Background: Cardiovascular (baroreflex) and respiratory (chemoreflex) control mechanisms were studied separately in diabetes, but their reciprocal interaction (well known for diseases like heart failure) had never been comprehensively assessed. We hypothesized that prevalent autonomic neuropathy would depress both reflexes, whereas prevalent autonomic imbalance through sympathetic activation would depress the baroreflex but enhance the chemoreflexes.
Methods: In 46 type-1 diabetic subjects (7.
Objective: The analysis of administrative health care data can be helpful to conveniently assess health care activities. In this context temporal data mining techniques can be suitably exploited to get a deeper insight into the processes underlying health care delivery. In this paper we present an algorithm for the extraction of temporal association rules (TARs) on sequences of hybrid events and its application on health care administrative databases.
View Article and Find Full Text PDFDiabetes care and chronic disease management represent data-intensive contexts which allow Local Healthcare Agencies (ASL) to collect a huge amount of information. Time is often an essential component of such information, given the strong importance of the temporal evolution of the considered disease and of its treatment. In this paper we show the application of a temporal data mining technique to extract temporal association rules over an integrated repository including both administrative and clinical data related to a sample of diabetic patients.
View Article and Find Full Text PDFGlycogen storage disease type II (GSDII) is an autosomal recessive myopathy caused by a deficiency of the lysosomal enzyme acid alpha-glucosidase (GAA). Enzyme replacement therapy (ERT) with recombinant GAA (rh-GAA) has become available for GSDII, although its effectiveness in adults remains unknown. We present a case of ERT with rhGAA in a 49-year-old male with GSDII in a severe stage of the disease.
View Article and Find Full Text PDFThe geographical analysis of a disease risk is particularly difficult when the disease is non-frequent and the area units are small. The practical use of the Bayesian modelling, instead of the classical frequentist one, is applied to study the geographical variation of multiple sclerosis (MS) across the province of Pavia, Northern Italy. 464 MS-affected individuals resident in the province of Pavia were identified on December 31st 2000.
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