Background Dementia affects people worldwide and its prevalence is growing. Early detection of dementia by primary care physicians can be beneficial; thus, their knowledge and attitudes about this issue are important. Objective To assess primary care physicians' knowledge and attitudes about the early detection of dementia in Hong Kong. Methods This was a mixed methods (qualitative and quantitative) study. Four focus groups with a purposive sample of 31 primary care physicians were interviewed, and a questionnaire-survey was completed and returned by 437 primary care physicians. Results Participants all agreed that the early detection of dementia would benefit patients and primary care physicians should be capable of making such diagnoses. Confidence in making an early diagnosis varied; physicians tended to overlook symptoms in the early stages. All agreed that more training is needed at the post-graduate level of medical education. Conclusions Participants had positive attitudes towards early detection of dementia; however, their confidence and ability to make an early diagnosis varied.
In this paper we introduce a method for runtime verification of the behavior of a system against state machines models in order to identify inconsistencies between the two. This is achieved by tracking states and transitions at runtime and comparing with the expected behavior of the system captured in the form of state machine models. The goal is to increase our confidence that the order of states at runtime matches what is specified by the models. The method also provides for defect localization by identifying that in the transition between which states a deviation from the expected behavior has occurred. The necessity and importance of the method lies in the fact that in model-based development, models are also used to perform analysis. Therefore, if there is any discrepancy between the behavior of the system at runtime and the models, then the result of model-based analyses which are performed may also be invalid and not applicable for the system anymore. For this purpose, in our method we create executable test cases from state machine models to test the runtime behavior of the system.
Background: Accurate prognostic awareness (PA) is essential for cancer patients to make informed end-of-life care plans. However, patients may not homogeneously develop accurate PA, and predictors of PA transition patterns have never been studied. We aimed to identify PA transition patterns and their predictors over cancer patients' last 6 months.Methods: PA was categorized into four states: (1) unknown and not wanting to know;(2) unknown but wanting to know; (3) inaccurate awareness; and (4) accurate awareness. Change patterns in PA states were identified by examining the first and last estimations by multistate Markov modeling during 332 cancer patients' last 6 months. Predictors of patients' distinct PA transition patterns were determined by multinomial logistic regression focused on lagged modifiable time-varying independent variables.Results: We identified four change patterns in PA states: maintaining accurate PA (56.6%), gaining accurate PA (20.5%), still wanting but inaccurate PA (7.2%), and still not wanting to know PA (15.7%). Physicians were more likely to disclose prognosis to the maintaining-accurate-PA group than other groups. Patients with more anxiety symptoms were less likely to be in the still-not-wanting to-know-PA group than in the maintaining-accurate-PA and gaining-accurate PA groups (adjusted odds ratio [95% confidence interval]¼AOR [95% CI]: 0.86 [0.76, 0.98] and 0.87 [0.76, 1.00], respectively). Patients with more social support (AOR [95% CI]: 0.94 [0.89, 0.99]) were less likely to be in the still-not-wanting to-know-PA group than in the maintaining-accurate-PA group. Patients with longer post-enrollment survival or higher educational levels were less likely to be in the still-not-wanting-to-know-PA group than in the gaining-accurate-PA group or the still-wanting but inaccurate-PA group, respectively.Conclusions: Most patients maintained or gained accurate PA before death, but about one-fourth of patients still wanted to know but had inaccurate PA or did not want to know PA. Modifiable factors like physicians' prognostic disclosure, and patients' anxiety symptoms and social support predicted distinct PA transition patterns over cancer patients' last 6 months.
We review our experience with patients harbouring putaminal intracerebral haematoma treated by intraoperative ultrasound guided aspiration and thrombolysis with Urokinase. We assessed the feasibility and safety of the procedure and compared the results with a similar group of patients previously treated in our unit by craniotomy and clot evacuation. From September 1998 to May 2000, eighteen consecutive patients with putaminal haemorrhage without suspected underlying structural aetiology or coagulopathy were included. Under general anesthesia, a catheter was inserted into the centre of the haematoma through a frontal burr hole under ultrasound guidance. An external ventricular catheter was also inserted for intracranial pressure monitoring. After maximally aspirating the haematoma, the catheter was left in place and 30 000 units of urokinase instilled. Further instillation of 20 000 units of urokinase was performed every 12 hours. The resolution of haematoma was followed with serial CT scan. The mean age was 55 years; mean haematoma size was 50 mL. The mortality rate was 11% (2/18); both deaths were not procedure related. Twenty-four patients were in the craniotomy; there were three deaths (13%). Other outcomes of the two groups were similar. We concluded that ultrasound guided aspiration and thrombolysis appears safe and effective in treating putaminal haemorrhage.Various methods and material have been used to treat cranium bifidum. We report the use of split calvarium bone graft in the treatment of the condition in a 3-year-old girl with a large bilateral parietooccipital defect. Early follow up reveals satisfactory results. 4.
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