bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patients’ preferences regarding the digital capturing of patient-reported outcomes: planning the future follow-up in a prospective heart failure registry
Authors: König Sebastian , Leiner Johannes , Nitsche Anne , Mouratis Konstantinos , Schanner Carolin , Sommerschuh Anett , Hindricks Gerhard , Meier-Hellmann Andreas , Kuhlen Ralf , Bollmann Andreas 
Published: August 2021

Abstract

Aims
Digital health technologies have the potential to improve patient care sustainably. A digital capturing of patient-reported outcome measures (PROMs) could facilitate patients’ surveillance and endpoint assessment within clinical trials especially in heart failure (HF) patients. However, data regarding the availability of digital infrastructure and patients’ willingness to use digital health solutions are scarce. Therefore, we conducted a survey as part of a digital-based HF registry.

Methods and results
The Helios Heart registry (H2-registry) has been introduced as a prospective registry being based on digitally augmented processes throughout the whole trial conduction from patients’ selection to data collection and follow-up (FU). Patient-reported outcome measures are captured paper-based at recruitment, but patients are offered two digital solutions for FU. Overall, 125 patients (mean age 67.8 years, 34.4% female) were included in the single-centre run-in phase of 16 weeks. Of them, 52.0% were not interested in any digital contact as part of the FU. If digital PROM capturing was conceivable, a web-based solution (70.0%) was preferred to an application-based approach (30.0%). Discrepancies occurred regarding the availability of email accounts and smartphones. Patients in the non-digital group were older (72.0 years vs. 63.2 years, P &lt; 0.01) and more frequently female (female sex, non-digital vs. digital group: 47.7% vs. 20.0%, P &lt; 0.01).

Conclusions
Our survey illustrated difficulties of implementing a digital FU to record PROMs in a contemporary HF cohort in particular among older patients. Further research is required to specify reasons in case of patients’ unwillingness and to better tailor digital health solutions to patients’ specific needs.
Targeting epigenetic modifiers to reprogramme macrophages in non-resolving inflammation-driven atherosclerosis
Authors: Jin Fengyan , Li Jian , Guo Jianfeng , Doeppner Thorsten R , Hermann Dirk M , Yao Gang , Dai Yun 
Published: August 2021

Abstract
Epigenomic and epigenetic research has been providing several new insights into a variety of diseases caused by non-resolving inflammation, including cardiovascular diseases. Atherosclerosis (AS) has long been recognized as a chronic inflammatory disease of the arterial walls, characterized by local persistent and stepwise accelerating inflammation without resolution, also known as uncontrolled inflammation. The pathogenesis of AS is driven primarily by highly plastic macrophages via their polarization to pro- or anti-inflammatory phenotypes as well as other novel subtypes recently identified by single-cell sequencing. Although emerging evidence has indicated the key role of the epigenetic machinery in the regulation of macrophage plasticity, the investigation of epigenetic alterations and modifiers in AS and related inflammation is still in its infancy. An increasing number of the epigenetic modifiers (e.g. TET2, DNMT3A, HDAC3, HDAC9, JMJD3, KDM4A) have been identified in epigenetic remodelling of macrophages through DNA methylation or histone modifications (e.g. methylation, acetylation, and recently lactylation) in inflammation. These or many unexplored modifiers function to determine or switch the direction of macrophage polarization via transcriptional reprogramming of gene expression and intracellular metabolic rewiring upon microenvironmental cues, thereby representing a promising target for anti-inflammatory therapy in AS. Here, we review up-to-date findings involving the epigenetic regulation of macrophages to shed light on the mechanism of uncontrolled inflammation during AS onset and progression. We also discuss current challenges for developing an effective and safe anti-AS therapy that targets the epigenetic modifiers and propose a potential anti-inflammatory strategy that repolarizes macrophages from pro- to anti-inflammatory phenotypes.
Systematic, early rhythm control strategy for atrial fibrillation in patients with or without symptoms: the EAST-AFNET 4 trial
Authors: Willems Stephan , Borof Katrin , Brandes Axel , Breithardt Günter , Camm A John , Crijns Harry J G M , Eckardt Lars , Gessler Nele , Goette Andreas , Haegeli Laurent M , Heidbuchel Hein , Kautzner Josef , Ng G André , Schnabel Renate B , Suling Anna , Szumowski Lukasz , Themistoclakis Sakis , Vardas Panos , van Gelder Isabelle C , Wegscheider Karl , Kirchhof Paulus 
Published: August 2021

Abstract

Aims
Clinical practice guidelines restrict rhythm control therapy to patients with symptomatic atrial fibrillation (AF). The EAST-AFNET 4 trial demonstrated that early, systematic rhythm control improves clinical outcomes compared to symptom-directed rhythm control.

Methods and results
This prespecified EAST-AFNET 4 analysis compared the effect of early rhythm control therapy in asymptomatic patients (EHRA score I) to symptomatic patients. Primary outcome was a composite of death from cardiovascular causes, stroke, or hospitalization with worsening of heart failure or acute coronary syndrome, analyzed in a time-to-event analysis. At baseline, 801/2633 (30.4%) patients were asymptomatic [mean age 71.3 years, 37.5% women, mean CHA2DS2-VASc score 3.4, 169/801 (21.1%) heart failure]. Asymptomatic patients randomized to early rhythm control (395/801) received similar rhythm control therapies compared to symptomatic patients [e.g. AF ablation at 24 months: 75/395 (19.0%) in asymptomatic; 176/910 (19.3%) symptomatic patients, P = 0.672]. Anticoagulation and treatment of concomitant cardiovascular conditions was not different between symptomatic and asymptomatic patients. The primary outcome occurred in 79/395 asymptomatic patients randomized to early rhythm control and in 97/406 patients randomized to usual care (hazard ratio 0.76, 95% confidence interval [0.6; 1.03]), almost identical to symptomatic patients. At 24 months follow-up, change in symptom status was not different between randomized groups (P = 0.19).

Conclusion
The clinical benefit of early, systematic rhythm control was not different between asymptomatic and symptomatic patients in EAST-AFNET 4. These results call for a shared decision discussing the benefits of rhythm control therapy in all patients with recently diagnosed AF and concomitant cardiovascular conditions (EAST-AFNET 4; ISRCTN04708680; NCT01288352; EudraCT2010-021258-20).
Continuity of care for patients with chronic disease: a registry-based observational study from Norway
Authors: Pahlavanyali Sahar , Hetlevik Øystein , Blinkenberg Jesper , Hunskaar Steinar 
Published: August 2021

Abstract

Background
Continuity of care (CoC) is accepted as a core value of primary care and is especially appreciated by patients with chronic conditions. Nevertheless, there are few studies investigating CoC for these patients across levels of healthcare.

Objective
This study aims to investigate CoC for patients with somatic chronic diseases, both with regular general practitioners (RGPs) and across care levels.

Methods
We conducted a registry-based observational study by using nationwide consultation data from Norwegian general practices, out-of-hours services, hospital outpatient care, and private specialists with public contracts. Patients with diabetes mellitus (type I or II), asthma, chronic obstructive pulmonary disease, or heart failure in 2012, who had ≥2 consultations with these diagnoses during 2014 were included. CoC was measured during 2014 by using the usual provider of care (UPC) index and Bice–Boxerman continuity of care score (COCI). Both indices have a value between 0 and 1.

Results
Patients with diabetes mellitus comprised the largest study population (N = 79,165) and heart failure the smallest (N = 4,122). The highest mean UPC and COCI were measured for patients with heart failure, 0.75 and 0.77, respectively. UPC increased gradually with age for all diagnoses, while COCI showed this trend only for asthma. Both indices had higher values in urban areas.

Conclusions
Our findings suggest that CoC in Norwegian healthcare system is achieved for a majority of patients with chronic diseases. Patients with heart failure had the highest continuity with their RGP. Higher CoC was associated with older age and living in urban areas.
Affective Practices of Diabetes Self-Management Among Older Adults: Cumulative Effects of Childhood Adversity
Authors: Roth Erin G , Chard Sarah 
Published: August 2021

AbstractBackground and ObjectivesA strong correlation exists between Type 2 diabetes mellitus and adverse childhood experiences. How adverse childhood experiences inform later-life diabetes management is less understood. This article examines diabetes management from the perspective of affective practice to explore the lingering impact of trauma biographies in diabetes management.Research Design and MethodsThis secondary narrative analysis of 15 in-depth interviews with community-dwelling older adults with diabetes (subsample of the Subjective Experiences of Diabetes Study) focuses on the ways their reported childhood adversity affects perceptions of and responses to diabetes self-management.ResultsThe experiences of adversity in childhood accumulate, throughout the life course, in the affective practices informing diabetes self-management, from blood glucose testing, to food consumption, to the emotions invested in body size. We identify 3 thematic areas that emerged across participants: (a) undermining self-worth, (b) (over)eating and food as comfort, and (c) weight and body size.Discussion and ImplicationsOur findings highlight affective practices as a mechanism through which adverse events accumulate and shape well-being over the life course. This analysis also suggests the potential for (de)accumulation of affective practices to improve diabetes management. The findings support recent calls for trauma-informed clinical care.
Illuminating the North Korean nuclear explosion test in 2017 using remote infrasound observations
Authors: Che Il-Young , Kim Keehoon , Le Pichon Alexis , Park Junghyun , Arrowsmith Stephen , Stump Brian 
Published: August 2021

SUMMARYNorth Korea conducted its sixth underground nuclear explosion test (${m_\mathrm{ b}}$ 6.3) on 2017 September 3. The underground explosion produced substantial low-frequency atmospheric waves, which were detected by infrasound arrays located up to a distance of 566 km. These infrasound waves are formed by the conversion of seismic energy to acoustic energy across the lithosphere–atmosphere interface. While infrasound records at regional distances produce estimates of ground motion amplitude over spatially extended regions covering about 26 500 km2, 3-D full seismo-acoustic simulations within the lithosphere and atmosphere provide quantitative information about seismo-acoustic energy partitioning. Our results demonstrate the capability of remote infrasound observations combined with 3-D propagation modelling to further develop discrimination methods for underground sources. These results contribute to enhance the confidence of source identification and characterization in nuclear test monitoring research, which is essential for the enforcement of the Comprehensive Nuclear-Test-Ban Treaty.
Upper mantle radial anisotropy under the Indian Ocean from higher mode surface waves and a hierarchical transdismensional approach
Authors: Weidner Erik , Beghein Caroline , Huang Quancheng , Schmerr Nicholas 
Published: August 2021

SUMMARYWe investigated the likelihood of radial anisotropy in the shallow and deep upper mantle, including the mantle transition zone (MTZ) under the Indian Ocean. Seismic anisotropy can be an indicator of mantle deformation through lattice preferred orientation of anisotropic crystals in the mantle. It has thus the potential to illuminate Earth’s dynamic interior, but previous seismic tomography studies have not achieved consensus on the existence of radial anisotropy below ∼250 km depth. We developed a fully nonlinear transdimensional hierarchical Bayesian Markov Chain Monte Carlo approach to invert fundamental and higher mode surface wave dispersion data and applied it to a subset of a global Love and Rayleigh wave data set. We obtained posterior model parameter distributions for shear wave velocity (VS) and radial anisotropy ξ under the Indian Ocean. These posterior model distributions were used to calculate the probability of having radial anisotropy at different depths. We demonstrated that separate inversions of Love and Rayleigh waves yield models compatible with the results of joint inversions within uncertainties. The obtained pattern of VS anomalies agrees with most previous studies. They display negative anomalies along ridges in the uppermost mantle, but those are stronger than for regularized inversions. The Central Indian Ridge and the Southeastern Indian Ridge present velocity anomalies that extend to ∼200 km depth, whereas the Southwestern Indian Ridge seems to have a shallower origin. Weaker, laterally variable velocity perturbations were found at larger depths. The anisotropy models differ more strongly from regularized inversion results and their uncertainties were rather large. We found that anisotropy models from regularized inversions also depend on the chosen parametrization, which is consistent with the existence of a large model null-space. Apart from a fast horizontally polarized shear wave signal in the top 100 km, likely reflecting the horizontal plate motion due to asthenospheric deformation, no clear relation to surface geology was detected in the anisotropy models. We found that, although the anisotropy model uncertainties are rather large, and lateral variations are present, the data generally prefer at least 1 per cent anisotropy in the MTZ with fast vertically polarized shear waves, within errors. Incorporating group velocity data did not help better constrain deep structure by reducing parameter trade-offs. We also tested the effect of prior constraints on the 410- and 660-km topography and found that the undulations of these discontinuities had little effect on the resulting models in our study region.
Application of an unsupervised clustering algorithm on in situ broadband acoustic data to identify different mesopelagic target types
Authors: Agersted Mette Dalgaard , Khodabandeloo Babak , Liu Yi , Melle Webjørn , Klevjer Thor A 
Published: August 2021

Abstract
The mesopelagic zone (200–1000 m depth) contains high fish species diversity but biomass and abundances are uncertain yet essential to understand ecosystem functioning. Hull-mounted acoustic systems (usually 38 kHz) often make assumptions on average target strength (TS) of mesopelagic fish assemblages when estimating biomass/abundance. Here, an unsupervised clustering algorithm was applied on broadband acoustic data (54–78 kHz), collected by a towed instrumented platform in the central Northeast Atlantic, to identify different mesopelagic target types based on similarity of individual TS spectra. Numerical density estimates from echo-counting showed spatial differences in vertical distribution patterns of the different target types and TS spectra data suggested that &gt;30% of the gas-bearing targets had high resonance frequencies (&gt;60 kHz) with low scattering strength at 38 kHz. This conceptual study highlights the importance of separating targets into different target groups to obtain correct backscatter information and to account for all relevant scatterers when estimating average TS at 38 kHz, in order to achieve more accurate biomass/abundance estimates. It furthermore demonstrates the use of a towed broadband acoustic platform for fine-scale numerical density estimates as a complementary method to hull-mounted acoustic data to increase knowledge on mesopelagic ecosystem structure.
Metabarcoding as a quantitative tool for estimating biodiversity and relative biomass of marine zooplankton
Authors: Ershova E A , Wangensteen O S , Descoteaux R , Barth-Jensen C , Præbel K 
Published: August 2021

AbstractAlthough metabarcoding is a well-established tool for describing diversity of pelagic communities, its quantitative value is still controversial, with poor correlations previously reported between organism abundance/biomass and sequence reads. In this study, we explored an enhanced quantitative approach by metabarcoding whole zooplankton communities using a highly degenerate primer set for the mitochondrial marker cytochrome oxidase I and compared the results to biomass estimates obtained using the traditional morphological approach of processing zooplankton samples. As expected, detected species richness using the metabarcoding approach was 3–4 times higher compared to morphological processing, with the highest differences found in the meroplankton fraction. About 75% of the species identified using microscopy were also recovered in the metabarcoding run. Within the taxa detected using both approaches, the relative numbers of sequence counts showed a strong quantitative relationship to their relative biomass, estimated from length-weight regressions, for a wide range of metazoan taxa. The highest correlations were found for crustaceans and the lowest for meroplanktonic larvae. Our results show that the reported approach of using a metabarcoding marker with improved taxonomic resolution, universal coverage for metazoans, reduced primer bias, and availability of a comprehensive reference database, allow for rapid and relatively inexpensive processing of hundreds of samples at a higher taxonomic resolution than traditional zooplankton sorting. The described approach can therefore be widely applied for monitoring or ecological studies.
Evidence of large systematic differences between countries in assigning ischaemic heart disease deaths to myocardial infarction: the contrasting examples of Russia and Norway
Authors: Timonin Sergey , Shkolnikov Vladimir M , Andreev Evgeny , Magnus Per , Leon David A 
Published: August 2021

Abstract

Background
There is considerable variation in mortality rates from myocardial infarction (MI) across high-income countries, some of which may be artefactual.

Methods
Time trends in mortality rates from ischaemic heart disease (IHD) and MI were analysed for a set of high-income countries from the end of the 1970s. Using individual-level mortality data from Russia (2005–2017) and Norway (2005–2016), we investigated factors associated with the proportion of total IHD deaths certified as due to MI.

Results
In most countries, MI mortality rates have dramatically declined from the 1970s. However, the share of MI in total IHD deaths varies substantially across countries. In Russia, only 12% of IHD deaths had MI assigned as the underlying cause vs 63% in Norway. IHD deaths occurring outside of hospital without autopsy were far less likely to be assigned as MI in Russia (2%) than in Norway (59%).

Conclusions
Although established international criteria for MI require specific clinical or post-mortem evidence, it appears that certifying specialists in different countries may interpret these criteria differently. At one extreme, Russian doctors may only assign MI as a cause of death when there is specific pathophysiological evidence. At the other extreme, their counterparts in Norway may be willing to specify MI as the cause even when this evidence is not available. Internationally established criteria for MI diagnosis are challenging to apply for out-of-hospital deaths. Differences between countries in how certifiers interpret these criteria may account for at least some of the international variation in MI mortality rates.
Elliptic Ruijsenaars Difference Operators on Bounded Partitions
Authors: van Diejen Jan , Görbe Tamás 
Published: August 2021

AbstractBy means of a truncation condition on the parameters, the elliptic Ruijsenaars difference operators are restricted onto a finite lattice of points encoded by bounded partitions. A corresponding orthogonal basis of joint eigenfunctions is constructed in terms of polynomials on the joint spectrum. In the trigonometric limit, this recovers the diagonalization of the truncated Macdonald difference operators by a finite-dimensional basis of Macdonald polynomials.
Natural language processing enabling COVID-19 predictive analytics to support data-driven patient advising and pooled testing
Authors: Meystre Stéphane M , Heider Paul M , Kim Youngjun , Davis Matthew , Obeid Jihad , Madory James , Alekseyenko Alexander V 
Published: August 2021

Abstract

Objective
The COVID-19 (coronavirus disease 2019) pandemic response at the Medical University of South Carolina included virtual care visits for patients with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The telehealth system used for these visits only exports a text note to integrate with the electronic health record, but structured and coded information about COVID-19 (eg, exposure, risk factors, symptoms) was needed to support clinical care and early research as well as predictive analytics for data-driven patient advising and pooled testing.

Materials and Methods
To capture COVID-19 information from multiple sources, a new data mart and a new natural language processing (NLP) application prototype were developed. The NLP application combined reused components with dictionaries and rules crafted by domain experts. It was deployed as a Web service for hourly processing of new data from patients assessed or treated for COVID-19. The extracted information was then used to develop algorithms predicting SARS-CoV-2 diagnostic test results based on symptoms and exposure information.

Results
The dedicated data mart and NLP application were developed and deployed in a mere 10-day sprint in March 2020. The NLP application was evaluated with good accuracy (85.8% recall and 81.5% precision). The SARS-CoV-2 testing predictive analytics algorithms were configured to provide patients with data-driven COVID-19 testing advices with a sensitivity of 81% to 92% and to enable pooled testing with a negative predictive value of 90% to 91%, reducing the required tests to about 63%.

Conclusions
SARS-CoV-2 testing predictive analytics and NLP successfully enabled data-driven patient advising and pooled testing.