The HeartQoL: Part I. Development of a new core health-related quality of life questionnaire for patients with ischemic heart disease

Background: Evaluation of health-related quality of life (HRQL) is important in improving the quality of patient care. Methods: The HeartQoL Project, with cross-sectional and longitudinal phases, was designed to develop a core ischemic heart disease (IHD) specific HRQL questionnaire, to be called the HeartQoL, for patients with angina, myocardial infarction (MI), or ischemic heart failure. Patients completed a battery of questionnaires and Mokken scaling analysis was used to identify items in the HeartQoL questionnaire. Results: We enrolled 6384 patients (angina, n = 2111, 33.1%; MI, n = 2351, 36.8%; heart failure, n = 1922, 30.1%) across 22 countries and 15 languages. The HeartQoL questionnaire comprises 14-items with 10-item physical and 4-item emotional subscales which are scored from 0 (poor HRQL) to 3 (better HRQL) with a global score if needed. The mean baseline HeartQoL global score was 2.2 (±0.5) in the total group and was different (p < 0.001) by diagnosis (MI, 2.4 ± 0.5; angina, 2.2 ± 0.6; and heart failure, 2.1 ± 0.6). Conclusion: The HeartQoL questionnaire, with global and subscale scores, has the potential to allow clinicians and researchers to (a) assess baseline HRQL, (b) make between-diagnosis comparisons of HRQL, and (c) evaluate change in HRQL in patients with angina, MI, or heart failure with a single IHD-specific HRQL instrument.

Walking near a conformal fixed point

We investigate the 2-d O(3) model with a q-term as a toy model for slowly walking 4-d non-Abelian gauge theories. Using the very efficient meron-cluster algorithm, an accurate investigation of the scale dependence of the renormalized coupling is carried out for different values of the vacuum angle q. Approaching q = p, the infrared dynamics of the 2-d O(3) model is determined by a non-trivial conformal fixed point. We provide evidence for a slowly walking behavior near the fixed point and we perform a finite-size scaling analysis of the mass gap.

Effect of smoking on the results of a chlorhexidine digluconate treatment extended up to 3 months after scaling and root planing-a pilot study

The aim of the study was to evaluate the impact of smoking on a prolongated chlorhexidine digluconate regimen after scaling and root planing. Forty-two smokers (test group) and 85 nonsmoking patients (control group) with generalized chronic periodontitis were examined for clinical attachment level (CAL), probing depth (PD), bleeding on probing (BoP), and Plaque Index (Pl) at baseline and after 1 and 3 months. During scaling and root planing, a 0.2% chlorhexidine digluconate solution and a 1% chlorhexidine digluconate gel were used. The subjects used a 0.2% chlorhexidine digluconate solution twice daily for 3 months. The Mann-Whitney U and Wilcoxon tests were used for statistical analysis. There were significant improvements of all studied variables after 1 and 3 months in both groups. After 3 months, the mean improvement in the test group was 1.62 mm for CAL, 2.85 mm for PD, and 48% for BoP; in the control group, the values were 2.18 mm for CAL, 2.81 mm for PD, and 47% for BoP. Only the maximum changes of CAL between 1 and 3 months (test group, 0.32 mm vs 0.69 mm in the control group) and PD (test group, 0.47 mm vs 0.76 mm in the control group) were significantly different between the groups (P < .05 and P = .05, respectively). The present data appear to suggest that the use of chlorhexidine digluconate twice daily during a period of 3 months following nonsurgical periodontal therapy may result in significant clinical improvements in smokers and nonsmokers.

Hyaluronic Acid as an Adjunct After Scaling and Root Planing - A Prospective Randomized Clinical Trial

Aim: The study was designed to determine the effect on clinical variables, subgingival bacteria and local immune response brought about by additional application of hyaluronan-containing gels in early wound healing after scaling and root planing (SRP). Material and Methods: In this randomised clinical study, data from 34 individuals with chronic periodontitis was evaluated after full-mouth SRP. In the test group (n = 17), hyaluronan gels in two molecular weights were additionally applied during the first two weeks after SRP. The control group (n = 17) was treated with SRP only. Probing depth (PD) and attachment level (AL) were recorded at baseline and after 3 and 6 months, and subgingival plaque and sulcus fluid samples were taken for microbiological and biochemical analysis. Results: In both groups, PD and AL were significantly reduced (p < 0.001). The changes in PD and the reduction of the numbers of pockets with PD ≥ 5mm were significantly higher in the test group after 3 (p = 0.014; p = 0.021) and 6 months (p = 0.046; p = 0.045). Six months after SRP, the counts of Treponema denticola were significantly reduced in both groups (both p = 0.043), those of Campylobacter rectus in the test group only (p = 0.028). Prevotella intermedia and Porphyromonas gingivalis increased in the control group. Conclusions: The adjunctive application of hyaluronan may have positive effects on probing depth reduction and may prevent recolonization by periodontopathogens.

Dynamic Optimization of SLA-Based Services Scaling Rules

Current advanced cloud infrastructure management solutions allow scheduling actions for dynamically changing the number of running virtual machines (VMs). This approach, however, does not guarantee that the scheduled number of VMs will properly handle the actual user generated workload, especially if the user utilization patterns will change. We propose using a dynamically generated scaling model for the VMs containing the services of the distributed applications, which is able to react to the variations in the number of application users. We answer the following question: How to dynamically decide how many services of each type are needed in order to handle a larger workload within the same time constraints? We describe a mechanism for dynamically composing the SLAs for controlling the scaling of distributed services by combining data analysis mechanisms with application benchmarking using multiple VM configurations. Based on processing of multiple application benchmarks generated data sets we discover a set of service monitoring metrics able to predict critical Service Level Agreement (SLA) parameters. By combining this set of predictor metrics with a heuristic for selecting the appropriate scaling-out paths for the services of distributed applications, we show how SLA scaling rules can be inferred and then used for controlling the runtime scale-in and scale-out of distributed services. We validate our architecture and models by performing scaling experiments with a distributed application representative for the enterprise class of information systems. We show how dynamically generated SLAs can be successfully used for controlling the management of distributed services scaling.

Explora: Infrastructure for Scaling Up Software Visualisation to Corpora

Visualisation provides good support for software analysis. It copes with the intangible nature of software by providing concrete representations of it. By reducing the complexity of software, visualisations are especially useful when dealing with large amounts of code. One domain that usually deals with large amounts of source code data is empirical analysis. Although there are many tools for analysis and visualisation, they do not cope well software corpora. In this paper we present Explora, an infrastructure that is specifically targeted at visualising corpora. We report on early results when conducting a sample analysis on Smalltalk and Java corpora.