ABSTRACT
Purpose@#Plasma osmolality, a marker of dehydration, is associated with cardiovascular mortality. We aimed to investigate whether elevated plasma osmolality is associated with case fatality within 1 year after severe acute ischemic stroke. @*Materials and Methods@#We included severe ischemic stroke patients (defined as National Institutes of Health Stroke Scale ≥15 score) within 24 hours from symptom onset admitted to the Department of Neurology, West China Hospital between January 2017 and June 2019. Admission plasma osmolality was calculated using the equation 1.86 * (sodium+potassium)+1.15 * glucose+urea+14. Elevated plasma osmolality was defined as plasma osmolality >296 mOsm/kg, indicating a state of dehydration. Study outcomes included 3-month and 1-year case fatalities. Multivariable logistic regression was performed to determine independent associations between plasma osmolality and case fatalities at different time points. @*Results@#A total of 265 patients with severe acute ischemic stroke were included. The mean age was 71.2±13.1 years, with 51.3% being males. Among the included patients, case fatalities were recorded for 31.7% (84/265) at 3 months and 39.6% (105/265) at 1 year. Elevated plasma osmolality (dehydration) was associated with 3-month case fatality [odds ratio (OR) 1.98, 95% confidence interval (CI) 1.07–3.66, p=0.029], but not 1-year case fatality (OR 1.51, 95% CI 0.84–2.72, p=0.165), after full adjustment for confounding factors. @*Conclusion@#Elevated plasma osmolality was independently associated with 3-month case fatality, but not 1-year case fatality, for severe acute ischemic stroke.
ABSTRACT
Purpose@#Plasma osmolality, a marker of dehydration, is associated with cardiovascular mortality. We aimed to investigate whether elevated plasma osmolality is associated with case fatality within 1 year after severe acute ischemic stroke. @*Materials and Methods@#We included severe ischemic stroke patients (defined as National Institutes of Health Stroke Scale ≥15 score) within 24 hours from symptom onset admitted to the Department of Neurology, West China Hospital between January 2017 and June 2019. Admission plasma osmolality was calculated using the equation 1.86 * (sodium+potassium)+1.15 * glucose+urea+14. Elevated plasma osmolality was defined as plasma osmolality >296 mOsm/kg, indicating a state of dehydration. Study outcomes included 3-month and 1-year case fatalities. Multivariable logistic regression was performed to determine independent associations between plasma osmolality and case fatalities at different time points. @*Results@#A total of 265 patients with severe acute ischemic stroke were included. The mean age was 71.2±13.1 years, with 51.3% being males. Among the included patients, case fatalities were recorded for 31.7% (84/265) at 3 months and 39.6% (105/265) at 1 year. Elevated plasma osmolality (dehydration) was associated with 3-month case fatality [odds ratio (OR) 1.98, 95% confidence interval (CI) 1.07–3.66, p=0.029], but not 1-year case fatality (OR 1.51, 95% CI 0.84–2.72, p=0.165), after full adjustment for confounding factors. @*Conclusion@#Elevated plasma osmolality was independently associated with 3-month case fatality, but not 1-year case fatality, for severe acute ischemic stroke.
ABSTRACT
Objective We evaluate if supplementary grading system can refine patient selection and accurately predict neurological outcome in BAVM. Methods We retrospectively study 221 BAVM patients who were treated micro?surgically by our hospital. The score of pre and post operation mRS and relative clinical, radiology data were collected. Two different logistic models (Spetzler-Martin, Supplementary Spetzler-Martin grading model) were constructed to com?pare the area under ROC. Results Some factors are significant different between worse outcome patients and good out?come patients:Non-hemorrhagic presentations prior surgery, AVM bigger than 3cm, diffuse shape of AVM and the elder patients. Predictive accuracy was higher for the supplementary model (ROC area, 0.91), than the Spetzler-Martin model (ROC area, 0.774). So the predictive accuracy of supplementary model was significantly better than that of the Spet?zler-Martin model (P=0.0362). Conclusions Supplementary Spetzler-Martin model can improve preoperative risk pre?diction and subgroup the patients more efficiently. When the score less than 5(including 5) in supplementary Spet?zler-Martin patients seem to have lower risk relative to surgery.