Abstract
Background
We sought to determine if monitoring heart rate variability (HRV) would enable preclinical detection of secondary complications after subarachnoid hemorrhage (SAH).
Methods
We studied 236 SAH patients admitted within the first 48 h of bleed onset, discharged after SAH day 5, and had continuous electrocardiogram records available. The diagnosis and date of onset of infections and DCI events were prospectively adjudicated and documented by the clinical team. Continuous ECG was collected at 240 Hz using a high-resolution data acquisition system. The Tompkins–Hamilton algorithm was used to identify R–R intervals excluding ectopic and abnormal beats. Time, frequency, and regularity domain calculations of HRV were generated over the first 48 h of ICU admission and 24 h prior to the onset of each patient’s first complication, or SAH day 6 for control patients. Clinical prediction rules to identify infection and DCI events were developed using bootstrap aggregation and cost-sensitive meta-classifiers.
Results
The combined infection and DCI model predicted events 24 h prior to clinical onset with high sensitivity (87 %) and moderate specificity (66 %), and was more sensitive than models that predicted either infection or DCI. Models including clinical and HRV variables together substantially improved diagnostic accuracy (AUC 0.83) compared to models with only HRV variables (AUC 0.61).
Conclusions
Changes in HRV after SAH reflect both delayed ischemic and infectious complications. Incorporation of concurrent disease severity measures substantially improves prediction compared to using HRV alone. Further research is needed to refine and prospectively evaluate real-time bedside HRV monitoring after SAH.
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References
Qureshi AI, Suri MF, Nasar A, et al. Trends in hospitalization and mortality for subarachnoid hemorrhage and unruptured aneurysms in the United States. Neurosurgery. 2005;57:1–8 (discussion 1–8).
Diringer MN. Management of aneurysmal subarachnoid hemorrhage. Crit Care Med. 2009;37:432.
Moorman JR, Carlo WA, Kattwinkel J, et al. Mortality reduction by heart rate characteristic monitoring in very low birth weight neonates: a randomized trial. J Pediatr. 2011. doi:10.1016/j.jpeds.2011.06.044.
Ahmad S, Ramsay T, Huebsch L, et al. Continuous multi-parameter heart rate variability analysis heralds onset of sepsis in adults. PLoS One. 2009;4:e6642.
Brun-Buisson C. The epidemiology of the systemic inflammatory response. Intensive Care Med. 2000;26:S064–74.
Tracey KJ. Physiology and immunology of the cholinergic antiinflammatory pathway. J Clin Investig. 2007;117:289–96.
Levy MM, Fink MP, Marshall JC, et al. 2001 SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference. Crit Care Med. 2003;31:1250–6.
Lenz A, Franklin GA, Cheadle WG. Systemic inflammation after trauma. Injury. 2007;38:1336–45.
Provencio JJ, Vora N. Subarachnoid hemorrhage and inflammation: bench to bedside and back. Semin Neurol. 2005;25:435–44.
Dhar R, Diringer MN. The burden of the systemic inflammatory response predicts vasospasm and outcome after subarachnoid hemorrhage. Neurocrit Care. 2008;8:404–12.
Yoshimoto Y, Tanaka Y, Hoya K. Acute systemic inflammatory response syndrome in subarachnoid hemorrhage. Stroke. 2001;32:1989–93.
Dumont AS, Dumont RJ, Chow MM, et al. Cerebral vasospasm after subarachnoid hemorrhage: putative role of inflammation. Neurosurgery. 2003;53:123–33 (discussion 33–5).
Wartenberg KE, Schmidt JM, Temes RE, et al. Medical complications after subarachnoid hemorrhage: frequency and impact on outcome. Stroke. 2005;36:521.
Park S, Kaffashi F, Loparo KA, Jacono FJ. The use of heart rate variability for the early detection of treatable complications after aneurysmal subarachnoid hemorrhage. J Clin Monit Comput. 2013;27:385–93.
Akbani R, Kwek S, Japkowicz N. Applying support vector machines to imbalanced datasets. Machine Learning: ECML 2004. Berlin: Springer; 2004. p. 39–50.
Bederson JB, Connolly ES Jr, Batjer HH, et al. Guidelines for the management of aneurysmal subarachnoid hemorrhage: a statement for healthcare professionals from a special writing group of the Stroke Council, American Heart Association. Stroke. 2009;40:994–1025.
Komotar RJ, Schmidt JM, Starke RM, et al. Resuscitation and critical care of poor-grade subarachnoid hemorrhage. Neurosurgery. 2009;64:397–411.
Hamilton PS, Tompkins WJ. Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database. IEEE Trans Biomed Eng. 1986;33:1157–65.
Robin X, Turck N, Hainard A, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12:77.
Kleiger RE, Stein PK, Bigger JT. Heart rate variability: measurement and clinical utility. Ann Noninvasive Electrocardiol. 2005;10:88–101.
Taylor JA, Carr DL, Myers CW, Eckberg DL. Mechanisms underlying very-low-frequency RR-interval oscillations in humans. Circulation. 1998;98:547–55.
Campbell B, Sturani A, Reid J. Evidence of parasympathetic activity of the angiotensin converting enzyme inhibitor, captopril, in normotensive man. Clin Sci. 1985;68:49–56.
Stein PK, Schmieg RE Jr, El-Fouly A, Domitrovich PP, Buchman TG. Association between heart rate variability recorded on postoperative day 1 and length of stay in abdominal aortic surgery patients. Crit Care Med. 2001;29:1738–43.
Electrophysiology, Task Force of the European Society of Cardiology the North American Society of Pacing. Heart rate variability : standards of measurement, physiological interpretation, and clinical use. Circulation. 1996;93:1043–65.
Wartenberg KE, Schmidt JM, Claassen J, et al. Impact of medical complications on outcome after subarachnoid hemorrhage. Crit Care Med. 2006;34:617–23 (quiz 24).
Rothoerl RD, Axmann C, Pina AL, Woertgen C, Brawanski A. Possible role of the C-reactive protein and white blood cell count in the pathogenesis of cerebral vasospasm following aneurysmal subarachnoid hemorrhage. J Neurosurg Anesthesiol. 2006;18:68–72.
Kubo Y, Ogasawara K, Kakino S, et al. Serum inflammatory adhesion molecules and high-sensitivity C-reactive protein correlates with delayed ischemic neurologic deficits after subarachnoid hemorrhage. Surg Neurol. 2008;69:592–6 (discussion 6).
Badjatia N, Carpenter A, Fernandez L, et al. Relationship between C-reactive protein, systemic oxygen consumption, and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage. Stroke. 2011;42:2436–42.
Acknowledgments
The Project described was supported by Grant Number KL2 RR024157 (JMS) from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH) and NIH Roadmap for Medical Research, and its contents are solely the responsibility of the authors and do not necessarily represent the official view of NCRR or NIH. Information on NCRR is available at NCRR Website. Information on Re-engineering the Clinical Research Enterprise can be obtained from NIH Roadmap website. Additional support was provided by the Charles A. Dana Foundation (SAM and JMS) and an IBM Faculty Research Award (JMS).
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Schmidt, J.M., Sow, D., Crimmins, M. et al. Heart Rate Variability for Preclinical Detection of Secondary Complications After Subarachnoid Hemorrhage. Neurocrit Care 20, 382–389 (2014). https://doi.org/10.1007/s12028-014-9966-y
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DOI: https://doi.org/10.1007/s12028-014-9966-y