Contribution of rare chromosome 22q11.2 copy number variants to non-syndromic bicuspid aortic valve.

Background: Bicuspid aortic valve (BAV) is the most common congenital heart defect in adults, often leading to complications such as thoracic aortic aneurysms and aortic stenosis. While BAV is frequently associated with 22q11.2 deletion syndrome (22q11.

A socioeconomic and cost benefit analysis of Tropical Race 4 (TR4) prevention methods among banana producers in Colombia.

The global banana industry faces a significant threat from Fusarium oxysporum f. sp. cubense Tropical Race 4 (TR4).

Rare genomic copy number variants implicate new candidate genes for bicuspid aortic valve.

Bicuspid aortic valve (BAV), the most common congenital heart defect, is a major cause of aortic valve disease requiring valve interventions and thoracic aortic aneurysms predisposing to acute aortic dissections. The spectrum of BAV ranges from early onset valve and aortic complications (EBAV) to sporadic late onset disease. Rare genomic copy number variants (CNVs) have previously been implicated in the development of BAV and thoracic aortic aneurysms.

Creating High-Quality Synthetic Health Data: Framework for Model Development and Validation.

Background: Electronic health records are a valuable source of patient information that must be properly deidentified before being shared with researchers. This process requires expertise and time. In addition, synthetic data have considerably reduced the restrictions on the use and sharing of real data, allowing researchers to access it more rapidly with far fewer privacy constraints.

An evaluation of the replicability of analyses using synthetic health data.

Synthetic data generation is being increasingly used as a privacy preserving approach for sharing health data. In addition to protecting privacy, it is important to ensure that generated data has high utility. A common way to assess utility is the ability of synthetic data to replicate results from the real data.

Physical fitness in children with Marfan and Loeys-Dietz syndrome: associations between cardiovascular parameters, systemic manifestations, fatigue, and pain.

Children with Marfan (MFS) and Loeys-Dietz syndrome (LDS) report limitations in physical activities, sports, school, leisure, and work participation in daily life. This observational, cross-sectional, multicenter study explores associations between physical fitness and cardiovascular parameters, systemic manifestations, fatigue, and pain in children with MFS and LDS. Forty-two participants, aged 6-18 years (mean (SD) 11.

Evaluating the Utility and Privacy of Synthetic Breast Cancer Clinical Trial Data Sets.

Purpose: There is strong interest from patients, researchers, the pharmaceutical industry, medical journal editors, funders of research, and regulators in sharing clinical trial data for secondary analysis. However, data access remains a challenge because of concerns about patient privacy. It has been argued that synthetic data generation (SDG) is an effective way to address these privacy concerns.

Rare Genomic Copy Number Variants Implicate New Candidate Genes for Bicuspid Aortic Valve.

Bicuspid aortic valve (BAV), the most common congenital heart defect, is a major cause of aortic valve disease requiring valve interventions and thoracic aortic aneurysms predisposing to acute aortic dissections. The spectrum of BAV ranges from early onset valve and aortic complications (EBAV) to sporadic late onset disease. Rare genomic copy number variants (CNVs) have previously been implicated in the development of BAV and thoracic aortic aneurysms.

Evaluation of a nurse-led multi-component transition program for adolescents with congenital heart disease.

Objective: To evaluate the effectiveness of the transition program for adolescents with congenital heart disease (CHD) 'Transition With a Heart' (TWAH) on disease-related knowledge, quality of life (QoL), transition experiences, and gaps in follow-up.

Methods: A study with pre-posttest and control group (post-test) using consecutive sampling, including adolescents with moderate to severely complex CHD, without intellectual disability, aged≥ 12 y, and parents. After weighting, t-tests were performed.

Unraveling the role of TGFβ signaling in thoracic aortic aneurysm and dissection using Fbn1 mutant mouse models.

Although abnormal TGFβ signaling is observed in several heritable forms of thoracic aortic aneurysms and dissections including Marfan syndrome, its precise role in aortic disease progression is still disputed. Using a mouse genetic approach and quantitative isobaric labeling proteomics, we sought to elucidate the role of TGFβ signaling in three Fbn1 mutant mouse models representing a range of aortic disease from microdissection (without aneurysm) to aneurysm (without rupture) to aneurysm and rupture. Results indicated that reduced TGFβ signaling and increased mast cell proteases were associated with microdissection.

Preferences for disease-related information and transitional skills among adolescents with congenital heart disease in the early transitional stage.

Purpose: The transition towards adult-focused healthcare comprises a complex process requiring careful, individualized guidance of adolescents with congenital heart disease (CHD). Detailed data on their preferences regarding disease-related information and acquirable transitional skills are mostly lacking. We examined the preferences of CHD adolescents in the early transition stage.

A method for generating synthetic longitudinal health data.

Getting access to administrative health data for research purposes is a difficult and time-consuming process due to increasingly demanding privacy regulations. An alternative method for sharing administrative health data would be to share synthetic datasets where the records do not correspond to real individuals, but the patterns and relationships seen in the data are reproduced. This paper assesses the feasibility of generating synthetic administrative health data using a recurrent deep learning model.

[Obstacles to malaria elimination in Guapi-Cauca, Colombia].

Objetive: To explain the obstacles for malaria elimination in Guapi (Cauca, Colombia), considering the community perception.

Method: A qualitative, descriptive and exploratory research was carried out in Guapi, from October to November 2016, through the content analysis of eight female volunteer's focus groups. Inductive and interpretive analyses were also performed.

Validating a membership disclosure metric for synthetic health data.

Background: One of the increasingly accepted methods to evaluate the privacy of synthetic data is by measuring the risk of membership disclosure. This is a measure of the F1 accuracy that an adversary would correctly ascertain that a target individual from the same population as the real data is in the dataset used to train the generative model, and is commonly estimated using a data partitioning methodology with a 0.5 partitioning parameter.

Measuring re-identification risk using a synthetic estimator to enable data sharing.

Background: One common way to share health data for secondary analysis while meeting increasingly strict privacy regulations is to de-identify it. To demonstrate that the risk of re-identification is acceptably low, re-identification risk metrics are used. There is a dearth of good risk estimators modeling the attack scenario where an adversary selects a record from the microdata sample and attempts to match it with individuals in the population.

Using machine learning to predict individual patient toxicities from cancer treatments.

Purpose: Machine learning (ML) is a powerful tool for interrogating datasets and learning relationships between multiple variables. We utilized a ML model to identify those early breast cancer (EBC) patients at highest risk of developing severe vasomotor symptoms (VMS).

Methods: A gradient boosted decision model utilizing cross-sectional survey data from 360 EBC patients was created.

Utility Metrics for Evaluating Synthetic Health Data Generation Methods: Validation Study.

Background: A regular task by developers and users of synthetic data generation (SDG) methods is to evaluate and compare the utility of these methods. Multiple utility metrics have been proposed and used to evaluate synthetic data. However, they have not been validated in general or for comparing SDG methods.

Analysis approaches to address treatment nonadherence in pragmatic trials with point-treatment settings: a simulation study.

Background: Two-stage least square [2SLS] and two-stage residual inclusion [2SRI] are popularly used instrumental variable (IV) methods to address medication nonadherence in pragmatic trials with point treatment settings. These methods require assumptions, e.g.

"CUIDARAS " : A Nominal and Personalized Health Care Model. Effectiveness of a Massive Screening for Colorectal Cancer Detection at Community level.

Unlabelled: Health systems provides care only to those people who spontaneous demand for attention; excluding those who dont perceive illness or are not aware enough to consult. Alternative healthcare models based on the nominal-personalized care like "University Center for Integrated Care of Referred Health Care" (CUIDARAS) may have better results. In order to demonstrate benefits of this model, it was performed an experience based in colorectal cancer (CRC) detection and care that focused the entire population of the town.

Safety and Outcomes of using ureteric access sheath (UAS) for treatment of Pediatric renal stones: Outcomes from 2 tertiary endourology centers.

Objective: To look at the safety and outcomes of using ureteral access sheath (UAS) for pediatric renal stones. The use of UAS is variable in urological practice with very little clinical work on their use in pediatric kidney stone disease.

Patients And Methods: Data was retrospectively collected from 2 large European tertiary endourology centers for all pediatric patients (≤16 years) with renal stones who underwent flexible ureteroscopy and lasertripsy (FURSL) via UAS.