War-Affected Children and Youth in Northern Uganda: Toward a Brighter Future

Examines current efforts by international organizations and local communities to aid children and youth living in internally displaced camps. Identifies programs to improve health care, education, economic activities, and justice and amnesty mechanisms

When the War Ends: A Population-Based Survey on Attitudes About Peace, Justice and Social Reconstruction in Northern Uganda

Analyzes survey findings on northern Ugandans' displacement and resettlement as well as views on peace, justice, and social reconstruction during peace talks between the Ugandan government and the Lord Resistance Army. Includes recommendations

RELEASE-HF study:a protocol for an observational, registry-based study on the effectiveness of telemedicine in heart failure in the Netherlands

Introduction:Meta-analyses show postive effects of telemedicine in heart failure (HF) management on hospitalisation, mortality and costs. However, these effects are heterogeneous due to variation in the included HF population, the telemedicine components and the quality of the comparator usual care. Still, telemedicine is gaining acceptance in HF management. The current nationwide study aims to identify (1) in which subgroup(s) of patients with HF telemedicine is (cost-)effective and (2) which components of telemedicine are most (cost-) effective. Methods and analysis:The RELEASE-HF ('REsponsible roLl-out of E-heAlth through Systematic Evaluation -Heart Failure') study is a multicentre, observational, registry-based cohort study that plans to enrol 6480 patients with HF using data from the HF registry facilitated by the Netherlands Heart Registration. Collected data include patient characteristics, treatment information and clinical outcomes, and are measured at HF diagnosis and at 6 and 12 months afterwards. The components of telemedicine are described at the hospital level based on closed-ended interviews with clinicians and at the patient level based on additional data extracted from electronic health records and telemedicine-generated data. The costs of telemedicine are calculated using registration data and interviews with clinicians and finance department staff. To overcome missing data, additional national databases will be linked to the HF registry if feasible. Heterogeneity of the effects of offering telemedicine compared with not offering on days alive without unplanned hospitalisations in 1 year is assessed across predefined patient characteristics using exploratory stratified analyses. The effects of telemedicine components are assessed by fitting separate models for component contrasts. Ethics and dissemination:The study has been approved by the Medical Ethics Committee 2021 of the University Medical Center Utrecht (the Netherlands). Results will be published in peer-reviewed journals and presented at (inter)national conferences. Effective telemedicine scenarios will be proposed among hospitals throughout the country and abroad, if applicable and feasible.</p

RELEASE-HF study:a protocol for an observational, registry-based study on the effectiveness of telemedicine in heart failure in the Netherlands

Introduction:Meta-analyses show postive effects of telemedicine in heart failure (HF) management on hospitalisation, mortality and costs. However, these effects are heterogeneous due to variation in the included HF population, the telemedicine components and the quality of the comparator usual care. Still, telemedicine is gaining acceptance in HF management. The current nationwide study aims to identify (1) in which subgroup(s) of patients with HF telemedicine is (cost-)effective and (2) which components of telemedicine are most (cost-) effective. Methods and analysis:The RELEASE-HF ('REsponsible roLl-out of E-heAlth through Systematic Evaluation -Heart Failure') study is a multicentre, observational, registry-based cohort study that plans to enrol 6480 patients with HF using data from the HF registry facilitated by the Netherlands Heart Registration. Collected data include patient characteristics, treatment information and clinical outcomes, and are measured at HF diagnosis and at 6 and 12 months afterwards. The components of telemedicine are described at the hospital level based on closed-ended interviews with clinicians and at the patient level based on additional data extracted from electronic health records and telemedicine-generated data. The costs of telemedicine are calculated using registration data and interviews with clinicians and finance department staff. To overcome missing data, additional national databases will be linked to the HF registry if feasible. Heterogeneity of the effects of offering telemedicine compared with not offering on days alive without unplanned hospitalisations in 1 year is assessed across predefined patient characteristics using exploratory stratified analyses. The effects of telemedicine components are assessed by fitting separate models for component contrasts. Ethics and dissemination:The study has been approved by the Medical Ethics Committee 2021 of the University Medical Center Utrecht (the Netherlands). Results will be published in peer-reviewed journals and presented at (inter)national conferences. Effective telemedicine scenarios will be proposed among hospitals throughout the country and abroad, if applicable and feasible.</p

Contemporary guideline-directed medical therapy in de novo, chronic, and worsening heart failure patients:First data from the TITRATE-HF study

Aims: Despite clear guideline recommendations for initiating four drug classes in all patients with heart failure (HF) with reduced ejection fraction (HFrEF) and the availability of rapid titration schemes, information on real-world implementation lags behind. Closely following the 2021 ESC HF guidelines and 2023 focused update, the TITRATE-HF study started to prospectively investigate the use, sequencing, and titration of guideline-directed medical therapy (GDMT) in HF patients, including the identification of implementation barriers. Methods and results: TITRATE-HF is an ongoing long-term HF registry conducted in the Netherlands. Overall, 4288 patients from 48 hospitals were included. Among these patients, 1732 presented with de novo, 2240 with chronic, and 316 with worsening HF. The median age was 71 years (interquartile range [IQR] 63–78), 29% were female, and median ejection fraction was 35% (IQR 25–40). In total, 44% of chronic and worsening HFrEF patients were prescribed quadruple therapy. However, only 1% of HFrEF patients achieved target dose for all drug classes. In addition, quadruple therapy was more often prescribed to patients treated in a dedicated HF outpatient clinic as compared to a general cardiology outpatient clinic. In each GDMT drug class, 19% to 36% of non-use in HFrEF patients was related to side-effects, intolerances, or contraindications. In the de novo HF cohort, 49% of patients already used one or more GDMT drug classes for other indications than HF. Conclusion: This first analysis of the TITRATE-HF study reports relatively high use of GDMT in a contemporary HF cohort, while still showing room for improvement regarding quadruple therapy. Importantly, the use and dose of GDMT were suboptimal, with the reasons often remaining unclear. This underscores the urgency for further optimization of GDMT and implementation strategies within HF management.</p

Contemporary guideline-directed medical therapy in de novo, chronic, and worsening heart failure patients: First data from the TITRATE-HF study

AIMS: Despite clear guideline recommendations for initiating four drug classes in all patients with heart failure (HF) with reduced ejection fraction (HFrEF) and the availability of rapid titration schemes, information on real-world implementation lags behind. Closely following the 2021 ESC HF guidelines and 2023 focused update, the TITRATE-HF study started to prospectively investigate the use, sequencing, and titration of guideline-directed medical therapy (GDMT) in HF patients, including the identification of implementation barriers. METHODS AND RESULTS: TITRATE-HF is an ongoing long-term HF registry conducted in the Netherlands. Overall, 4288 patients from 48 hospitals were included. Among these patients, 1732 presented with de novo, 2240 with chronic, and 316 with worsening HF. The median age was 71 years (interquartile range [IQR] 63-78), 29% were female, and median ejection fraction was 35% (IQR 25-40). In total, 44% of chronic and worsening HFrEF patients were prescribed quadruple therapy. However, only 1% of HFrEF patients achieved target dose for all drug classes. In addition, quadruple therapy was more often prescribed to patients treated in a dedicated HF outpatient clinic as compared to a general cardiology outpatient clinic. In each GDMT drug class, 19% to 36% of non-use in HFrEF patients was related to side-effects, intolerances, or contraindications. In the de novo HF cohort, 49% of patients already used one or more GDMT drug classes for other indications than HF. CONCLUSION: This first analysis of the TITRATE-HF study reports relatively high use of GDMT in a contemporary HF cohort, while still showing room for improvement regarding quadruple therapy. Importantly, the use and dose of GDMT were suboptimal, with the reasons often remaining unclear. This underscores the urgency for further optimization of GDMT and implementation strategies within HF management

DETECTING PATTERNS IN OBJECT-ORIENTED SOURCE CODE – A CASE STUDY

Abstract: Pattern detection methods discover recurring solutions in a system’s implementation, for example design patterns in object-oriented source code. Usually this is done with a pattern library. This has the disadvantage that the precise implementation of the patterns must be known in advance. The method used in our case study does not have this disadvantage. It uses a mathematical technique called Formal Concept Analysis and is applied to find structural patterns in two subsystems of a printer controller. The case study shows that it is possible to detect frequently used structural design constructs without upfront knowledge. However, even the detection of relatively simple patterns in relatively small pieces of software takes a lot of computing time. Since this is due to the complexity of the applied algorithms, applying the method to large software systems like the complete controller is not practical. They can be applied to its subsystems though, which are about five to ten percent of its size

Pattern detection in object-oriented source code

Pattern detection methods discover recurring solutions, like design patterns in object-oriented source code. Usually this is done with a pattern library. Hence, the precise implementation of the patterns must be known in advance. The method used in our case study does not have this disadvantage. It uses a mathematical technique, Formal Concept Analysis, and is applied to find structural patterns in two subsystems of a printer controller. The case study shows that it is possible to detect frequently used structural design constructs without upfront knowledge. However, even the detection of relatively simple patterns in relatively small pieces of software takes a lot of computing time. Since this is due to the complexity of the applied algorithms, applying the method to large software systems like the complete controller is not practical. It can be applied to its subsystems though, which are about 5-10% of its size.</p

Using Version Information in Architectural Clustering – A Case Study

This paper describes a case study that uses clustering to group classes of an existing objectoriented system of significant size into subsystems. The clustering process is based on the structural relations between the classes: associations, generalizations and dependencies. We experiment with different combinations of relationships and different ways to use this information in the clustering process. The results clearly show that dependency relations are vital to achieve good clusterings. The clustering is performed with a third party tool called Bunch. Compared to other clustering methods the results come relatively close to the result of a manual reconstruction. Performance wise the clustering takes a significant amount of time, but not too much to make it unpractical. In our case study, we base the clustering on information from multiple versions and compare the result to that obtained when basing the clustering on a single version. We experiment with several combinations of versions. If the clustering is based on relations that were present in both the reconstructed and the first version this leads to a significantly better clustering result compared to that obtained when using only information from the reconstructed version. 1