Implications of ACC/AHA Versus ESC/EAS LDL-C Recommendations for Residual Risk Reduction in ASCVD: A Simulation Study From DA VINCI

© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.[Purpose] Low-density lipoprotein cholesterol (LDL-C) recommendations differ between the 2018 American College of Cardiology/American Heart Association (ACC/AHA) and 2019 European Society of Cardiology/European Atherosclerosis Society (ESC/EAS) guidelines for patients with atherosclerotic cardiovascular disease (ASCVD) (< 70 vs. < 55 mg/dl, respectively). In the DA VINCI study, residual cardiovascular risk was predicted in ASCVD patients. The extent to which relative and absolute risk might be lowered by achieving ACC/AHA versus ESC/EAS LDL-C recommended approaches was simulated.[Methods] DA VINCI was a cross-sectional observational study of patients prescribed lipid-lowering therapy (LLT) across 18 European countries. Ten-year cardiovascular risk (CVR) was predicted among ASCVD patients receiving stabilized LLT. For patients with LDL-C ≥ 70 mg/dl, the absolute LDL-C reduction required to achieve an LDL-C of < 70 or < 55 mg/dl (LDL-C of 69 or 54 mg/dl, respectively) was calculated. Relative and absolute risk reductions (RRRs and ARRs) were simulated.[Results] Of the 2039 patients, 61% did not achieve LDL-C < 70 mg/dl. For patients with LDL-C ≥ 70 mg/dl, median (interquartile range) baseline LDL-C and 10-year CVR were 93 (81–115) mg/dl and 32% (25–43%), respectively. Median LDL-C reductions of 24 (12–46) and 39 (27–91) mg/dl were needed to achieve an LDL-C of 69 and 54 mg/dl, respectively. Attaining ACC/AHA or ESC/EAS goals resulted in simulated RRRs of 14% (7–25%) and 22% (15–32%), respectively, and ARRs of 4% (2–7%) and 6% (4–9%), respectively.[Conclusion] In ASCVD patients, achieving ESC/EAS LDL-C goals could result in a 2% additional ARR over 10 years versus the ACC/AHA approach.This study was funded by Amgen Europe (GmbH).Peer reviewe

Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life

Implications of ACC/AHA Versus ESC/EAS LDL‑C Recommendations for Residual Risk Reduction in ASCVD: A Simulation Study From DA VINCI

Purpose Low-density lipoprotein cholesterol (LDL-C) recommendations difer between the 2018 American College of Cardi ology/American Heart Association (ACC/AHA) and 2019 European Society of Cardiology/European Atherosclerosis Society (ESC/EAS) guidelines for patients with atherosclerotic cardiovascular disease (ASCVD) (<70 vs.<55 mg/dl, respectively). In the DA VINCI study, residual cardiovascular risk was predicted in ASCVD patients. The extent to which relative and absolute risk might be lowered by achieving ACC/AHA versus ESC/EAS LDL-C recommended approaches was simulated. Methods DA VINCI was a cross-sectional observational study of patients prescribed lipid-lowering therapy (LLT) across 18 European countries. Ten-year cardiovascular risk (CVR) was predicted among ASCVD patients receiving stabilized LLT. For patients with LDL-C≥70 mg/dl, the absolute LDL-C reduction required to achieve an LDL-C of<70 or<55 mg/dl (LDL-C of 69 or 54 mg/dl, respectively) was calculated. Relative and absolute risk reductions (RRRs and ARRs) were simulated. Results Of the 2039 patients, 61% did not achieve LDL-C<70 mg/dl. For patients with LDL-C≥70 mg/dl, median (inter quartile range) baseline LDL-C and 10-year CVR were 93 (81–115) mg/dl and 32% (25–43%), respectively. Median LDL-C reductions of 24 (12–46) and 39 (27–91) mg/dl were needed to achieve an LDL-C of 69 and 54 mg/dl, respectively. Attaining ACC/AHA or ESC/EAS goals resulted in simulated RRRs of 14% (7–25%) and 22% (15–32%), respectively, and ARRs of 4% (2–7%) and 6% (4–9%), respectively. Conclusion In ASCVD patients, achieving ESC/EAS LDL-C goals could result in a 2% additional ARR over 10 years ver sus the ACC/AHA approa

Application of wearables for remote monitoring of oncology patients: A scoping review

Objective This review aims to systematically map and categorize the current state of wearable applications among oncology patients and to identify determinants impeding clinical implementation. Methods A Medline, Embase and clinicaltrials.gov search identified journal articles, conference abstracts, letters, reports, dissertations and registered studies on the use of wearables in patients with malignancies published up to 10 November 2021. Results Of 2509 records identified, 112 met the eligibility criteria. Of these, 9.8% (11/112) were RCTs and 47.3% (53/112) of publications were observational. Wearables were investigated pre-treatment (2.7%; 3/112), during treatment (34.8%; 39/112), post-treatment (17.9%; 20/112), in survivors (27.7%; 31/112) and in non-specified or multiple treatment phases (17.0%; 19/112). Medical-grade wearables were applied in 22.3% (25/112) of publications. Primary objectives ranged from technical feasibility (8.0%; 9/112), user feasibility (42.9%; 48/112) and correlational analysis (40.2%; 45/112) to outcome change analysis (8.9%; 10/112). Outcome change was mostly investigated regarding physical activity improvement (80.0%; 8/10). Most publications (42.9%; 48/112) and registered studies (39.3%; 24/61) featured multiple cancer types, with breast cancer as the most prevalent specific type (22.3% in publications, 16.4% in registered studies). Conclusions Most studies among oncology patients using wearables are focused on assessing the user feasibility of consumer-grade wearables, whereas rates of RCTs assessing clinical efficacy are low. Substantial improvements in clinically relevant endpoints by the use of wearables, such as morbidity and mortality are yet to be demonstrated

Developing an AI-based decision engine for disease-modifying therapy in heart failure – A pilot study

Aim Heart failure is an escalating burden on global health care systems. Modernizing heart failure care is inevitable, with eHealth products poised to play an important role. However, eHealth devices that can initiate and adjust heart failure medication are currently lacking. Consequently, this study aimed to develop an artificial intelligence-based decision engine to provide guideline-based recommendations for disease-modifying medication in heart failure patients. Methods and Results We developed the decision engine by converting the ESC heart failure guidelines into Business Process Model and Notation, a visual modeling language suitable for developing complex decision engines. A safety evaluation, based on clinical parameters, was conducted to ascertain the system’s applicability to specific cases. The decision engine renders specific decisions concerning disease- modifying therapy for heart failure patients. We defined 72 virtual heart failure patient scenarios, encompassing a broad spectrum of baseline characteristics and background medication. All recommendations offered by the engine were evaluated by an independent heart failure specialist. All but three recommendations (94%) were identical to the treatment decisions by the heart failure specialist and all (100%) were in line with the 2021 ESC heart failure guidelines. Conclusion The decision engine offers guideline-based recommendations for disease-modifying therapy, positioning it as a tool to enhance self-care among heart failure patients. To validate our results, the decision engine is being prospectively tested in real-world patients in a multicenter clinical trial (NCT04699253)

sj-xlsx-4-dhj-10.1177_20552076241233998 - Supplemental material for Application of wearables for remote monitoring of oncology patients: A scoping review

Supplemental material, sj-xlsx-4-dhj-10.1177_20552076241233998 for Application of wearables for remote monitoring of oncology patients: A scoping review by Katharina Cloß, Marlo Verket, Dirk Müller-Wieland, Nikolaus Marx, Katharina Schuett, Edgar Jost, Martina Crysandt, Fabian Beier, Tim H Brümmendorf, Guido Kobbe, Julia Brandts and Malte Jacobsen in DIGITAL HEALTH</p