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An Electroencephalographic Classification for Coma

Published online by Cambridge University Press:  18 September 2015

G.B. Young*
Affiliation:
Departments of Clinical Neurological Sciences and Medicine, the University of Western Ontario, London
R.S. McLachlan
Affiliation:
Departments of Clinical Neurological Sciences and Medicine, the University of Western Ontario, London
J.H. Kreeft
Affiliation:
Departments of Clinical Neurological Sciences and Medicine, the University of Western Ontario, London
J.D. Demelo
Affiliation:
Departments of Clinical Neurological Sciences and Medicine, the University of Western Ontario, London
*
Department of Clinical Neurological Sciences, London Health Sciences Centre, 375 South Street, London, Ontario, Canada N6A 4G5
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Abstract:

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Background:

The assessment of thalamocortical function in comatose patients in the intensive care unit (ICU) can be difficult to determine. Since the electroencephalogram (EEG) affords such assessment, we have developed an EEG classification for comatose patients in our general ICU.

Methods:

One hundred EEGs were classified in a blinded fashion by two EEGers, using our method and that of Synek. Interobserver agreement was assessed using kappa score determination.

Results:

Kappa scores were 0.90 for our system and 0.75 for the Synek system. (The Kappa score represents the inter-rater agreement that is beyond chance; 0.90 is almost perfect agreement, while 0.75 is substantial agreement).

Conclusion:

Our system for classifying EEGs in comatose patients has a higher interobserver reliability than one that was previously published. This EEG classification scheme should be useful in clinical electrophysiological research involving ICU patients, allowing for internal consistency and comparisons among centres.

Type
Original Articles
Copyright
Copyright © Canadian Neurological Sciences Federation 1997

References

REFERENCES

1.Bleck, TP, Smith, MC, Pierre-Louis, SJ-C, et al. Neurological complications of critical medical illnesses. Crit Care Med 1993; 21: 98103.CrossRefGoogle ScholarPubMed
2.Knaus, WA, Zimmerman, JE, Wagner, DP, Draper, EZ, Lawrence, DE. APACHE - acute physiology and chronic health evaluation: a physiologically-based classification system. Crit Care Med 1981; 9: 591597.CrossRefGoogle ScholarPubMed
3.Knaus, WA, Draper, EA, Wagner, DP, Zimmerman, JE. APACHE II: a severity of disease classification system. Crit Care Med 1983; 13: 818829.CrossRefGoogle Scholar
4.Elebute, EA, Stoner, HB. The grading of sepsis. Br J Sug 1983; 70: 2931.CrossRefGoogle ScholarPubMed
5.Lemeshow, S, Teres, D, Pastides, H, et al. A method for predicting survival and mortality in ICU patients using objectively derived weights. Crit Care Med 1985; 13: 519525.CrossRefGoogle ScholarPubMed
6.Chang, R, Le Gall, JR, Suter, P, et al. Predicting outcome in intensive care unit patients. Intensive Care World 1995; 11: 148151.Google Scholar
7.Teasdale, G, Jennett, B. Assessment of coma and impaired consciousness - a practical scale. Lancet 1974; 2: 8184.CrossRefGoogle ScholarPubMed
8.Benzer, A, Mitterschiffthaler, G, Marosi, M, et al. Prediction of nonsurvival after trauma: Innsbruck coma scale. Lancet 1991; 338: 977978.CrossRefGoogle ScholarPubMed
9.Binnie, CD, Prior, PF, Lloyd, DSL, Scott, DF, Margerison, JH. Electroencephalographic prediction of fatal anoxic brain damage after resuscitation from cardiac arrest. Br Med J 1970; 4: 265268.CrossRefGoogle ScholarPubMed
10.Hockaday, JM, Potts, F, Epstein, E, et al. Electroencephalographic changes in acute cerebral anoxia from cardiac or respiratory arrest: prognostic value of early electorencephalographic findings. Electroencephalogr Clin Neurophysiol 1965; 18: 575586.CrossRefGoogle ScholarPubMed
11.Young, GB, Blume, WT, Campbell, VM, et al. Alpha, theta and alpha-theta coma; a clinical outcome study using serial recordings. Electroencephalogr Clin Neurophysiol 1994; 91: 9399.CrossRefGoogle Scholar
12.Chiappa, KH, Hoch, DB. Electrophysiologic monitoring. In: Ropper, AH, ed. Neurological and Neurosurgical Intensive Care. New York: Raven Press, 1993: 147183.Google Scholar
13.Jordan, KG. Continuous EEG and evoked potential monitoring in the neurscience intensive care unit. J Clin Neurophysiol 1993; 10: 445475.CrossRefGoogle Scholar
14.Teasdale, G, Jennett, B. Assessment of coma and impaired consciousness. Lancet 1974; 2: 8183.CrossRefGoogle ScholarPubMed
15.Marion, DW. The Glasgow Coma Scale Score: contemporary application. Intensive Care World 1994; 11: 101102.Google Scholar
16.Synek, VM. Prognostically important EEG coma patterns in diffuse anoxic and traumatic encephalopathies in adults. J Clin Neurophysiol 1988; 5: 161174.CrossRefGoogle ScholarPubMed
17.Fleiss, JL. Statistical Methods for Rates and Proportions (2nd edition). New York: Whitley 1981: 217234.Google Scholar
18.Jasper, HH. The ten-twenty system of the International Federation. Electroencephalogr Clin Neurophysiol 1958; 10: 371373.Google Scholar
19.Fishgold, H, and Mathis, P. Obnubilations Comas et stupeurs: études électroencephalographiques. Electroencephalogr Clin Neurophysiol 1959; (Suppl 11): 2768.Google Scholar
20.Vespa, PM, Nuwer, MR, Martin, MA, Becker, DP. Early detection of vasospasm after subarachnoid hemorrhage using continuous quantitative electroencephalogram. Neurology 1996; 46 (Suppl): A385.Google Scholar
21.Thomassen, A, Weinberg, M. Prevalence and prognostic significance of coma after cardiac arrest outside intensive care and coronary care units. Acta Anesth Scand 1979; 23: 143148.CrossRefGoogle Scholar
22.Longstreth, W, Diehr, P, Inui, TS. Prediction of awakening after out-of-hospital cardiac arrest. N Engl J Med 1983; 308: 13781382.CrossRefGoogle ScholarPubMed
23.Wagner, DP, Knaus, WA, Draper, EA. Statistical validation of a severity of illness measure. Am J Public Health 1983; 73: 878884.CrossRefGoogle ScholarPubMed
24.Pampliglione, G, Harden, A. Resuscitation after cardiovascular arrest. Prognostic evaluation of early electroencephalographic findings. Lancet 1968; 1: 12611264.Google Scholar
25.Scollo-Lavizzari, G, Bassetti, C. Prognostic value of EEG in postanoxic coma after cardiac arrest. Eur Neurol 1987; 26: 161170.CrossRefGoogle ScholarPubMed
26.Young, GB, Leung, LS, Campbell, VJ, et al. The electroencephalogram in metabolic/toxic coma. Am J EEG Technology 1992; 32: 243260.CrossRefGoogle Scholar
27.Young, GB. The value of the neurological examination and EEG in determining the prognosis in general intensive care units. Neurology 1992; 42 (Suppl 3): 194195.Google Scholar
28.Young, GB, DeMelo, J, Kreeft, J, McLachlan, R. The significance of epileptiform activity in comatose patients in the general intensive care unit (ICU). Can J Neurol Sci 1992; 19: 251.Google Scholar
29.Pedley, TA, Traub, RD. Physiological basis of the EEG. In: Daly, DD, Pedley, TA, eds. Current Practice of Clinical Electroencephalography. New York: Raven Press, 1990: 107137.Google Scholar
30.Hansotia, P, Gottschalk, PI, Green, P, Zais, D. Spindle coma: incidence, clincopathological correlations and prognostic value. Neurology 1981; 31: 8387.CrossRefGoogle Scholar
31.Young, GB, Bolton, CF, Austin, TW, Archibald, Y, Wells, GA. The electroencephalogram in sepsis-associated encephalopathy. J Clin Neurophysiol 1992; 9: 145152.CrossRefGoogle ScholarPubMed
32.Ruttiman, UE. Statistical approaches to development and validation of predictive instruments. In: Schuster, DP, Kollef, MH, eds. Critical Care Clinics: Predicting Intensive Care Unit Outcome. Philadelphia: Saunder, 1994; 10: 1935.CrossRefGoogle Scholar
33.Brunko, E, Zegers de Beyl, D. Prognostic value of early cortical somatosensory evoked potentials after resuscitation from cardiac arrest. Electroencephalogr Clin Neurophysiol 1987; 66: 1524.CrossRefGoogle ScholarPubMed
34.Rothstein, TL, Thomas, EM, Sumi, SM. Predicting outcome in hypoxicschemic coma. A prospective clinical and electrophysiologic study. Electroencephalogr Clin Neurophysiol 1991; 79: 101107.CrossRefGoogle Scholar
35.Cant, BR, Hume, AL, Shaw, NA. The assessment of severe head injury by short latency somatosensory and brain-stem auditory evoked potentials. Electroencephalogr Clin Neurophysiol 1986; 65: 188195.CrossRefGoogle ScholarPubMed