Neurology最新文献

Background and objectives: Previous studies have indicated an increased risk of cerebrovascular and coronary events shortly after cancer diagnosis. However, whether cancer affects mortality outcomes after stroke and myocardial infarction (MI) remains unclear. We aimed to investigate the relationship between cancer diagnosis and mortality after stroke and MI.

Methods: Using linked nationwide databases from Taiwan, we conducted a population-based cohort study including 3 cohorts of patients with first-time ischemic stroke, hemorrhagic stroke, and MI between 2011 and 2019. The primary outcome was 90-day mortality, with follow-up beginning at the index stroke (for ischemic and hemorrhagic stroke cohorts) and MI (for the MI cohort) event date for all patients. Odds ratios (ORs) of 90-day mortality associated with all cancers combined and 15 cancer types were estimated through propensity score matching for potential confounding variables. Excess mortality rates (between patients with cancer and matched controls) were analyzed across time intervals after cancer diagnosis, stratified by age group, cancer stage, and cancer type.

Results: Overall, 440,664, 159,606, and 228,993 patients were included in ischemic stroke (mean age, 70.1 years; 40.7% female), hemorrhagic stroke (mean age, 65.4 years; 36.5% female), and MI (mean age, 67.8 years; 29.7% female) cohorts, respectively. Compared with matched controls, patients with cancer had higher risks of 90-day mortality in ischemic stroke (OR 2.71, 95% CI 2.63-2.79), hemorrhagic stroke (OR 2.20, 95% CI 2.11-2.29), and MI (OR 1.63, 95% CI 1.57-1.69). Across 3 cohorts, substantial variations existed among cancer types, with aggressive malignancies (e.g., pancreatic cancer) consistently presenting the highest risks. Excess mortality rates were highest during the first postdiagnosis year and declined progressively thereafter. This temporal pattern was consistent across age groups and cancer stages, with excess mortality rates highest among patients aged 18-59 years and those with stage 4 disease. Despite variability among cancer types, excess mortality typically peaked within 2 years.

Discussion: This population-based study showed that patients with cancer had higher risks of mortality after stroke and MI, with substantial variations by cancer type, although cause-specific mortality data were lacking. Excess mortality rates peaked shortly after diagnosis, particularly for early-onset cancer and advanced disease.

Background and objectives: Although etiology is considered central to outcomes in status epilepticus (SE), previous studies often lacked standardized classification and adjustment for confounders, particularly withdrawal of life-sustaining treatment (WLST). This study examined the association between SE etiology, mortality, and neurologic recovery using the International League Against Epilepsy (ILAE) classification while accounting for confounders and WLST.

Methods: This 2-center observational study included adults (≥18 years) with SE treated at the University Hospitals of Basel and Geneva from 2015 to 2023. Etiologies were classified as acute symptomatic, remote symptomatic-unprovoked, progressive CNS disorders, epilepsy without additional triggers, or cryptogenic. Demographics, SE type, SE severity score, Charlson Comorbidity Index, treatment data, complications, and WLST were assessed. The primary outcome was in-hospital mortality; secondary outcomes were 30-day mortality and recovery to premorbid neurologic function at discharge. Associations were assessed using Poisson regression with robust error variance, adjusted for age, nonconvulsive SE (NCSE) with coma, comorbidity, and center.

Results: Among 967 patients (median age 67 years, interquartile range 54-78; 46.5% female), SE was terminated in 95%, with 48.5% of patients recovering to premorbid function. Acute symptomatic SE accounted for 34.2%, remote symptomatic SE for 27.6%, SE due to progressive CNS disorders for 14.4%, epilepsy without additional triggers for 16.7%, and cryptogenic SE for 7.1%. In-hospital and 30-day mortality were 7.9% and 13.9%, respectively, while 48.5% recovered to premorbid function. Etiology was associated with neurologic recovery, with intracranial hemorrhage (relative risk [RR] 0.49, 95% CI 0.35-0.67) and acute symptomatic SE (RR 0.71, 95% CI 0.60-0.83) being associated with reduced likelihood of recovery, whereas known epilepsy was associated with increased likelihood of recovery (RR 1.40, 95% CI 1.23-1.60). NCSE with coma (11.9%) was independently associated with higher in-hospital and 30-day mortality and reduced recovery across all ILAE etiology groups. WLST did not significantly alter these associations.

Discussion: Etiology was associated with neurologic recovery but not with short-term mortality after adjustment for confounders and WLST. By contrast, NCSE with coma showed the strongest association with adverse outcomes. This suggests that while etiology informs prognosis for recovery, SE type, particularly NCSE with coma, is the more critical determinant of survival.

Background and objectives: Ischemic stroke remains a leading cause of death and disability worldwide, with large vessel occlusion (LVO) accounting for a disproportionate share of poststroke morbidity. Early identification of LVO is essential for timely intervention with endovascular thrombectomy; however, the clinical scales currently used for triage vary widely in their application and accuracy. This study assesses the diagnostic performance of clinical stroke scales in predicting LVO.

Methods: A systematic review was conducted to identify studies evaluating the diagnostic accuracy of prehospital stroke scales for detecting LVO. Pooled sensitivity and specificity were estimated using a bivariate random-effects model, with diagnostic performance further assessed through summary receiver operating characteristic (ROC) curves and area under the curve (AUC) analysis. A Bayesian network meta-analysis was conducted to rank the scales using surface under the cumulative ranking (SUCRA) probabilities, and post hoc analyses were performed to evaluate publication bias.

Results: A total of 58 studies comprising 58,381 patients and 33 unique stroke scales were included in the final analysis. The studies, published between 2014 and 2023, were primarily conducted in North America (50%) and Europe (26%), with a median sample size of 473 participants. Pooled sensitivity ranged from 0.30 (HEMIPARESIS) to 0.99 (LARIO) while specificity varied from 0.34 (FANG) to 0.94 (HEMIPLEGIA). Among the highest-performing scales overall were LARIO (AUC = 0.983), FPSS (AUC = 0.896), FACE2AD (AUC = 0.876), and ACT-FAST (AUC = 0.873). In prehospital settings, FPSS (AUC = 0.896), FAST VAN (AUC = 0.878), and FACE2AD (AUC = 0.876) demonstrated strong performance while LARIO (AUC = 0.983) and ACT-FAST (AUC = 0.883) showed the highest accuracy in hospital settings. Bayesian network meta-analysis identified POMONA (SUCRA = 0.877), NIHSS (0.856), sNIHSS EMS (0.854), G-FAST (0.823), and SAFE (0.788) as the top-ranked scales. Funnel plot analysis revealed minimal publication bias among the most frequently evaluated tools, including RACE, CPSS, and NIHSS.

Discussion: Numerous clinical scales are available for detecting LVO in the prehospital setting. While several demonstrate strong performance in specific contexts, there remains a clear need for a simple, accurate, and generalizable tool to reliably identify patients with LVO across diverse clinical environments.