Objective We seek to identify potentially modifiable determinants associated with variability in leptomeningeal collateral status in patients with acute ischemic stroke. Methods Data are from the Keimyung Stroke Registry. Consecutive patients with M1 segment middle cerebral artery (MCA) ± intracranial internal carotid artery (ICA) occlusions on baseline CT-angiography (CTA) from May 2004 to July 2009 were included. Baseline and follow-up imaging was analyzed blinded to all clinical information. Two raters assessed leptomeningeal collaterals on baseline CTA by consensus, using a previously validated regional leptomeningeal score (rLMC). Results Baseline characteristics (n=206) were: mean age 66.9±11.6 years, median baseline NIHSS 14 (IQR 11-20), and median stroke symptom onset to CTA 166 minutes (IQR 96-262), Poor collateral status at baseline (rLMC score 0-10) was seen in 73/206 (35.4%). On univariate analyses, patients with poor collateral status at baseline were older, hypertensive, had higher white blood cell count, blood glucose, D-dimer, serum uric acid levels, and were more likely to have metabolic syndrome. Multivariable modeling identified metabolic syndrome (OR 3.22 95% CI 1.69-6.15, p<0.001), hyperuricemia (per 1 mg/dl OR 1.35 95% CI 1.12-1.62, p<0.01) and older age (per 10 years, OR 1.34 95% CI 1.02-1.77, p=0.03) as independent predictors of poor leptomeningeal collateral status at baseline. Conclusion Metabolic syndrome, hyperuricemia and age are associated with poor leptomeningeal collateral status in patients with acute ischemic stroke.
BACKGROUND AND PURPOSE:Collateral status at baseline is an independent determinant of clinical outcome among patients with acute ischemic stroke. We sought to identify whether the association between recanalization after intra-arterial acute stroke therapy and favorable clinical response is modified by the presence of good collateral flow assessed on baseline CTA.
To assess the effects of slaughter weight and sex on APGS (Animal Products Grading Service) quality and APGS yield grade of Korean Hanwoo (n = 20,881) cattle, data were collected from cow, bull, and steer carcasses during a 1-yr period. Factors used to determine quality grade (marbling, meat color, fat color, texture, and overall maturity score) and yield grade (cold carcass weight, adjusted fat thickness, and longissimus muscle area) by the Korean grading system were recorded. Both yield and quality grades were improved (P < 0.01) with heavier slaughter weight, but there was no difference in yield grade for Hanwoo cattle classes heavier than 551 kg (P > 0.01). Longissimus muscle area, adjusted fat thickness, and marbling score increased (P < 0.01) with carcass weight. Bull carcasses showed higher yield but lower quality than those of cows or steers (P < 0.01). The quality grade of steer carcasses was higher (P < 0.01) than that of cow carcasses due to higher marbling scores, lower maturity scores, and heavier carcass weights. Hanwoo carcasses with larger longissimus muscle areas in relation to their carcass weight had lower APGS quality grades. The APGS quality grades were different between yield grade A and B carcasses (P < 0.01), but quality grade was not improved by increased fat thickness beyond the point of yield grade B. Adjusted fat thickness and marbling score showed significant (P < 0.01) differences among all yield grade classes, and this resulted in increased quality grade as yield grade decreased. Adjusted fat thickness showed the strongest correlation (r = -0.63) with yield grade, whereas marbling score had the strongest correlation (r = 0.81) with quality grade. Results showed a negative effect of castration on yield but a positive effect on quality. Also, data showed that Hanwoo carcasses with heavier weights had higher quality grades than those of lighter weight.
Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. Further, respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this study, we propose an efficient data mining solution for the detection and recognition of pig wasting diseases using sound data in audio surveillance systems. In this method, we extract the Mel Frequency Cepstrum Coefficients (MFCC) from sound data with an automatic pig sound acquisition process, and use a hierarchical two-level structure: the Support Vector Data Description (SVDD) and the Sparse Representation Classifier (SRC) as an early anomaly detector and a respiratory disease classifier, respectively. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (even a cheap microphone can be used) and accurately (94% detection and 91% classification accuracy), either as a standalone solution or to complement known methods to obtain a more accurate solution.
Periodontal disease is a potential predictor of stroke and cognitive impairment. However, this association is unclear in adults aged 50 yr and above without a history of stroke or dementia. We evaluated the association between the number of teeth lost, indicating periodontal disease, and cognitive impairment in community-dwelling adults without any history of dementia or stroke. Dental examinations were performed on 438 adults older than 50 yr (315 females, mean age 63 ± 7.8 yr; 123 males, mean age 61.5 ± 8.5 yr) between January 2009 and December 2010. In the unadjusted analysis, odds ratios (OR) of cognitive impairment based on MMSE score were 2.46 (95% CI, 1.38-4.39) and 2.7 (95% CI, 1.57-4.64) for subjects who had lost 6-10 teeth and those who had lost more than 10 teeth, respectively, when compared with subjects who had lost 0-5 teeth. After adjusting for age, education level, hypertension, diabetes, hyperlipidemia, and smoking, the relationship remained significant (OR, 2.0; 95% CI, 1.08-3.69, P = 0.027 for those with 6-10 teeth lost; OR, 2.26; 95% CI, 1.27-4.02, P = 0.006 for those with more than 10 teeth lost). The number of teeth lost is correlated with cognitive impairment among community-dwelling adults aged 50 and above without any medical history of stroke or dementia.
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