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心血管磁共振特征追踪衍生应变分析可预测劳力性热射病后恢复训练的情况。

Cardiovascular magnetic resonance feature tracking derived strain analysis can predict return to training following exertional heatstroke.

作者信息

Zhang Jun, Luo Song, Qi Li, Xu Shutian, Yi Dongna, Jiang Yue, Kong Xiang, Liu Tongyuan, Dou Weiqiang, Cai Jun, Zhang Long Jiang

机构信息

Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002 Jiangsu, China.

National Clinical Research Centre of Kidney Diseases, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002 Jiangsu, China.

出版信息

J Cardiovasc Magn Reson. 2024;26(2):101076. doi: 10.1016/j.jocmr.2024.101076. Epub 2024 Aug 6.

DOI:10.1016/j.jocmr.2024.101076
PMID:39098574
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11417221/
Abstract

BACKGROUND

Exertional heatstroke (EHS) is increasingly common in young trained soldiers. However, prognostic markers in EHS patients remain unclear. The objective of this study was to evaluate cardiovascular magnetic resonance (CMR) feature tracking derived left ventricle (LV) strain as a biomarker for return to training (RTT) in trained soldiers with EHS.

METHODS

Trained soldiers (participants) with EHS underwent CMR cine sequences between June 2020 and August 2023. Two-dimensional (2D) LV strain parameters were derived. At 3 months after index CMR, the participants with persistent cardiac symptoms including chest pain, dyspnea, palpitations, syncope, and recurrent heat-related illness were defined as non-RTT. Multivariable logistic regression analysis was used to develop a predictive RTT model. The performance of different models was compared using the area under curve (AUC).

RESULTS

A total of 80 participants (median age, 21 years; interquartile range (IQR), 20-23 years) and 27 health controls (median age, 21 years; IQR, 20-22 years) were prospectively included. Of the 77 participants, 32 had persistent cardiac symptoms and were not able to RTT at 3 months follow-up after experiencing EHS. The 2D global longitudinal strain (GLS) was significantly impaired in EHS participants compared to the healthy control group (-15.8 ± 1.7% vs -16.9 ± 1.2%, P = 0.001), which also showed significant statistical differences between participants with RTT and non-RTT (-15.0 ± 3.5% vs -16.5 ± 1.4%, P < 0.001). 2D-GLS (≤ -15.0%) (odds ratio, 1.53; 95% confidence interval: 1.08, 2.17; P = 0.016) was an independent predictor for RTT even after adjusting known risk factors. 2D-GLS provided incremental prognostic value over the clinical model and conventional CMR parameters model (AUCs: 0.72 vs 0.88, P = 0.013; 0.79 vs 0.88, P = 0.023; respectively).

CONCLUSION

Two-dimensional global longitudinal strain (≤ -15.0%) is an incremental prognostic CMR biomarker to predict RTT in soldiers suffering from EHS.

摘要

背景

劳力性热射病(EHS)在年轻的训练有素的士兵中越来越常见。然而,EHS患者的预后标志物仍不明确。本研究的目的是评估心血管磁共振(CMR)特征追踪得出的左心室(LV)应变作为EHS训练有素的士兵恢复训练(RTT)的生物标志物。

方法

2020年6月至2023年8月期间,对患有EHS的训练有素的士兵(参与者)进行CMR电影序列检查。得出二维(2D)LV应变参数。在首次CMR检查后3个月,有持续心脏症状(包括胸痛、呼吸困难、心悸、晕厥和复发性热相关疾病)的参与者被定义为未恢复训练(non-RTT)。采用多变量逻辑回归分析建立预测RTT的模型。使用曲线下面积(AUC)比较不同模型的性能。

结果

前瞻性纳入了80名参与者(中位年龄21岁;四分位间距(IQR),20 - 23岁)和27名健康对照者(中位年龄21岁;IQR,20 - 22岁)。在77名参与者中,32人有持续心脏症状,在经历EHS后3个月随访时无法恢复训练。与健康对照组相比,EHS参与者的二维整体纵向应变(GLS)明显受损(-15.8±1.7%对-16.9±1.2%,P = 0.001),在恢复训练和未恢复训练的参与者之间也显示出显著统计学差异(-15.0±3.5%对-16.5±1.4%,P < 0.001)。即使在调整已知危险因素后,二维GLS(≤ -15.0%)(比值比,1.53;95%置信区间:1.08,2.17;P = 0.016)仍是RTT的独立预测因子。二维GLS比临床模型和传统CMR参数模型具有更高的预后价值(AUC分别为:0.72对0.88,P = 0.013;0.79对0.88,P = 0.023)。

结论

二维整体纵向应变(≤ -15.0%)是一种增加预后价值的CMR生物标志物,可用于预测患有EHS士兵的RTT。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/445849c9daaf/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/9e3e97fafb41/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/293bb34c8616/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/ab83b624da64/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/ad4d6d0db7bb/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/445849c9daaf/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/9e3e97fafb41/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/293bb34c8616/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/ab83b624da64/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/ad4d6d0db7bb/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51d5/11417221/445849c9daaf/gr4.jpg

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