QJM Advance Access published online on November 16, 2008
QJM, doi:10.1093/qjmed/hcn149
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Factors predictive of outcome in patients with de novo status epilepticus
From the 1Department of Neurology, Chang Gung Memorial Hospital-Kaohsiung Medical Center, Chang Gung University College of Medicine, 2Department of Biological Science, National Sun Yat-Sen University, 3Department of Neurolosurgery, Chang Gung Memorial Hospital-Kaohsiung Medical Center, Chang Gung University College of Medicine, Kaohsiung, Taiwan
Address correspondence to C.-H. Lu, Department of Neurology, Chang Gung Memorial Hospital, #123, Ta Pei Road, Niao Sung Hsiang, Kaohsiung County, Taiwan. email: chlu99{at}ms44.url.com.tw
Received 23 May 2008 and in revised form 16 October 2008
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Background: About 50% of status epilepticus (SE) patients have no previous history of epilepsy, but often have worse outcome. The aim of this study was to evaluate potential risk factors that are predictive of poor outcome in non-selected de novo status epilepticus patients.
Methods: Eighty-three adult status epilepticus patients without a pre-existing history of epilepsy that were admitted to hospital for treatment were enrolled in this 11-year retrospective study. The baseline prognostic variables were analyzed based on stepwise logistic regression analysis after a minimum of one-and-half years of follow-up.
Results: The overall fatality rate was 55.4% (46/83) during the study period. Poor outcome was associated with older age, presence of refractory status epilepticus, potential fatal etiologies, lower GCS score at presentation and level of consciousness on admission. The results of stepwise logistic regression demonstrated that age on presentation and potential fatal etiologies were independently associated with presence of poor outcome, and any increase in age by 1 year increases poor outcome by 7.5%.
Conclusions: The outcome for those with de novo status epilepticus is poor and this poor outcome may be attributed to the older age at onset and the potential fatal underlying conditions such as infection and metabolic derangement.