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KMID : 0858420060080020179
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Korean Journal of Stroke
2006 Volume.8 No. 2 p.179 ~ p.186
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Predictors of In-Hospital Death of Stroke Patients Regarding the Demographics and Previous Medical Illness
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Kim Cheol-Gyu
Park Hyeoun-Ae
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Abstract
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Background: Stroke is the 2nd leading cause of death in Korea. Our aim was to investigate the predictors of in-hospital death of stroke patients regarding the demographics and previous medical illeness.
Method: Using the Korea nationwide insurance claim database between Jan 1 2003 and Dec 31 2003, we retrospectively identified stroke patients who were hospitalized and discharged with an International Classification of Disease (ICD) 10 code of stroke including‘subarachnoid hemorrhage (I60)’,‘intracerebral hemorrhage (I61) ’,‘other nontraumatic intracranial hemorrhage (I62) ’ and‘cerebral infarction (I63) ’. We collected the data of age, sex, medical security, and previous medical illness such as atrial fibrillation/flutter, other cardiac arrhythmia, ischemic heart disease, heart failure, chronic obstructive pulmonary disease, hypertension, diabetes mellitus, malignancy, liver disease, renal failure and stroke. Case fatality was assessed by the national death certificate data of 2003. Logistic regression analysis was performed to identify the independent predictors for in-hospital death.
Result: We identified 92,717 stroke patients including 65,440 (70.6%), and 27,277 (29.4%) hemorrhagic stroke. In-hospital mortalities were 6.4% for all stroke, 3.5% for non- hemorrhagic stroke, and 13.4% for hemorrhagic stroke.
Older age, male, low socioeconomic status, history of renal failure and previous stroke were independent predictors of in-hospital death in both of non-hemorrhagic and hemorrhagic stroke. For non-hemorrhagic stroke, additional predictors were atrial fibrillation/ flutter and heart failure. For hemorrhagic stroke, malignancy, other cardiac arrhythmia, and diabetes mellitus were additional predictors
of in-hospitla death.
Conclusion: To reduce the in-hospital stroke mortality, more efficienct strategy is required for high risk patients.
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KEYWORD
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Stroke, In-hospital death, Predictor
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