Background And Purpose: The benefit of endovascular thrombectomy (EVT) treatment is still unclear in stroke patients presenting with extensive baseline infarct. The use of additional imaging biomarkers could improve clinical outcome prediction and individualized EVT selection in this vulnerable cohort. We hypothesized that cerebral venous outflow (VO) may be associated with functional outcomes in patients with low Alberta Stroke Program Early CT Score (ASPECTS).
Methods: We conducted a retrospective multicenter cohort study of patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO). Extensive baseline infarct was defined by an ASPECTS of ≤5 on admission computed tomography (CT). VO profiles were assessed on admission CT angiography using the Cortical Vein Opacification Score (COVES). Favorable VO was defined as COVES ≥3. Multivariable logistic regression was used to determine the association between cerebral VO and good clinical outcomes (90-day modified Rankin Scale score of ≤3).
Results: A total of 98 patients met the inclusion criteria. Patients with extensive baseline infarct and favorable VO achieved significantly more often good clinical outcomes compared to patients with unfavorable VO (45.5% vs. 10.5%, P<0.001). Higher COVES were strongly associated with good clinical outcomes (odds ratio, 2.17; 95% confidence interval, 1.15 to 4.57; P=0.024), independent of ASPECTS, National Institutes of Health Stroke Scale, and success of EVT.
Conclusions: Cerebral VO profiles are associated with good clinical outcomes in AIS-LVO patients with extensive baseline infarct. VO profiles could serve as a useful additional imaging biomarker for treatment selection and outcome prediction in low ASPECTS patients.
Objective: Excess cholesterol loading on arterial macrophages is linked to foam cell formation, atherosclerosis and cardiovascular risk in rheumatoid arthritis (RA). However, the effect of changes in cholesterol loading on coronary plaque trajectory and the impact of RA therapies on this relationship are unknown. We investigated the association between variations in cholesterol loading capacity (CLC) over time and atherosclerosis progression.
Background: Patients with tuberculosis (TB) often harbor diverse bacteria in their sputum, including both commensal and opportunistic pathogens. This study aimed to characterize the sputum microbiota of TB patients before and after the intensive phase of anti-TB treatment and assess changes in bacterial diversity and antibiotic resistance profiles.
Methods: A total of 162 patients with TB (128 males, 34 females; age range 18-82 years) provided sputum samples at baseline, of which 72 provided follow-up sputum after two months of intensive phase treatment.
Background: Extensive experience with antidepressant clinical trials indicates that interrater reliability (IRR) must be maintained to achieve reliable clinical trial results. Contract research organizations have generally accepted 6 points of rating disparity between study site raters and central "master raters" as concordant, in part because of the personnel turnover and variability within many contract research organizations. We developed and tested an "insourced" model using a small, dedicated team of rater program managers (RPMs), to determine whether 3 points of disparity could successfully be demonstrated as a feasible standard for rating concordance.
Unlabelled: This study presents large-scale normative models of white matter (WM) organization across the lifespan, using diffusion MRI data from over 25,000 healthy individuals aged 0-100 years. These models capture lifespan trajectories and inter-individual variation in fractional anisotropy (FA), a marker of white matter integrity. By addressing non-Gaussian data distributions, race, and site effects, the models offer reference baselines across diverse ages, ethnicities, and scanning conditions.
Objective: While current multimodal approaches in the diagnosis and severity assessment of pneumonia demonstrate remarkable performance, they frequently overlook the issue of modality absence-a common challenge in clinical practice. Thus, we present the (RMT) model, crafted to bridge this gap. The RMT model aims to enhance diagnosis and severity assessment accuracy in situations with incomplete data, thereby ensuring it meets the complex needs of real-world clinical settings.
