Heart Rate Variability as a Biomarker of Neurocardiogenic Injury After Subarachnoid Hemorrhage.

TitleHeart Rate Variability as a Biomarker of Neurocardiogenic Injury After Subarachnoid Hemorrhage.
Publication TypeJournal Article
Year of Publication2020
AuthorsMegjhani M, Kaffashi F, Terilli K, Alkhachroum A, Esmaeili B, Doyle KWilliam, Murthy S, Velazquez AG, E Connolly S, Roh DJinou, Agarwal S, Loparo KA, Claassen J, Boehme A, Park S
JournalNeurocrit Care
Date Published2020 02

BACKGROUND: The objective of this study was to examine whether heart rate variability (HRV) measures can be used to detect neurocardiogenic injury (NCI).

METHODS: Three hundred and twenty-six consecutive admissions with aneurysmal subarachnoid hemorrhage (SAH) met criteria for the study. Of 326 subjects, 56 (17.2%) developed NCI which we defined by wall motion abnormality with ventricular dysfunction on transthoracic echocardiogram or cardiac troponin-I > 0.3 ng/mL without electrocardiogram evidence of coronary artery insufficiency. HRV measures (in time and frequency domains, as well as nonlinear technique of detrended fluctuation analysis) were calculated over the first 48 h. We applied longitudinal multilevel linear regression to characterize the relationship of HRV measures with NCI and examine between-group differences at baseline and over time.

RESULTS: There was decreased vagal activity in NCI subjects with a between-group difference in low/high frequency ratio (β 3.42, SE 0.92, p = 0.0002), with sympathovagal balance in favor of sympathetic nervous activity. All time-domain measures were decreased in SAH subjects with NCI. An ensemble machine learning approach translated these measures into a classification tool that demonstrated good discrimination using the area under the receiver operating characteristic curve (AUROC 0.82), the area under precision recall curve (AUPRC 0.75), and a correct classification rate of 0.81.

CONCLUSIONS: HRV measures are significantly associated with our label of NCI and a machine learning approach using features derived from HRV measures can classify SAH patients that develop NCI.

Alternate JournalNeurocrit Care
PubMed ID31093884
PubMed Central IDPMC6856427
Grant ListK01 ES026833 / ES / NIEHS NIH HHS / United States
R03 NS101417 / NS / NINDS NIH HHS / United States
R21 ES030093 / ES / NIEHS NIH HHS / United States
R21 MD012451 / MD / NIMHD NIH HHS / United States

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