Research Article: Prediction of Acute Kidney Injury in Intracerebral Hemorrhage Patients Using Machine Learning
Abstract:
As the second leading cause of death and disability worldwide, stroke is classified as ischemic and hemorrhagic type and is the leading cause of death and the second leading cause of long-term disability globally. Accounting for –% of all stroke incidences, cerebral hemorrhage (ICH) has a -day mortality rate exceeding %. The high mortality associated with ICH is not solely ascribed to cerebral injury induced by intracranial hemorrhage but also to extracranial complications such as infection, stress ulcer, deep vein thrombosis, and acute kidney injury (AKI). Some studies have found that AKI is correlated with higher mortality and develops widely among patients with ICH, with an incidence ranging from .% to .%.– It is necessary to assess the risk of AKI in patients with ICH as early as possible during hospitalization to avoid unnecessary nephrotoxic interventions and poor prognosis. The National Institutes of Health Stroke Scale (NIHSS) score, hypertension, baseline estimated glomerular filtration rate, serum cystatin C, and serum uric acid have been identified as risk factors for AKI among ICH patients using traditional logistic regression.,,,
Introduction:
As the second leading cause of death and disability worldwide, stroke is classified as ischemic and hemorrhagic type and is the leading cause of death and the second leading cause of long-term disability globally. Accounting for –% of all stroke incidences, cerebral hemorrhage (ICH) has a -day mortality rate exceeding %. The high mortality associated with ICH is not solely ascribed to cerebral injury induced by intracranial hemorrhage but also to extracranial complications such as infection, stress ulcer, deep…
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