Anti-Spike IgG antibodies as correlates of protection against SARS-CoV-2 infection in the pre-Omicron and Omicron era.

Anti-Spike IgG antibodies against SARS-CoV-2, which are elicited by vaccination and infection, are correlates of protection against infection with pre-Omicron variants. Whether this association can be generalized to infections with Omicron variants is unclear. We conducted a retrospective cohort study with 8457 blood donors in Tyrol, Austria, analyzing 15,340 anti-Spike IgG antibody measurements from March 2021 to December 2022 assessed by Abbott SARS-CoV-2 IgG II chemiluminescent microparticle immunoassay. Using a Bayesian joint model, we estimated antibody trajectories and adjusted hazard ratios for incident SARS-CoV-2 infection ascertained by self-report or seroconversion of anti-Nucleocapsid antibodies. At the time of their earliest available anti-Spike IgG antibody measurement (median November 23, 2021), participants had a median age of 46.0 years (IQR 32.8-55.2), with 45.3% being female, 41.3% having a prior SARS-CoV-2 infection, and 75.5% having received at least one dose of a COVID-19 vaccine. Among 6159 participants with endpoint data, 3700 incident SARS-CoV-2 infections with predominantly Omicron sublineages were recorded over a median of 8.8 months (IQR 5.7-12.4). The age- and sex-adjusted hazard ratio for SARS-CoV-2 associated with having twice the anti-Spike IgG antibody titer was 0.875 (95% credible interval 0.868-0.881) overall, 0.842 (0.827-0.856) during 2021, and 0.884 (0.877-0.891) during 2022 (all p < 0.001). The associations were similar in females and males (Pinteraction = 0.673) and across age (Pinteraction = 0.590). Higher anti-Spike IgG antibody titers were associated with reduced risk of incident SARS-CoV-2 infection across the entire observation period. While the magnitude of association was slightly weakened in the Omicron era, anti-Spike IgG antibody continues to be a suitable correlate of protection against newer SARS-CoV-2 variants.

Visualizing Nursing Narratives: An Evaluation of Latent Dirichlet Allocation Topic Modeling for Care Reports.

The increasing volume of unstructured textual data in healthcare, particularly in nursing care reports, presents both challenges and opportunities for enhancing patient care and operational efficiency. This study explores the application of Latent Dirichlet Allocation (LDA) topic modeling to analyze free-text nursing narratives from inpatient stays in three different clinics, aiming to uncover the latent thematic structures within. Utilizing the R programming environment and the visualization tool LDAvis, we identified three main themes: "Patient Well-being," "Patient Mobility and Care Activities," and "Treatment and Pain Management," the latter combining two closely related but initially distinct topics due to their overlapping content. Our findings demonstrate the potential of LDA topic modeling in extracting meaningful insights from nursing narratives, which could inform patient care strategies and healthcare practices. However, the study also highlights significant challenges associated with the method, including the sensitivity to parameter settings, the lack of updates for key software packages, and concerns about reproducibility. These issues highlight the need for meticulous parameter validation and the exploration of alternative text analysis methodologies for future research. By addressing these methodological challenges and emphasizing the importance of comparative method analysis, this study contributes to the advancement of text analytics in healthcare. It opens avenues for further research aimed at developing more robust, efficient, and accessible tools for analyzing free-text data, thereby enhancing the ability of healthcare professionals to use unstructured data to improve decision making and patient outcomes.

Smart FOX - Enabling Citizen-Based Donation of EHR-Standardised Data for Clinical Research in Austria.

Access to healthcare data for secondary use in clinical research is often restricted due to privacy concerns or business interests, hindering comprehensive analysis across patient pathways. The Smart FOX project seeks to address this challenge by developing concepts, methods, and tools to facilitate citizen/patient-driven donations of health data for clinical research. Leveraging the groundwork, laid by the national Electronic Health Record implementation in Austria (called ELGA), Smart FOX aims to harness structured datasets from ELGA for research purposes through an opt-in approach. With funding secured from the Austrian Research Promotion Agency, the project embarks on innovative solutions encompassing governance frameworks, community engagement, and technical infrastructure. The Smart FOX consortium, comprising key stakeholders across various healthcare-associated domains, will evaluate these efforts through demonstrators focusing on clinical registries, patient-generated data, and recruitment services. The project targets to accompany the development of future data donation infrastructure while ultimately advancing clinical research efficiency and bolstering Austria's preparedness for the European Health Data Space. This paper presents the first systematic evaluation of the technical concept and proposal for the federated system architecture of the Austrian Health Data Donation Space, which is the socio-technical goal of Smart FOX.

A Neuronal Network-Based Score Predicting Survival in Patients Undergoing Aortic Valve Intervention: The ABC-AS Score.

Background: Despite being the most commonly performed valvular intervention, risk prediction for aortic valve replacement in patients with severe aortic stenosis by currently used risk scores remains challenging. The study aim was to develop a biomarker-based risk score by means of a neuronal network. Methods: In this multicenter study, 3595 patients were divided into test and validation cohorts (70% to 30%) by random allocation. Input variables to develop the ABC-AS score were age, the cardiac biomarker high-sensitivity troponin T, and a patient history of cardiac decompensation. The validation cohort was used to verify the scores' value and for comparison with the Society of Thoracic Surgery Predictive Risk of Operative Mortality score. Results: Receiver operating curves demonstrated an improvement in prediction by using the ABC-AS score compared to the Society of Thoracic Surgery Predictive Risk of Operative Mortality (STS prom) score. Although the difference in predicting cardiovascular mortality was most notable at 30-day follow-up (area under the curve of 0.922 versus 0.678), ABC-AS also performed better in overall follow-up (0.839 versus 0.699). Furthermore, univariate analysis of ABC-AS tertiles yielded highly significant differences for all-cause (p < 0.0001) and cardiovascular mortality (p < 0.0001). Head-to-head comparison between both risk scores in a multivariable cox regression model underlined the potential of the ABC-AS score (HR per z-unit 2.633 (95% CI 2.156-3.216), p < 0.0001), while the STS prom score failed to reach statistical significance (p = 0.226). Conclusions: The newly developed ABC-AS score is an improved risk stratification tool to predict cardiovascular outcomes for patients undergoing aortic valve intervention.

Towards an Electronic Health Prevention Record Based on HL7 FHIR and the OMOP Common Data Model.

BACKGROUND: Approximately 40% of all recorded deaths in Austria are due to behavioral risks. These risks could be avoided with appropriate measures. OBJECTIVES: Extension of the concept of EHR and EMR to an electronic prevention record, focusing on primary and secondary prevention. METHODS: The concept of a structured prevention pathway, based on the principles of P4 Medicine, was developed for a multidisciplinary prevention network. An IT infrastructure based on HL7 FHIR and the OHDSI OMOP common data model was designed. RESULTS: An IT solution supporting a structured and modular prevention pathway was conceptualized. It contained a personalized management of prevention, risk assessment, diagnostic and preventive measures supported by a modular, interoperable IT infrastructure including a health app, prevention record web-service, decision support modules and a smart prevention registry, separating primary and secondary use of data. CONCLUSION: A concept was created on how an electronic health prevention record based on HL7 FHIR and the OMOP common data model can be implemented.

CareNet Tyrol - Information System Success Assessment for Case & Care Management Service.

BACKGROUND: CareNet is the IT-based tool for Case and Care Management (CCM) in Tyrol, which facilitates standardised documentation of CCM activities. OBJECTIVES: Analysing the pilot usage of CareNet Tyrol. METHODS: Evaluation of the success and user experience of CareNet, expert interviews and a questionnaire-based assessment. RESULTS: Feedback from users in both phases indicated that the CareNet platform provides general benefits, but falls short of fully supporting the daily work of CCM experts and avoiding the need for parallel use of different documentation tools. CONCLUSION: This paper provides an insight into the ongoing transition to digital documentation for CCM at LIV Tyrol. While user feedback highlights areas for improvement, digital documentation is proved to be beneficial for the CCM team.

HerzMobil Tirol PreOp - A Multidisciplinary Telemonitoring Project for Heart Failure Patients Prior to Cardiac Surgery.

BACKGROUND: Patients with heart failure are at risk of perioperative complications with elective cardiac surgery. OBJECTIVES: Conception of a multidisciplinary telemedicine-assisted optimisation project for high-risk patients prior to elective cardiac surgery. METHODS: Multidisciplinary concept design. RESULTS: A pilot-project for 30 patients was developed. CONCLUSION: Design of the first preoperative telemonitoring-assisted optimisation project for high-risk patients undergoing cardiac surgery.

Exploring Opportunities for Clinical Data Warehouse Enhancement Through Data Catalog Integration.

Secondary use of clinical health data implies a prior integration of mostly heterogenous and multidimensional data sets. A clinical data warehouse addresses the technological and organizational framework conditions required for this, by making any data available for analysis. However, users of a data warehouse often do not have a comprehensive overview of all available data and only know about their own data in their own systems - a situation which is also referred to as 'data siloed state'. This problem can be addressed and ultimately solved by implementation of a data catalog. Its core function is a search engine, which allows for searching the metadata collected from different data sources and thereby accessing all data there is. With this in mind, we conducted an explorative online market survey followed by vendor comparison as a pre-requisite for system selection of a data catalog. Assessment of vendor performance was based on seven predetermined and weighted selection criteria. Although three vendors achieved the highest score, results were lying closely together. Detailed investigations and test installations are needed for further narrowing down the selection process.

Understanding IT in Healthcare: Relevance and Training Needs of IT in Private Medical Practice.

BACKGROUND: The integration of Information Technology (IT) into private medical practice is crucial in modern healthcare. Physicians managing office-related IT without proper knowledge risk operational inefficiencies and security. OBJECTIVES: This study determines the relevance of specific IT topics in medical practice and identifies the training needs of physicians for enhancing IT competencies in healthcare. METHODS: In March 2023 a cross-sectional online survey was conducted with physicians comprising nine IT-related topics in Tyrol, Austria. RESULTS: The survey results highlighted a strong perceived relevance and high demand for IT education among physicians working in their medical practice, especially in areas of core medical IT and security. The majority of responses indicated high relevance (76.7%) and high demand (69.7%) for IT topics in medical practice. CONCLUSION: The findings underscore a significant need for targeted IT training and support in medical practices, particularly in areas related to the medical practice and security. Addressing these needs could lead to improved healthcare delivery and better management of technological resources in the healthcare sector.

Quality and Effectiveness of AI Tools for Students and Researchers for Scientific Literature Review and Analysis.

This study scrutinizes free AI tools tailored for supporting literature review and analysis in academic research, emphasizing their response to direct inquiries. Through a targeted keyword search, we cataloged relevant AI tools and evaluated their output variation and source validity. Our results reveal a spectrum of response qualities, with some tools integrating non-academic sources and others depending on outdated information. Notably, most tools showed a lack of transparency in source selection. Our study highlights two key limitations: the exclusion of commercial AI tools and the focus solely on tools that accept direct research queries. This raises questions about the potential capabilities of paid tools and the efficacy of combining various AI tools for enhanced research outcomes. Future research should explore the integration of diverse AI tools, assess the impact of commercial tools, and investigate the algorithms behind response variability. This study contributes to a better understanding of AI's role in academic research, emphasizing the importance of careful selection and critical evaluation of these tools in academic endeavors.

Unveiling the Surge: A Comprehensive Analysis of the Stimulating Impact of the Covid-19 Pandemic on Telemedicine and Its Academic Landscape.

The Covid-19 pandemic spurred an unprecedented shift towards digitalization, prompting a surge in telehealth practices. This paper explores the impact of the pandemic on telemedicine through a comprehensive analysis of scientific publications. Utilizing a bibliometric approach, the study examines trends in telemedicine research before and after the onset of Covid-19. The systematic search in PubMed yielded 8,454 pre-Covid-19 publications (2016-2019) and 16,633 post-Covid-19 publications (2020-2023). A total of 21,989 distinct keywords were extracted. Co-occurrence maps reveal evolving thematic clusters, with "mhealth" and "ehealth" dominating pre-Covid-19, while "Covid-19" emerges as a top keyword post-pandemic. The Top-10 keywords shift post-Covid-19, reflecting dynamic research priorities. The bibliometric approach illuminates a heightened exploration of telehealth solutions post-pandemic, emphasizing the enduring impact of the crisis on academic discourse. Changes in key terms and shifts in key term ranking indicate dynamic research priorities and a broader consideration of multidimensional healthcare challenges. Acknowledging study limitations, the analysis offers a high-level perspective, focusing on authors' keywords. Despite challenges, the study provides a systematic overview, revealing the emergence of new telemedicine application domains and the need for further in-depth analyses. Future research directions may explore the ecological impact of telemedicine applications and other intriguing aspects, contributing to a comprehensive understanding of telemedicine's scholarly trajectory.

Telemedicine for Ketogenic Dietary Treatment in Refractory Epilepsy and Inherited Metabolic Disease: State of Play and Future Perspectives.

Ketogenic dietary therapies (KDT) are diets that induce a metabolic condition comparable to fasting. All types of KDT comprise a reduction in carbohydrates whilst dietary fat is increased up to 90% of daily energy expenditure. The amount of protein is normal or slightly increased. KDT are effective, well studied and established as non-pharmacological treatments for pediatric patients with refractory epilepsy and specific inherited metabolic diseases such as Glucose Transporter Type 1 Deficiency Syndrome. Patients and caregivers have to contribute actively to their day-to-day care especially in terms of (self-) calculation and (self-) provision of dietary treatment as well as (self-) measurement of blood glucose and ketones for therapy monitoring. In addition, patients often have to deal with ever-changing drug treatment plans and need to document occurring seizures on a regular basis. With this review, we aim to identify existing tools and features of telemedicine used in the KDT context and further aim to derive implications for further research and development.

Health data space nodes for privacy-preserving linkage of medical data to support collaborative secondary analyses.

Introduction: The potential for secondary use of health data to improve healthcare is currently not fully exploited. Health data is largely kept in isolated data silos and key infrastructure to aggregate these silos into standardized bodies of knowledge is underdeveloped. We describe the development, implementation, and evaluation of a federated infrastructure to facilitate versatile secondary use of health data based on Health Data Space nodes. Materials and methods: Our proposed nodes are self-contained units that digest data through an extract-transform-load framework that pseudonymizes and links data with privacy-preserving record linkage and harmonizes into a common data model (OMOP CDM). To support collaborative analyses a multi-level feature store is also implemented. A feasibility experiment was conducted to test the infrastructures potential for machine learning operations and deployment of other apps (e.g., visualization). Nodes can be operated in a network at different levels of sharing according to the level of trust within the network. Results: In a proof-of-concept study, a privacy-preserving registry for heart failure patients has been implemented as a real-world showcase for Health Data Space nodes at the highest trust level, linking multiple data sources including (a) electronical medical records from hospitals, (b) patient data from a telemonitoring system, and (c) data from Austria's national register of deaths. The registry is deployed at the tirol kliniken, a hospital carrier in the Austrian state of Tyrol, and currently includes 5,004 patients, with over 2.9 million measurements, over 574,000 observations, more than 63,000 clinical free text notes, and in total over 5.2 million data points. Data curation and harmonization processes are executed semi-automatically at each individual node according to data sharing policies to ensure data sovereignty, scalability, and privacy. As a feasibility test, a natural language processing model for classification of clinical notes was deployed and tested. Discussion: The presented Health Data Space node infrastructure has proven to be practicable in a real-world implementation in a live and productive registry for heart failure. The present work was inspired by the European Health Data Space initiative and its spirit to interconnect health data silos for versatile secondary use of health data.

Anti-SARS-CoV-2 IgG Seroprevalence in Tyrol, Austria, among 28,768 Blood Donors between May 2022 and March 2023.

BACKGROUND: To provide updated estimates on SARS-CoV-2 antibody seroprevalence and average antibody titres for Central Europe. METHODS: In repeat cross-sectional investigations (1 May 2022 to 9 March 2023) involving 28,768 blood donors in the Federal State of Tyrol, Austria (participation rate: 87.0%), we measured Spike receptor-binding domain (RBD) and Nucleocapsid IgG antibodies (37,065 and 12,645 samples), and estimated monthly seroprevalences and geometric mean titres. RESULTS: Median age of participants was 45.4 years (range 18-70); 43.2% were female. Spike RBD IgG antibody seroprevalence was 96.3% (95% CI: 95.6-96.9%) in May 2022, 97.4% (96.7-98.0%) in December 2022, and 97.9% (96.4-98.8%) in March 2023. Among seropositive participants, geometric mean titres increased from 1400 BAU/mL (95% CI: 1333-1471) in May 2022 to 1821 BAU/mL (1717-1932) in December 2022, and dropped to 1559 BAU/mL (1405-1729) by March 2023. Furthermore, titres differed markedly by vaccination status and history of infection, with being the highest in participants with booster vaccination and prior infection. In autumn 2022, Nucleocapsid IgG antibody seroprevalence ranged from 36.5% (35.0-38.1) in September to 39.2% (37.2-41.2) in December 2022. CONCLUSION: Seroprevalence of SARS-CoV-2 antibodies in blood donors from Tyrol, Austria, was remarkably stable from May 2022 to March 2023. In contrast, average Spike RBD IgG antibody titres peaked in December 2022.

Penetrance, cancer incidence and survival in HFE haemochromatosis-A population-based cohort study.

BACKGROUND AND AIMS: Haemochromatosis is characterized by progressive iron overload affecting the liver and can cause cirrhosis and hepatocellular carcinoma. Most haemochromatosis patients are homozygous for p.C282Y in HFE, but only a minority of individuals with this genotype will develop the disease. The aim was to assess the penetrance of iron overload, fibrosis, hepatocellular carcinoma and life expectancy. METHODS: A total of 8839 individuals from the Austrian region of Tyrol were genotyped for the p.C282Y variant between 1997 and 2021. Demographic, laboratory parameters and causes of death were assessed from health records. Penetrance, survival, and cancer incidence were ascertained from diagnosed cases, insurance- and cancer registry data. Outcomes were compared with a propensity score-matched control population. RESULTS: Median age at diagnosis in 542 p.C282Y homozygous individuals was 47.8 years (64% male). At genotyping, the prevalence of iron overload was 55%. The cumulative penetrance of haemochromatosis defined as the presence of provisional iron overload was 24.2% in males and 10.5% in females aged 60 years or younger. Among p.C282Y homozygotes of the same ages, the cumulative proportion of individuals without fibrosis (FIB-4 score < 1.3) was 92.8% in males and 96.7% in females. Median life expectancy was reduced by 6.8 years in individuals homozygous for p.C282Y when compared with population-matched controls (p = .001). Hepatocellular carcinoma incidence was not significantly higher in p.C282Y homozygotes than in controls matched for age and sex. CONCLUSION: Reduced survival and the observed age-dependent increase in penetrance among p.C282Y homozygotes call for earlier diagnosis of haemochromatosis to prevent complications.

Transforming Clinical Information Systems: Empowering Healthcare through Telemedicine, Data Science, and Artificial Intelligence Applications.

OBJECTIVE: In this synopsis, the editors of the Clinical Information Systems (CIS) section of the IMIA Yearbook of Medical Informatics overview recent research and propose a selection of best papers published in 2022 in the CIS field. METHODS: The editors follow a systematic approach to gather relevant articles and select the best papers for the section. This year, they updated the query to incorporate the topic of telemedicine and removed search terms related to geographic information systems. The revised query resulted in a larger number of identified papers, necessitating the appointment of a third section editor to handle the increased workload. The editors narrowed the initial pool of articles to 15 candidate papers through a multi-stage selection process. At least seven independent reviews were collected for each candidate paper, and a selection meeting with the IMIA Yearbook editorial board led to the final selection of the best papers for the CIS section. RESULTS: The query was carried out in mid-January 2023 and retrieved a deduplicated result set of 5,206 articles from 1,500 journals. This year, 15 papers were nominated as candidates, and four were finally selected as the best papers in the CIS section.Including telemedicine in the query resulted in a substantial increase in the number of papers found. The analysis highlights the growing convergence between clinical information systems and telemedicine, with mobile health (mHealth) technologies and data science applications gaining prominence. The selected candidate papers emphasize the practical impact of research efforts, focusing on patient-centric outcomes and benefits, including intelligent mobile health monitoring systems and AI-assisted decision-making in healthcare. CONCLUSIONS: Looking ahead, the field of CIS is expected to continue evolving, driven by advances in telemedicine, mHealth technologies, data science, and AI integration, leading to more efficient, patient-oriented, and intelligent healthcare systems and overall improvement of global healthcare outcomes.

Impact of route of access and stenosis subtype on outcome after transcatheter aortic valve replacement.

Introduction: Previous analyses have reported the outcomes of transcatheter aortic valve replacement (TAVR) for patients with low-flow, low-gradient (LFLG) aortic stenosis (AS), without stratifying according to the route of access. Differences in mortality rates among access routes have been established for high-gradient (HG) patients and hypothesized to be even more pronounced in LFLG AS patients. This study aims to compare the outcomes of patients with LFLG or HG AS following transfemoral (TF) or transapical (TA) TAVR. Methods: A total of 910 patients, who underwent either TF or TA TAVR with a median follow-up of 2.22 (IQR: 1.22-4.03) years, were included in this multicenter cohort study. In total, 146 patients (16.04%) suffered from LFLG AS. The patients with HG and LFLG AS were stratified according to the route of access and compared statistically. Results: The operative mortality rates of patients with HG and LFLG were found to be comparable following TF access. The operative mortality rate was significantly increased for patients who underwent TA access [odds ratio (OR): 2.91 (1.54-5.48), p = 0.001] and patients with LFLG AS [OR: 2.27 (1.13-4.56), p = 0.02], which could be corroborated in a propensity score-matched subanalysis. The observed increase in the risk of operative mortality demonstrated an additive effect [OR for TA LFLG: 5.45 (2.35-12.62), p < 0.001]. LFLG patients who underwent TA access had significantly higher operative mortality rates (17.78%) compared with TF LFLG (3.96%, p = 0.016) and TA HG patients (6.36%, p = 0.024). Conclusions: HG patients experienced a twofold increase in operative mortality rates following TA compared with TF access, while LFLG patients had a fivefold increase in operative mortality rates. TA TAVR appears suboptimal for patients with LFLG AS. Prospective studies should be conducted to evaluate alternative options in cases where TF is not possible.

Distinct smell and taste disorder phenotype of post-acute COVID-19 sequelae.

PURPOSE: Olfactory dysfunction (OD) commonly accompanies coronavirus disease 2019 (COVID-19). We investigated the kinetics of OD resolution following SARS-CoV-2 infection (wild-type and alpha variant) and its impact on quality of life, physical and mental health. METHODS: OD prevalence was assessed in an ambulatory COVID-19 survey (n = 906, ≥ 90 days follow-up) and an observational cohort of ambulatory and hospitalized individuals (n = 108, 360 days follow-up). Co-occurrence of OD with other symptoms and effects on quality of life, physical and mental health were analyzed by multi-dimensional scaling, association rule mining and semi-supervised clustering. RESULTS: Both in the ambulatory COVID-19 survey study (72%) and the observational ambulatory and hospitalized cohort (41%) self-reported OD was frequent during acute COVID-19. Recovery from self-reported OD was slow (survey: median 28 days, observational cohort: 90 days). By clustering of the survey data, we identified a predominantly young, female, comorbidity-free group of convalescents with persistent OD and taste disorders (median recovery: 90 days) but low frequency of post-acute fatigue, respiratory or neurocognitive symptoms. This smell and taste disorder cluster was characterized by a high rating of physical performance, mental health, and quality of life as compared with convalescents affected by prolonged fatigue or neurocognitive complaints. CONCLUSION: Our results underline the heterogeneity of post-acute COVID-19 sequelae calling for tailored management strategies. The persistent smell and taste disorder phenotype is characterized by good clinical, physical, and mental recovery and may pose a minor challenge for public health. STUDY REGISTRATION: ClinicalTrials.gov: NCT04661462 (survey study), NCT04416100 (observational cohort).

Visualization of the SyncAV® Algorithm for CRT Optimization by Non-invasive Imaging of Cardiac Electrophysiology: NICE-CRT Trial.

(1) Background: Periodic repetitive AV interval optimization using a device-based algorithm in cardiac resynchronization therapy (CRT) devices may improve clinical outcomes. There is an unmet need to successfully transform its application into clinical routine. (2) Methods: Non-invasive imaging of cardiac electrophysiology was performed in different device programming settings of the SyncAV® algorithm in 14 heart failure patients with left bundle branch block and a PR interval ≤ 250 milliseconds to determine the shortest ventricular activation time. (3) Results: the best offset time (to be manually programmed) permitting automatic dynamic adjustment of the paced atrioventricular interval after every 256 heart beats was found to be 30 and 50 milliseconds, decreasing mean native QRS duration from 181.6 ± 23.9 milliseconds to 130.7 ± 10.0 and 130.1 ± 10.5 milliseconds, respectively (p = 0.01); this was followed by an offset of 40 milliseconds (decreasing QRS duration to 130.1 ± 12.2 milliseconds; p = 0.08). (4) Conclusions: The herein presented NICE-CRT study supports the current recommendation to program an offset of 50 milliseconds as default in patients with left bundle branch block and preserved atrioventricular conduction after implantation of a CRT device capable of SyncAV® optimization. Alternatively, offset programming of 30 milliseconds may also be applied as default programming. In patients with no or poor CRT response, additional efforts should be spent to individualize best offset programming with electrocardiographic optimization techniques.

Can virtual care reduce treatment burden in pediatric leukemia? A retrospective cost analysis.

We conducted a retrospective analysis to determine the potential reduction in treatment burden through the expansion of virtual care among children with leukemia (n = 152). Patients living in urban areas traveled median distances of 1555 km compared with 7536 km for patients living in rural areas (p < .05). For the latter group, a median reduction in travel distance of 3560 km (interquartile range [IQR], 2136-5787 km), travel time of 51 h (IQR, 26-78 h), and CO2 emissions of 623 kg (IQR, 374-1013 kg) was estimated, if every second visit was replaced by video consultations.