Predictors of Short-Term Mortality in Patients with Ischemic Stroke.
Silvina IluţȘtefan-Cristian VesaVitalie VăcărașDafin-Fior MureșanuPublished in: Medicina (Kaunas, Lithuania) (2023)
Background and Objectives : The purpose of this study is to investigate the predictive factors for intrahospital mortality in ischemic stroke patients. We will examine the association between a range of clinical and demographic factors and intrahospital mortality, including age, sex, comorbidities, laboratory values, and medication use. Materials and Methods : This retrospective, longitudinal, analytic, observational cohort study included 243 patients over 18 years old with a new ischemic stroke diagnosis who were hospitalized in Cluj-Napoca Emergency County Hospital. Data collected included the patient demographics, baseline characteristics at hospital admission, medication use, carotid artery Doppler ultrasound, as well as cardiology exam, and intrahospital death. Results : Multivariate logistic regression was used to determine which variables were independently associated with intrahospital death. An NIHSS score > 9 (OR-17.4; p < 0.001) and a lesion volume > 22.3 mL (OR-5.8; p = 0.003) were found to be associated with the highest risk of death. In contrast antiplatelet treatment (OR-0.349; p = 0.04) was associated with lower mortality rates. Conclusions : Our study identified a high NIHSS score and large lesion volume as independent risk factors for intrahospital mortality in ischemic stroke patients. Antiplatelet therapy was associated with lower mortality rates. Further studies are needed to explore the potential mechanisms underlying these associations and to develop targeted interventions to improve patient outcomes.
Keyphrases
- cardiovascular events
- antiplatelet therapy
- risk factors
- healthcare
- emergency department
- coronary artery disease
- magnetic resonance imaging
- acute coronary syndrome
- magnetic resonance
- cardiovascular disease
- percutaneous coronary intervention
- chronic kidney disease
- newly diagnosed
- computed tomography
- machine learning
- end stage renal disease
- physical activity
- type diabetes
- cardiac surgery
- artificial intelligence
- brain injury
- subarachnoid hemorrhage
- data analysis
- cancer therapy
- drug induced
- smoking cessation