Study objectives-To compare inhospital mortality for acute myocardial infarction (AMI) between metropolitan and nonmetropolitan hospitals after adjustment for patients' severity; to examine the role of the use of eVective cardiac medications in the possible mortality diVerence between these types of hospital. Design-Retrospective cohort study. Setting-47 acute public hospitals in metropolitan and non-metropolitan areas of New South Wales, Australia, taking part in the Acute Cardiac Care Project based on medical record review. Patients-1665 patients with principal discharge diagnosis of AMI from February to June 1996.Main results-There was no diVerence in crude mortality rate (assessed as seven day mortality) between metropolitan and non-metropolitan hospitals (11.0% compared with 10.7% respectively, p=0.893). After adjustment for severity in a logistic regression model, the odds of death in non-metropolitan hospitals was significantly higher than in metropolitan hospitals (odds ratio = 1.90; 95% CI 1.21, 3.23). The addition of the use of eVective cardiac medications to the model resulted in the diVerence between hospital type becoming non-significant (odds ratio=1.09; 95% CI 0.57, 2.07). Conclusions-Inhospital mortality in non-metropolitan hospitals was higher than that in metropolitan hospitals, after adjustment for patients' severity. This might partly be explained by the diVerence in use of eVective cardiac medications between hospital type. (J Epidemiol Community Health 2000;54:590-595)
The majority of reviewed studies found poorer male mortality outcome. A small number of studies maintained a null association between sex and mortality. This indicates male premature and LBW neonates experience higher risk of mortality by discharge compared with females, an observation which may inform clinical decision making in the NICU.
Rationale: In intracranial arterial dolichoectasia (IADE) development, the feedback loop between inflammatory cytokines and macrophages involves TNF-α and NF-κB signaling pathways and leads to subsequent MMP-9 activation and extracellular matrix (ECM) degeneration. In this proof-of-concept study, melittin-loaded L-arginine-coated iron oxide nanoparticle (MeLioN) was proposed as the protective measure of IADE formation for this macrophage-mediated inflammation and ECM degeneration. Methods: IADE was created in 8-week-old C57BL/6J male mice by inducing hypertension and elastase injection into a basal cistern. Melittin was loaded on the surface of ION as a core-shell structure (hydrodynamic size, 202.4 nm; polydispersity index, 0.158). Treatment of MeLioN (2.5 mg/kg, five doses) started after the IADE induction, and the brain was harvested in the third week. In the healthy control, disease control, and MeLioN-treated group, the morphologic changes of the cerebral arterial wall were measured by diameter, thickness, and ECM composition. The expression level of MMP-9, CD68, MCP-1, TNF-α, and NF-κB was assessed from immunohistochemistry, polymerase chain reaction, and Western blot assay. Results: MeLioN prevented morphologic changes of cerebral arterial wall related to IADE formation by restoring ECM alterations and suppressing MMP-9 expression. MeLioN inhibited MCP-1 expression and reduced CD68-positive macrophage recruitments into cerebral arterial walls. MeLioN blocked TNF-α activation and NF-κB signaling pathway. In the Sylvian cistern, co-localization was found between the CD68-positive macrophage infiltrations and the MeLioN distributions detected on Prussian Blue and T2* gradient-echo MRI, suggesting the role of macrophage harboring MeLioN. Conclusions:The macrophage infiltration into the arterial wall plays a critical role in the MMP-9 secretion. MeLioN, designed for ION-mediated melittin delivery, effectively prevents IADE formation by suppressing macrophage-mediated inflammations and MMP activity. MeLioN can be a promising strategy preventing IADE development in high-risk populations.
The aim of this study was to compare the performance of a deep-learning convolutional neural network (Faster R-CNN) model to detect imaging findings suggestive of idiopathic Parkinson’s disease (PD) based on [18F]FP-CIT PET maximum intensity projection (MIP) images versus that of nuclear medicine (NM) physicians. The anteroposterior MIP images of the [18F]FP-CIT PET scan of 527 patients were classified as having PD (139 images) or non-PD (388 images) patterns according to the final diagnosis. Non-PD patterns were classified as overall-normal (ONL, 365 images) and vascular parkinsonism with definite defects or prominently decreased dopamine transporter binding (dVP, 23 images) patterns. Faster R-CNN was trained on 120 PD, 320 ONL, and 16 dVP pattern images and tested on the 19 PD, 45 ONL, and seven dVP patterns images. The performance of the Faster R-CNN and three NM physicians was assessed using receiver operating characteristics curve analysis. The difference in performance was assessed using Cochran’s Q test, and the inter-rater reliability was calculated. Faster R-CNN showed high accuracy in differentiating PD from non-PD patterns and also from dVP patterns, with results comparable to those of NM physicians. There were no significant differences in the area under the curve and performance. The inter-rater reliability among Faster R-CNN and NM physicians showed substantial to almost perfect agreement. The deep-learning model accurately differentiated PD from non-PD patterns on MIP images of [18F]FP-CIT PET, and its performance was comparable to that of NM physicians.
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