Suppr超能文献

家族性自主神经功能异常中死亡率的高级心电图预测指标

Advanced electrocardiographic predictors of mortality in familial dysautonomia.

作者信息

Solaimanzadeh I, Schlegel T T, Feiveson A H, Greco E C, DePalma J L, Starc V, Marthol H, Tutaj M, Buechner S, Axelrod F B, Hilz M J

机构信息

National Space Biomedical Research Institute, Houston, Texas, USAA.

出版信息

Auton Neurosci. 2008 Dec 15;144(1-2):76-82. doi: 10.1016/j.autneu.2008.08.016. Epub 2008 Oct 11.

Abstract

OBJECTIVE

To identify electrocardiographic predictors of mortality in patients with familial dysautonomia (FD).

METHODS

Ten-minute resting high-fidelity 12-lead electrocardiograms (ECGs) were obtained from 14 FD patients and 14 age/gender-matched healthy subjects. Multiple conventional and advanced ECG parameters were studied for their ability to predict mortality over a subsequent 4.5-year period, including representative parameters of heart rate variability (HRV), QT variability (QTV), T-wave complexity, signal averaged ECG, and 3-dimensional ECG.

RESULTS

Four of the 14 FD patients died during the follow-up period, three with concomitant pulmonary disorder. Of the ECG parameters studied, increased non-HRV-correlated QTV and decreased HRV were the most predictive of death. Compared to controls as a group, FD patients also had significantly increased ECG voltages, JTc intervals and waveform complexity, suggestive of structural heart disease.

CONCLUSION

Increased QTV and decreased HRV are markers for increased risk of death in FD patients. When present, both markers may reflect concurrent pathological processes, especially hypoxia due to pulmonary disorders and sleep apnea.

摘要

目的

确定家族性自主神经功能障碍(FD)患者死亡的心电图预测指标。

方法

从14例FD患者和14例年龄/性别匹配的健康受试者中获取10分钟静息状态下的高保真12导联心电图(ECG)。研究了多种传统和先进的ECG参数预测随后4.5年死亡率的能力,包括心率变异性(HRV)、QT变异性(QTV)、T波复杂性、信号平均心电图和三维心电图的代表性参数。

结果

14例FD患者中有4例在随访期间死亡,3例伴有肺部疾病。在所研究的ECG参数中,与HRV无关的QTV增加和HRV降低对死亡的预测性最强。与作为一个整体的对照组相比,FD患者的ECG电压、JTc间期和波形复杂性也显著增加,提示存在结构性心脏病。

结论

QTV增加和HRV降低是FD患者死亡风险增加的标志。当两者都存在时,可能反映了并发的病理过程,尤其是肺部疾病和睡眠呼吸暂停导致的缺氧。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验