1,720,971 research outputs found
Mining Health Care Administrative Data with Temporal Association Rules on Hybrid Events
No full textObjective: 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. Methods: We propose a method that extends TAR mining by managing hybrid events, namely events characterized by a heterogeneous temporal nature. Hybrid events include both point-like events (e.g. ambulatory visits) and interval-like events (e.g. drug consumption). The definition of user-defined rule templates can be optionally used to constrain the search only to the extraction of a subset of interesting rules. A TAR post-pruning strategy, based on a case-control approach, is also presented. Results: We analyzed the administrative database of diabetic patients in charge to the regional health care agency (ASL) of Pavia. TAR mining allowed to find patterns specifically related to the diabetic population in comparison with a control group, as well as to check the compliance of the actual clinical careflow with the ASL recommendations. Conclusion: The experimental results highlighted the main potentials of the algorithm, such as the opportunity to detect interesting temporal relationships between diagnostic or therapeutic patterns, or to check the adherence of past temporal behaviors to specific expected paths (e.g. guidelines) or to discover new knowledge that could be implicitly hidden in the data
Lipoprotein(a), apolipoprotein(a) polymorphism and coronary atherosclerosis severity in type 2 diabetic patients
No full textAbstract: Background: Few and conflicting data are available in the literature on the association between Lp(a) levels and the severity of coronary artery disease (CAD) in diabetic patients. In addition, no studies took into account the role of apo(a) polymorphism. The purpose of the present study was to analyse the association of the degree of coronary atherosclerosis with Lp(a) levels and apo(a) polymorphism in a large group of type 2 diabetic patients.
Methods: The study population consisted of 227 consecutive type 2 diabetic patients undergoing a routine coronary angiography to evaluate chest pain or suspected CAD. The patients were subdivided into four subgroups according to the number of coronary arteries diseased: normal arteries (n = 26), mono-vessel disease (n = 67), bi-vessel disease (n = 54) and multi-vessel disease (n = 80).
Results: Lp(a) levels (normal arteries: 14.6 +/- 19.6 mg/dl; mono-vessel disease: 19.0 +/- 16.4 mg/dl; bi-vessel disease: 19.3 +/- 15.1 mg/dl; multi-vessel disease: 26.5 +/- 16.8 mg/dl; p < 0.001) and the percentages of patients with at least one isoform of low molecular weight (normal arteries: 23.1%; mono-vessel disease: 38.8%; bi-vessel disease: 75.9%; multi-vessel disease: 81.2%; p < 0.001) were significantly correlated with increasing number of coronary vessels diseased. Multiple logistic regression analysis showed that both Lp(a) levels (OR: 1.31; 95% CI: 1.02-4.11) and apo(a) polymorphism (OR: 3.43; 95% CI: 1.67-7.05) were independent predictors of CAD severity.
Conclusions: Our data suggest that Lp(a) levels and apo(a) polymorphism may be reliable predictors of CAD severity in type 2 diabetic patients
Mining healthcare data with temporal association rules: Improvements and assessment for a practical use
No full textRestenosis after intracoronary stent placement: can apolipoprotein(a) polymorphism play a role?
No full textThe relationship between lipoprotein(a) and restenosis after intracoronary stent implantation has been analysed by two specific studies, but the role of apoliprotein(a) polymorphism was not considered. The aim of the present prospective study was to evaluate whether lipoprotein(a) levels and apolipoprotein(a) phenotypes are predictors of restenosis after elective stent implantation in patients with de novo lesions of coronary arteries.
METHODS:
We recruited 182 patients with a new lesion successfully treated with elective placement of one or two Palmaz-Schatz stents. Follow-up angiography was scheduled at 6 months or earlier if clinically indicated. Nine patients were lost to the follow up. Among 173 patients enrolled, restenosis was present in 52 (30.0%) and absent in 121 (70.0%).
RESULTS:
Lipoprotein(a) levels were higher in the restenosis than in the nonrestenosis group (29.5+/-17.2 versus 27.4+/-20.2 mg/dl), even if the difference did not attain statistical significance (P=0.067). The restenosis group had a percentage of subjects with at least one apolipoprotein(a) isoform of low molecular weight significantly greater than the nonrestenosis group (82.7 versus 66.9%; P=0.035). A multiple logistic regression analysis showed that multiple stenting (RR: 4.01; CI 95%: 1.65-13.91; P=0.004), presence of diabetes (RR: 3.96; CI 95%: 1.67-9.37; P=0.002) and presence of multivessel disease (RR: 2.71; CI 95%: 1.19-6.16; P=0.017) were predictors of restenosis after stent placement. Lipoprotein(a) and apolipoprotein(a) polymorphism did not enter the model as predictive variables.
CONCLUSIONS:
Our study confirms that multiple stenting, diabetes and multivessel disease are powerful predictors of restenosis after intracoronary stent implantation. On the contrary, lipoprotein(a) and apolipoprotein(a) polymorphism do not appear to be reliable markers of restenosis in patients with stent implantation
Temporal data mining for the assessment of the costs related to diabetes mellitus pharmacological treatment
No full textAssociation of lipoprotein(a) levels and apolipoprotein(a) phenotypes with coronary artery disease in Type 2 diabetic patients and in non-diabetic subjects
No full textAssociation between apolipoprotein(a) phenotypes and coronary heart disease at a young age.
No full textApolipoprotein(a) phenotypes and their predictive value for coronary heart disease: identification of an operative cut-off of apolipoprotein(a) polymorphism.
No full textApolipoprotein(a) isoforms of low-molecular weight are associated with coronary heart disease. However, because of the high number of apolipoprotein(a) isoforms, it is difficult to assess the cardiovascular risk linked to the apolipoprotein(a) gene of a subject; indeed a cut-off of apolipoprotein(a) polymorphism has not been established. The aim of this investigation was to identify an 'operative' cut-off that discriminates apolipoprotein(a) isoforms associated with high genetic risk for coronary heart disease.
Two hundred and fifty-one patients with coronary heart disease and 284 controls were recruited. Apolipoprotein(a) isoforms were detected using a high-resolution phenotyping method.
Twenty-seven apolipoprotein(a) isoforms with apparent molecular weight varying from 280 to 820 kDa were identified. Several cut-offs of apolipoprotein(a) polymorphism were used in order to compare the frequencies of apolipoprotein(a) isoforms of low and high molecular weight between patients and controls: the cut-off between 640 and 655 kDa had the highest chi 2 (130.40). Even when possible differences in apolipoprotein(a) phenotypes (subjects with at least one isoform of low molecular weight and subjects with only isoforms of high molecular weight) were assessed, the same cut-off showed the highest chi 2 (122.47). Multivariate analysis showed that apolipoprotein (a) isoforms had the greatest predictive value for coronary heart disease (F value = 107.0720), when the cut-off between 640 and 655 kDa was used.
The cut-off between 640 and 655 kDa appears to be the most efficient in identifying subjects at high cardiovascular risk linked to apolipoprotein(a) gene, since this cut-off discriminates apolipoprotein(a) isoforms expressing a greater risk for coronary heart disease
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