dataesr/scientific-paragraphs-categorization huggingface dataset:
Thus, real-life information on unselected patients will be obtained, whereas randomised trials are done in selected populations. The large number of participating ICUs and future involvement of international centres will ensure strong external validity. Moreover, the considerable sample size combined with potent statistical tools such as propensity-score matching will provide robust statistical results despite the observational nature of the data. The modular nature of the cohort with the establishment of satellite databases around the core set of variables provides room for almost real-time responsiveness to the data collected thus far and to changes in epidemiological circumstances. These satellite databases will allow a broad diversity of study designs. The vast core database will limit the amount of additional data needed for the satellites, thereby substantially reducing study times and costs.
Finally, the creation of satellite databases will be open to investigators from multiple disciplines (eg, neurophysiologists, neurologists, emergency physicians, resuscitators, rehabilitation physicians, family physicians, nurses, physiotherapists and occupational therapists), which constitutes a major advantage since patients with SE require both organ support and also antiseizure treatment, EEG monitoring (continuous whenever possible), laboratory tests and imaging studies to identify the cause and treatment of the cause. Also, patients recovering from SE are managed in neurology wards or rehabilitation units and, after discharge, by acute care physicians. The ICTAL Registry will allow conducting cohort multiple randomised controlled trials. This type of trial consists in testing interventions within large longitudinal cohorts and has the advantage of minimising recruitment difficulties and costs.
Other trial-within-cohorts designs will be possible, including cross-sectional observational studies and longitudinal outcome studies. Patient inclusion into studies based on the ICTAL Registry will be subject to the obtaining of informed written consent, in compliance with regulations. Finally, the ICTAL Registry data will be open to sharing with other registries focused on SE or on other conditions, thereby promoting international collaboration. The ICTAL Registry will allow evaluations of associations linking specific components of management, such as very early initiation of EEG monitoring, to outcomes. Some of these management components may apply to all patients with SE. However, a major goal of the ICTAL Registry is to separate patient subgroups that differ regarding the management strategies associated with the best outcomes.
Acknowledgements We thank  A Wolfe MD  ( Chaumont, France ) for helping to prepare the manuscript. The study was supported by the  French public funding agency Délégation à la Recherche Clinique et à l'Innovation (DRCI) ,  Versailles, France. Collaborators Ictal Study Group:  Coralie Marjolet  ( Centre Hospitalier de Versailles );  Louison Feyrit  ( Centre Hospitalier de Versailles );  Gabriel Obert  ( Centre Hospitalier de Versailles );  Lea Jacot  ( Centre Hospitalier de Versailles );  Sonia Garrigou  ( Groupe Hospitalier Paris Saint Joseph );  Roxane Bai  ( Groupe Hospitalier Paris Saint Joseph );  Camille Prudat  ( Groupe Hospitalier Paris Saint Joseph );  Carole Ouisse  ( Centre Hospitalier Universitaire de Nantes );  Diane Maugars  ( Centre Hospitalier Universitaire de Nantes );  Jack Richecoeur  ( Centre Hospitalier de Beauvais );  Didier Ledoux  ( Centre Hospitalier Universitaire de Liège );  Audrey Massard  ( Centre Hospitalier Universitaire de Dijon );  Mathilde Godard  ( Centre Hospitalier Universitaire de Dijon );  Mathilde Audry  ( Centre Hospitalier Universitaire de Dijon );  Ludivine Garrier  ( Centre Hospitalier Universitaire de Dijon );  Magaly Noel  ( Centre Hospitalier du Cotentin );  Guillaume Duhommet  ( Centre Hospitalier du Cotentin );  Alice Langlois  ( Centre Hospitalier de La Rochelle );  Julie Noublanche  ( Centre Hospitalier de La Rochelle );  Sonia Garrigou  ( Groupe Hospitalier Paris Saint Joseph );  Sybille Merceron  ( Centre Hospitalier de Versailles ).
Acknowledgments: We are deeply thankful to  Marco Antônio Silva Campos ,  Alexandre de Magalhães Vieira Machado , and their team, who provided viral culture infrastructure at the  Imunologia de Doenças Virais Group (IDV-IRR/FIOCRUZ). We are grateful to  Rivaldo Venâncio  for the kindly provided CHIKV strain. We thank the  Program for Technological Development of Tools for Health-PDTIS-FIOCRUZ  for use of its facilities. We are grateful to all members of the  Mosquitos Vetores Group  ( MV-IRR/FIOCRUZ ) and the  World Mosquito Program Brazil. We are grateful for support from the  Coordination for the Improvement of Higher Education Personnel (CAPES).
Statistical analysis All results are presented at mean ± standard deviation. Qualitative image assessments were evaluated using a Mann-Whitney rank sum test (SigmaPlot 12. 5, Systat Software Inc. , San Jose, CA). Paired t-tests (SigmaPlot 12. 5, Systat Software Inc. , San Jose, CA) were used to test for a potential difference between measurements obtained with T-echo and 3D and the level of agreement between T-echo and 3D measures was determined using Bland-Altman plots and Pearson's linear correlation (r) for each assessment (SigmaPlot 12. 5, Systat Software Inc. , San Jose, CA). For all tests, significance was set a p < 0. 05.
Methods We analyzed individual-level data from NLST and MLHCs. Each study has been described in detail and both screened individuals aged 55-74 years  [1, 3, 4]. To align the designs of the two studies, we included lung cancers detected at the baseline screen, during the interval, and at the 1-year incidence screen among participants who underwent the baseline screen, disregarding the third screen for NLST. We excluded MLHCs participants who did not meet NLST eligibility criteria (N = 305, among whom 10 cancers occurred). Throughout, we calculated 'detection ratios' as the ratio of lung cancer detection between MLHCs and NLST. First, to determine the influence of the risk-based eligibility criterion used in MLHCs, we excluded NLST participants with a PLCOm2012 6-year lung cancer risk < 1. 51 %.
The standardized detection ratios divide the number of cases observed in MLHCs in the indicated subgroup by the number of cases expected based on NLST risk-specific detection frequencies. Across these analyses, the MLHCs population is stratified by the variables indicated, while the NLST population is not. **The adjusted odds ratios were calculated from a logistic regression model fit to the MLHCs dataset. The model included a reduced set of variables (those for which odds ratios are listed in the table) with adjustment for the log of the detection frequency in NLST. This detection frequency was calculated in 10 strata of baseline lung cancer risk and assigned to individuals in MLHCs based on their membership in one stratum (see first two columns of Supplementary Table  1 ). that these factors might also have unique associations with lung cancer risk.
As expected, both assays showed no neutralising titres in the 7 dpv samples, while all volunteers had protective titres at 28 dpv. While the absence or presence of protection is a useful qualitative result, quantitative assay development instead requires determining the actual antibody titre reliably and comparably, with emphasis on assay robustness, data quality, and assay practicability. We first assessed and compared assay practicability between FRNT and FluoRNT.
FluoRNT offers significantly greater assay practicability than FRNT and PRNT In addition to assay robustness and data quality, it is important for assay selection to evaluate practicability. Fig  1  shows the time line for PRNT, FRNT and FluoRNT. The following features that differentiate the ease of use and implementation of these assays will be considered in more detail in the discussion section. Of note, only FRNT and FluoRNT were evaluated and compared directly experimentally; the comparison to PRNT is from previous experience and literature. 1. FluoRNT delivers results distinctly faster than FRNT and PRNT (fewer (handling) steps, shorter run time). 2. FluoRNT readout by flow cytometry is objective and quantitative with the potential for automation 3. FluoRNT cuts assay costs by 84% compared to FRNT (S1  In addition to showing the improved practicability of FluoRNT in its assay setup, we also tested for improvements in data quality delivered by FluoRNT, analysing reproducibility, assay dynamic range and precision compared to the benchmark FRNT.
Acknowledgments We thank  Giulia Spielmann ,  Natalie Ro  ¨der und  Christine Ho ¨rth (LMU)  for assisting with study sample preparation, neutralisation assays and viral stock preparation. We thank  Renate Stirner  of the  LMU HIV Ambulanz  for excellent technical assistance and access to technical equipment. We thank  Liz Schultze-Naumburg  for invaluable support in building up the yellow fever vaccination cohort. We thank  Charles M. Rice  and  Margaret MacDonald  for their kind gift of the initial plasmid containing the sequence of YF-17D with the Venus-reporter sequence. Parts of this work have been performed for the doctoral theses of MKS, LL, MZ at the  Ludwig-Maximilians-Universita ¨t Mu ¨nchen.
This research was supported by funds from:  -Einheit fu ¨r Klinische Pharmakologie (EKliP) ,  Helmholtz Center Munich, Neuherberg, Germany  (https://www. helmholtzmuenchen. de/forschung/forschungseinrichtungen/klinische kooperationen/ klinische pharmakologie/forschung/index. html), to JTS, SE and SR; - LMU Center  for  Integrated Protein Science Munich (CIPSMwomen)  to  JTS -German Research Foundation (DFG) :  Emmy Noether  grant  TH2231/1-1  to OTS (https://gepris. dfg. de/gepris/projekt/400324123) - Friedrich Baur Foundation (FBS)  to  JTS -Ro 25257/-1  grant number  391217598  (https://gepris. dfg. de/gepris/projekt/391217598)  KR2199/10-1  to SR and  ABK -SFB/TR-237-B14  Grant No. 369799452  (https:// gepris. dfg. de/gepris/projekt/404450088) to SR and ABK Furthermore, we would also like to acknowledge support from the international doctoral program "iTarget: Immunotargeting of cancer" funded by the  Elite Network of Bavaria  to MKS, MZ, LL, and SE.
This paper examines questions in section C, i. e. endocrinological aspects of pituitary surgery and perioperative patient care. The study period started on 1 April 2019 and closed on 30 June 2019. The remaining sections were covered in previous papers  1, 2. All questions used in survey are presented as supplementary data. The minimum time to complete the survey was 12 min (min) (mean time 18 min). All received surveys were complete. Data from 34 European countries were obtained. Altogether, 254 European Departments of Neurosurgery completed the survey. Most responses came from Germany (60), Italy (28), France (22), the UK (  16 ), the Czech Republic (13) and Spain (10). A univariate analysis was planned based on the following variables: • Academic/non-academic centers (based on participant answers) • High-volume/low-volume centers.
Statistics. Basic descriptive statistics were performed that included counts and percentages for each survey question. Differences in responses to survey questions based on selected grouping variables (academic center, surgical technique, case volume per year and region) were examined using Pearson's chi-square test (Fisher's exact test was applied as appropriate) with adjusted residuals. The level of statistical significance was set at α = 0. 05. The descriptive statistical analysis (frequencies and percentages) and data processing were done with SPSS statistical software (SPSS version 25•0, SPSS Inc. , Chicago, IL, USA) and Microsoft Excel.
SEEG recording All intracranial SEEG procedures were performed according to clinical practice and the epilepsy features of the patients. In addition to macroelectrodes, Behnke-Fried-type (23) macromicroelectrodes (AdTech R ) were inserted in nodules (Table  2 ). Signals from macro-and microelectrodes were continuously and synchronously recorded at 4 and 32 kHz, respectively, using a hardware filter at 0. 01Hz (Atlas Recording System; NeuraLynx, Tucson, AZ, USA). Post-implantation electrode locations were based on a pre-implant 3T 3D-MRI, post-implant 1. 5T 3D-MRI, and CT scan, integrated using the Epiloc toolbox, an inhouse developed plugin for the 3D-Slicer visualization software  (24, 25). Patients gave written informed consent (project C11-16 conducted by INSERM and approved by the local ethic committee, CPP Paris VI).
Visual analysis of micro-LFP patterns Pathological activities were visually identified on microelectrode LFP signals, according to traditional morphological characteristics used in clinical practice, and then classified into different interictal patterns (IPs). Criteria for each pattern were then used for a complete manual scoring of continuous data recorded on the first day after implantation. The annotations were performed on the first day after the implantation when the quality of the microelectrode signal is typically the highest. For each nodule, the annotations of the IPs were based on the LFP from the same microwire, selected for the clearest morphology, using software developed in-house (MUSE). We describe our classification according to standard guidelines  (26, 27). Albeit designed for the critical care unit, such standard terminology improves clarity in communication, and to the best of our knowledge, no other such standard exists.
Time-locked and time-frequency analysis Analyses were performed with a combination of FieldTrip  (28)  and custom MATLAB scripts (The MathWorks Inc. , Natick, Massachusetts). Manual annotations of each pattern, in each nodule, were temporally aligned by maximizing the cross correlation between electrode time courses. Data were then down-sampled to 1 kHz. The average LFPs were extracted based on the aligned time courses. Time-frequency representations (TFRs) were calculated using a Hanning taper applied to a sliding time window in steps of 5 ms. The time window was 200 ms for epileptic spikes and 400 ms for all other (longer) patterns. The average power in 60-200 Hz was expressed in percentage change relative to the baseline period that was set at -1s to -0. 5 s for epileptic spikes and -2 s to -1 s relative to pattern onset (annotation) for the other patterns.
Spike time analyses Spike times were epoched and time-locked according to the aligned annotations. The average spike rates were calculated continuously at 1,000 Hz, using a Gaussian smoothing kernel of 10 ms for epileptic spikes and 50 ms for the longer patterns to better capture the slower modulations of firing rate. Correlations were calculated between the average time-locked spike rates of each unit and the average time-locked LFP of every pattern. Finally, the spike rates of each trial were binned into 100 bins for statistical analyses. To determine the resting behavior of detected units, data were first to split into 10-s time periods, excluding time periods that overlapped with IED or seizure occurrence. The mean firing rate and coefficient of variation  (30)  were calculated over the remaining time periods.
Funding This study was supported by the  program Investissements d'avenir   ANR-10-IAIHU-06  and grants from the  OCIRP-ICM  and the  Fondation de l'APHP pour la Recherche -Marie-Laure PLV Merchandising. Marie-Laure PLV Merchandising  was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.
Acknowledgements. Both authors acknowledge fruitful discussions with  Alexandre Tsybakov ,  Cristina Butucea  and  Rajarshi Mukherjee. The work of  A. Carpentier  is partially supported by the  Deutsche Forschungsgemeinschaft (DFG)   Emmy Noether grant MuSyAD  ( CA 1488/1-1 ), by the  DFG -314838170 , GRK 2297 MathCoRe, by the  FG DFG  , by the  DFG CRC 1294  'Data Assimilation', Project  A03 , and by the  UFA-DFH  through the  French-German Doktorandenkolleg   CDFA 01-18  and by the  SFI Sachsen-Anhalt  for the project  RE-BCI.
Purpose -The COVID-19 pandemic has demonstrated the urgency of better chronic disease management and the importance of making it an integral part of the recovery agenda in Europe. This paper aims to explore the shift towards digital and integrated care systems in Europe. Design/methodology/approach -In this viewpoint paper the Expert Group for Integrated Care and Digital Health Europe (EGIDE) group argues that an orchestrated shift towards integrated care holds the solution to the chronic disease pandemic. Findings -The development of integrated care cannot happen without shifting towards a digitalised healthcare system via large-scale initiatives like the European Health Data Space (EHDS) and the involvement of all stakeholders.
The European Health Data Space (EHDS) can act as a catalyst for change in several important areas: (1) Approach to health data from an integrated care perspective: How to accelerate data integration? What data governance framework is needed to ensure interoperability both within and between health systems? How to recognise the value of health data? What does it take to use health data to improve patient care and enable self-care? How should we reconcile individual patient data privacy with collective data research? (2) Digital health financing: How to guide new investment in data infrastructure? What are the new reimbursement and financing models needed to facilitate integrated digital healthcare? What are the appropriate financial incentives for integrated digital care? And how to target funds to strengthen healthcare digital infrastructure, given the varying organisation of healthcare systems? (3) Putting patients in the centre of the new organisation of healthcare systems: How to enhance patients' trust in health data? How to ensure patients' access to digital health innovation? (4) Digital health education as an enabler of integrated care: How to improve digital health education and training for HCPs? How to improve patient education and understanding of the purpose and methods of digital health? While those topics are at the core of the future European Union legislative cycle, this paper will go a step further.
JICA (2) The needs of patients to manage their condition alongside the healthcare system; (3) The involvement of stakeholders at all levels and areas of healthcare. Integrated care and digitalisation then has the potential to: (1) Dramatically improve the lives of patients living with chronic diseases; (2) Facilitate the work of HCPs; (3) Provide optimisation of resources and efficiencies for the healthcare systems in general. The opportunity ahead of the European Health Data Space for chronic diseases in Europe A strong EU commitment The current European Commission 2019-2025, from the start of its mandate, has shown a strong commitment to the establishment of a general European Data Space with more specific focus on several strategic sectors, healthcare being one of the main priorities. A common EHDS will be built on the basis of strong data governance, data quality and interoperability.
Digital and integrated care systems The potential of the European Health Data Space for integrated care If developed and implemented with the appropriate principles in its vision, the EHDS has the potential not only to contribute but to be the foundation for a truly integrated healthcare system in Europe by bringing benefits for: (1) The holistic management of chronic diseases The availability and access to data can help improve diagnostic timelines and facilitate remote monitoring to ease chronic conditions. Importantly, with the power of data analytics and predictive modelling, the opportunities ahead of prevention and early detection have never been so vast. Chronic diseases are often mismanaged due to the lack of personalised approach. The data available through the EHDS can enable the development of personalised medicine and precision treatments by fostering the possibility to match the patient's genetic characteristics to the most effective treatment solution based on a data analysis.
Objectives The consequences of psoriasis associated to axial spondyloarthritis (axSpA) are unclear. The objectives were to determine the prevalence and the consequences of psoriasis in recent axSpA over 6 years of follow-up. Methods The multicentric prospective cohort DESIR (NCT01648907) of adult patients with recent inflammatory back pain suggestive of axSpA was analysed over 6 years. Psoriasis was recorded at each visit and cumulative prevalence and incidence were calculated. Patients with vs without psoriasis at any time point were compared. Outcomes included disease activity (Ankylosing Spondylitis Disease Activity Score-C reactive protein (ASDAS-CRP), joint and enthesitis count, CRP), patient-reported outcomes for function (Health Assessment Questionnaire for axSpA, HAQ-AS) and quality of life, and treatment use over 6 years.
Study population and study design The DESIRcohort (DEvenir des Spondylarthropathies Indifférenciés Récentes) has been previously reported; this longitudinal, prospective, multicentre French cohort included 708 adult patients (18-50 years old) with recent onset inflammatory back pain of more than 3 months and less than 3 years of duration, suggestive of early axSpA, between October 2007 and April 2010. 17 Patients were followed up every 6 months the first 2 years and then annually with a planned follow-up of 20 years. 17 For this analysis, data from the first 6 years were available and were analysed. At baseline, no patients were treated by biological disease-modifying antirheumatic drugs (bDMARDs). Each patient gave written informed consent.
Baseline characteristics Demographic and socioeconomic data were collected including age, sex, ethnicity. Clinical features were also collected such as body mass index, symptom duration, history of symptoms and family history. Disease activity was assessed through Ankylosing Spondylitis Disease Activity Score-C reactive protein (ASDAS-CRP), BASDAI, joint counts (28 swollen joint count, 53 tender joint count) and enthesitis (Maastricht Ankylosing Spondylitis Enthesis score, MASES, ranging 0-13). 18 19 Healthrelated quality of life and functional capacity were assessed through patient-reported outcomes including the Health Assessment Questionnaire for axSpA (HAQ-AS), Bath Ankylosing Spondylitis Functional Index (BASFI), Ankylosing Spondylitis Quality of Life Scale (ASQoL) and Short Form 36 Health Survey Questionnaire (SF-36).
Consequences of psoriasis on recent axSpA Outcomes were compared between patients with vs without psoriasis using two methods: ► Univariable analysis and multivariable linear regression at year 6, including variables with p<0. 20 and excluding collinear variables. The variables were also checked for clinical relevance by the investigators. This analysis was performed on the 589 patients present at year 6. ► Longitudinal models. In order to take into account the longitudinal nature of the data and to analyse the 708 patients, we performed generalised linear mixedeffects models with the patient as a random effect. Covariates associated with psoriasis at baseline were included in each model with a stepwise approach in order to select the best model based on the Akaike information criterion. 24 here was no imputation of missing data.
RESULTS Among the 708 patients included in the DESIR cohort at baseline, 92% fulfilled at least one set of classification criteria for SpA; 589 (83. 2%) were followed up after 6 years (figure  1 ). Baseline characteristics of the 589 patients were globally similar to those of the overall cohort (data not shown) and included 270 (45. 8%) men, mean age was 33. 9 (SD 8. 8) years, 213 (36. 4%) were current smokers, mean symptom duration was 1. 5 (SD 0. 9) years and 357 (60. 7%) patients carried the HLA B27 allele.