Clinical examination for outcome prediction in nontraumatic coma.
OBJECTIVE
Determine the utility of the neurologic examination in comatose patients from nontraumatic causes in the modern era.


METHODS
Prospective observational study.


METHODS
Single academic medical center.


METHODS
Data from 500 patients in nontraumatic coma collected sequentially from 2000 to 2007 in the emergency department and neuroscience, medical, and cardiac intensive care units.


METHODS
None.


RESULTS
Clinical data were collected on days 0, 1, 3, and 7. Outcome was assessed at 6 months; good outcome was determined at two levels by modified Rankin Scale, ≤3 as independence and ≤4 as moderate but not severe disability. A classification and regression tree analysis was performed to determine prognostic variables, creating predictive algorithms of good vs. poor outcome for each day. Patients with coma attributable to subarachnoid hemorrhage (4/80; 5%) or global hypoxic-ischemic injury (20/202, 10%) were more likely to achieve good outcomes. The pupillary reflex was an important determinant, regardless of day or modified Rankin Scale cut point (mean odds ratio 12.51, range [6.01, 22.56] for modified Rankin Scale ≤3; mean odds ratio 19.26, range [5.38, 42.26] for modified Rankin Scale ≤4). A less robust effect was seen for oculocephalic reflexes (mean odds ratio 62.61, range [2.24, 177] for modified Rankin Scale ≤3; mean odds ratio 34.13, range [4.95, 89.93] for modified Rankin Scale ≤4). The motor response was selected as a predictor of outcome only on day 0 (odds ratio 2.35, 95% confidence interval 0.64-5.74 for modified Rankin Scale ≤3; odds ratio 2.1, 95% confidence interval 0.81-4.24 for modified Rankin Scale score ≤4). Age was not associated with outcome.


CONCLUSIONS
The clinical neurologic examination remains central to determining prognosis in nontraumatic coma. Additional clinical and diagnostic variables may also aid in outcome prediction for specific disease states.
Department of Neurology, Yale University School of Medicine, New Haven, CT, USA. david.greer@yale.edu
David M
DM
Greer
Jingyun
J
Yang
Patricia D
PD
Scripko
John R
JR
Sims
Sydney
S
Cash
Ronan
R
Kilbride
Ona
O
Wu
Jason P
JP
Hafler
David A
DA
Schoenfeld
Karen L
KL
Furie
D000465:Algorithms; D016009:Chi-Square Distribution; D003128:Coma / Q000175:diagnosis* / Q000209:etiology; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D000860:Hypoxia; D020925:Hypoxia-Ischemia, Brain / Q000150:complications; D008297:Male; D008875:Middle Aged; D009460:Neurologic Examination / Q000379:methods / Q000706:statistics & numerical data; D017063:Outcome Assessment, Health Care / Q000379:methods; D011446:Prospective Studies; D012025:Reflex, Pupillary; D018709:Statistics, Nonparametric; D013345:Subarachnoid Hemorrhage / Q000150:complications; D016896:Treatment Outcome