174e9e3c9/12944_2024_2264_Fig5_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf71/11373395/4d8174e9e3c9/12944_2024_2264_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf71/11373395/59ab54a1a9f0/12944_2024_2264_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf71/11373395/c9752ecc3d5f/12944_2024_2264_Fig2_HTML.jpg
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