dataesr/scientific-paragraphs-categorization huggingface dataset:
SB did statistical analysis of the INTERVAL GWAS for restless legs syndrome. ASB and NS were responsible for data curation of the INTERVAL study. ASB, NS, WHOu DJR, JD, and EDA acquired funding for and supervised the INTERVAL study. EDA conceived and oversaw the INTERVAL GWAS for restless legs syndrome. DAH performed data analysis of the 23andMe restless legs syndrome GWAS. All authors contributed and critically reviewed the final version of the manuscript.
Acknowledgments We thank all colleagues and staff at the participating centres of the  EU-RLS-GENE consortium  for their help with recruitment of patients. We thank  Daniel Lam ,  Institute of Neurogenomics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany , for critically proofreading the draft paper. We thank the  German Restless Legs Syndrome Foundation  for continuously supporting our study and  NIH Research Cambridge Biomedical Research Centre  for funding ( RG64219 ). JW was supported by the  Deutsche Forschungsgemeinschaft  (grant  WI 1820/5-1 ). WHOe is a  Hertie Senior Research Professor , supported by the  Charitable Hertie Foundation. MT-L and AM were supported by the  Estonian Research Council  (grant  IUT20-60 ),  European Union Framework for Research and Innovation Horizon 2020  (grant  692145 ),  European Regional Development Fund  (project  2014-2020.
Background: In cancer patients with symptomatic venous thromboembolism (VTE) (deep-vein thrombosis (DVT) and/or pulmonary embolism (PE)), clinical factors that influence the benefit-risk balance of anticoagulation need to be identified so treatment intensity and duration can be optimally adjusted for the individual patient. Methods: Using clinical data for cancer patients with VTE obtained from the RIETE registry, we compared how rates of fatal PE and fatal bleeding during and after anticoagulation vary depending on patients' clinical characteristics. Results: Data were analysed from the 10,962 cancer patients with VTE (5,740 with PE with or without DVT; 5,222 with DVT alone) in RIETE registry as of March 2016. Fatal PE occurred in 2. 18% of patients, while fatal bleedings occurred in 1. 55%.
The ongoing RIETE (Registro Informatizado de Enfermedad TromboEmbólica) Registry provides a large prospective cohort of consecutive patients with symptomatic VTE (deep vein thrombosis (DVT) orpulmonary embolism (PE) or both), derived from multiple centres across several countries in Europe and in North and South America (its methodology is summarised in the Methods section and has been described elsewhere)  [18, 19, 20]. So far, published analyses of data from the RIETE registry have provided valuable information on current outcomes of acute VTE, including the frequency of recurrent VTE and of major bleeding, mortality rates and risk factors  [18, 19, 20]. In the study presented here, we took data from RIETE Registry in order to determine the frequency and time course of occurrence of fatal PE and of fatal bleeding in this large cohort of cancer patients with VTE.
Registry design, patient collective and data collection The RIETE registry is an ongoing, international, (Spain, Belgium, Canada, Czech Republic, Ecuador, France, Greece, Israel, Italy, Latvia, Portugal, Republic of Macedonia, Switzerland), multicenter, prospective collection of clinical data from consecutive patients presenting with symptomatic, acute VTE (DVT and/or PE)  [18, 19, 20]. Clinical data were collected for patients presenting with symptomatic VTE  [21, 22]. The methodology of data collection has been described previously  [18, 20]  and is summarised in the following. Consecutive patients with symptomatic acute VTE confirmed by objective tests (contrast venography or ultrasonography for suspected DVT, pulmonary angiography, lung scintigraphy or helical computed tomography scan for suspected PE) were enrolled in RIETE registry.
The only patients excluded from the registry are those currently participating in a therapeutic clinical trial with a blinded therapy. All patients provided written or oral consent for participation in the registry, in accordance with local ethics committee requirements. Participating physicians ensured that eligible patients were consecutively enrolled. Data recorded on a computer-based case report form at each participating hospital were submitted to a centralised coordinating center through a secure website. Data quality (including comparison of the data on medical records with the data that were transferred) was regularly monitored as previously described. This analysis was approved by the Ethics Committees of the UZ Gasthuisberg Hospital in Leuven, Belgium (B70721111790) and the Hospital Clinic of Barcelona, Spain (Reg.
Statistical analysis Categorical variables were reported as percentages and compared using the chisquare test (two-sided) and Fisher's exact Test as appropriate. Odds ratios and corresponding 95% confidence intervals were calculated, and a p-value of <0. 05 was considered to be statistically significant. Continuous variables were compared with a Student t-test. Incidence rates were calculated as cumulative incidence (events/100 patient-years). The SPSS software (version 20, SPSS Inc. Chicago, Illinois) was used for the statistical management of the data. developed fatal PE, mostly (96%) during anticoagulant treatment, while 170 (1. 55%) had fatal bleeding, with 20 (12%) cases occurring after discontinuing anticoagulant treatment. Ten percent of the patients dying of PE and 8. 1% of patients dying of bleeding were aged below 50 years.
Funding statement The  RIETE Registry  is supported by unrestricted educational grants from  [ 4 _ T D $ D I F F ] Sanofi Spain and Bayer Pharma AG. The funding source had no role in the design, protocol development, or conduct of the study; data collection, management, or analysis; interpretation, preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication. [ 5  _ T D $ D I F F ] LEO Pharma  provided financial support for the writing and editing of this manuscript by  Gerard McGregor , working for the company Copentown.
Randomization and allocation In April 2017, after the 1-year baseline period, hospitals will be randomly assigned either to the intervention group or the control group. Randomization will be stratified according to level of care of each hospital (community, regional, or tertiary hospital). To avoid imbalance in the size of the two groups, we will use computer-generated, blocked randomization within each stratum, with blocks consisting of four centers or, for strata with fewer than eight hospitals, two centers. The names of participating hospitals will be coded and the randomization will be generated by an independent statistician blinded to group allocation. The Data Safety Monitoring Board will receive the results of the randomization and the key code to ensure validity of the process and reveal the distribution of both intervention and control groups to the coordination team.
Data collection Clinical data are collected independently of the intervention. Subjects will be initially screened by the medical archives department staff in every participating hospital, and then will be validated by the data collectors according to the study inclusion and exclusion criteria. Computerized data collection will be performed on-site using Dacima Clinical Suite from Dacima Software Inc. [63] The electronic case report form includes individual clinical information about the mother and the newborn, namely maternal characteristics, prenatal care, labor and delivery and maternal and neonatal complications. Inhospital data will be abstracted by trained research nurses or medical archivists from the medical records of mothers and newborns at least 3 months after delivery; data will be abstracted in the same way at both intervention and control hospitals from April 2016 to March 2017 (baseline period) and from September 2017 to August 2019 (intervention period).
Data management The Dacima Clinical Suite and the trial database are managed by the Data Management Team located at the Research Center of the CHU de Québec (Laval University, Québec City, QC) and hosted on secure servers in Dacima software facilities (Montreal, QC). Until the end of the trial, access to the clinical database will be restricted to the Data Management Team. All steps involved in the management of clinical data will be annually monitored by an independent Data Safety Monitoring Board (DSMB).
Quality control of data Four levels of control have been set up. The first level represents the data entry controls included in the Dacima software (bounds, branching logics, associations between variables). The second level is a random case review of around 5% of all medical records by a second data collector. In addition, all cases of major perinatal and maternal morbidity will be systematically monitored for quality. The third quality control level targets specific cases of perinatal and maternal morbidity for which a consensus between the collectors and the data management team could not be reached. These cases will then be submitted to a committee of experts (obstetricians and neonatologists) for further study. Finally, the Data Management Team will assess the data completeness and quality directly in the database (fourth level of control).
Type of analysis and handling loss-to-follow-up Analyses will be conducted in intention-to-treat, i. e. , each patient will be analyzed in the hospital to which she will be admitted and each hospital will be analyzed in the group to which it will be assigned by the randomization. If a hospital decides to withdraw from the trial after the randomization, data collection will continue until the end of the trial, according to the commitment made by the hospital authorities at the time of inclusion. This hospital will not be excluded from the analyses.
baseline)  [64, 65]. The adjusted odds ratio for interaction will be estimated with the use of data on women who were delivered during the baseline period or the intervention period and measures the intervention effect with the difference-in-differences approach  [69, 70] , which is adapted for generalized-estimating equation analyses of clustered binary outcomes  [65]. In each group, the change over time, from the baseline to the intervention period, will be measured by the respective odds ratio, i. e. the exponent of the difference between log odds of cesarean delivery in intervention versus baseline periods. Then, additional change over time in the intervention group, relative to the concurrent change in the control group, will be estimated by the difference between group-specific differences.
The exponent of the resulting difference-in-differences in log odds provides the adjusted odds ratio, with 95% CIs, for the interaction between group (intervention vs. control) and time (intervention vs. baseline), which will be used as the main measure of the intervention effect  [64, 69, 70]. Two-tailed P values of less than 0. 05 will be considered to indicate statistical significance. All primary analyses will include adjustments for prespecified potential maternal, perinatal and institutional risk factors associated with major perinatal morbidity  [64]. To conform to the intention-to-treat approach, all eligible women who deliver at participating hospitals will be included in the analyses. For adjustment variables for which less than 1% of the data are missing, we will use random imputation (performed on the basis of the observed distributions of the imputed variable and of highly correlated covariates).
Variables for which more than 1% of the data are missing will be excluded from the analyses. Randomization will be stratified by level of care in hospitals. To assess whether the intervention effect will vary according to the level of care, we will test the corresponding three-way interactions: level of care × intervention × time. Subgroup-specific intervention effects will be reported for outcomes with significant three-way interactions (two-tailed tests, with P value of less than 0. 05 will be considered statistically significant)  [69, 70]. Secondary outcomes will be analyzed by means of methods similar to those used for the primary outcome. Subgroup analyses for preterm and term birth will be also planned to take into account major neonatal morbidity related to preterm birth and not related to the mode of delivery.
If the generalized-estimating-equations models do not converge, the intervention effect will be estimated with the use of multivariable logistic model, which do not account for within-hospital clustering; to correct for the resulting underestimation of the standard errors, a conservative P value of less than 0. 001 will be used  [68, 70]. All analyses will be performed with the use of SAS software, version 9. 4 by an independent team whose members will be unaware of the group assignments.
Information and consent forms The participating hospitals are included on the basis of an informed consent form signed by the head of obstetrics. The informed consent form specifies that: (1) the site can withdraw from the program at any time; (2) the data collection will continue until the end of the trial, even if a site withdraw from the project; and 93) that the PRISMA program will be offered to control group hospitals at the end of the trial if the intervention is proven effective. Collection of clinical data from medical records is authorized by the director of professional services in each participating hospital and does not require patient consent. During the intervention period, the involvement of patients will be sought with the use of the decision analysis tool (DAT) and for the LUS thickness measurement.
Interim analyses and stopping rules An independent Data Safety and Monitoring Board (DSMB) has been established, made up of three international experts in epidemiology and biostatistics, reproductive health research, and obstetrics and gynaecology. It will be responsible for ensuring the safety of the trial and for monitoring the progress of the research according to the protocol. Serious adverse events (maternal and perinatal death, perinatal asphyxia, hemostatic, hysterectomy, uterine rupture) will be monitored annually during the intervention by the DSMB, blinded, for all patients in the study. To assess the effectiveness of the program at the end of the first year of the intervention period, an intermediate analysis will be planned using Peto criteria (α = 0. 001), which ensure that a total type-I risk of error, for the final analysis, of 0.
Acknowledgments We wish to thank the  Canadian Institutes of Health Research (CIHR) , our sponsor, which supports the PRISMA trial, grant number  201503MOP-340680-RC1-CFBA-153236. PRISMA Trial research group:  Laval University (Quebec, Canada ):  Nils Chaillet ,  Emmanuel Bujold ,  Suzanne Demers ,  Marylène Dugas ,  Bruno Piedboeuf ;  University of Montreal (Montreal, Canada ):  Mira Johri ,  François Beaudoin ,  Robert Gauthier ,  Benoit Masse ,  François Audibert ,  Louise Duperron ,  Marie Josée Bédard ,  François Champagne ,  Diane Francoeur ;  Sherbrooke University (Sherbrooke, Canada ):  William D. Fraser ,  Jean-Charles Pasquier ;  McGill University (Montreal, Canada ):  Haim Abenhaim ,  Robert Gagnon ,  Patricia Monnier ,  Isabelle Girard ,  Guy-Paul Gagné ;  Northwestern University (Chicago, IL, USA ):  William A.
Data variables, sources of data and data collection Data were sourced from the assessment information collected by the Ebola IPC teams using the MST at county level for each facility. Baseline and 1-year follow-up data were collected respectively in June-July 2015 and April-May 2016. Data were collected on paper during the evaluation visits and entered into an Excel database (Microsoft Corp, Redmond, WA, USA). All records were cross-checked for validity. Output indicators were the overall MST scores for 16 key questions (yielding a score between 0 and 16) and the degree of implementation of six core aspects of IPC practice (Table ). Implementation for each IPC aspect was classified as not implemented (no requirements met), partially implemented (at least one requirement met) or fully implemented (all requirements met).
Data collection Baseline patients' demographic and clinical characteristics, cancer characteristics, site (jugular or subclavian) and side (right or left) of CVC insertion were recorded as well as the insertion procedure duration and the number of venipunctures (>2). According to Good Clinical Practices Guidelines  [15] , Doppler-ultrasonography (DUS) was recommended to guide CVC insertion, which had to be preferably positioned on the right side  [10, 14, 16] , with CVC distal tip at the superior vena cava and the right atrium junction. In women with right BC, CVC insertion was allowed on the left side.
Acknowledgements Other GFTC members significantly contributed to patients inclusion and data collection as co-investigators in the study:  Ismail Elalamy  ( Department of Haematology, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France ),  Grigorios Gerotziafas  ( Department of Haematology, Assistance Publique-Hôpitaux de Paris, Hôpital Tenon, Paris, France ),  Joel Lelong  ( Department of Gynecology, Clinique des Aubépines, Saint-Aubin-sur-Scie, France ),  Sandrine Lavau-Denes  ( Department of Medical Oncology, CHU Dupuytren, Limoges, France ),  Pierre Yves Dubois  ( Department of Surgery, Institut Jean Goudinot, Reims, France ),  Marie Antoinette Sevestre  ( Department of Vascular Medicine, Amiens University Hospital, Amiens, France ), and  Laurent Bastit  ( Department of Radiotherapy ,  Clinique Pasteur ,  Evreux, France).
Indeed, very few measurements for documenting radiative effects of trees in an urban environment are available  (Park et al. , 2012). The objective here is to quantify the performances of TEB in simulating the different contributions of the solar radiation budget for the ensemble of urban facets and vegetation. For this purpose, we compare TEB with the SOLENE software, which is a highspatial-resolution solar and lighting architectural model and which is used in this work as a reference. Various configurations of urban canyons with street trees (that differ in terms of vegetation density and spatial distribution) are studied so that the capacities and limits of the TEB geometric approach can be highlighted and evaluated.
For all experiments, the leaf area index of trees is prescribed to 1, and the albedo is prescribed  to 0. 25 for road, 0. 30 for walls, and 0. 25 for trees. All configurations are described in Figs. 1, 2, 3,  and Table 2. To treat the ensemble of configurations, 55 digital mockups (52 canyons with vegetation and 3 canyons without vegetation) have been built with the computer-aided design (CAD) software Salome V7_4_0. All mockups have been meshed by the GMSH software which is a finite element mesh generator. We have applied a non-uniform meshing here, with a characteristic length of only 1 m in order to refine the spatial discretization of vegetation blocks, whose smallest ones for some of the vegetation layouts do not exceed 2. 4 m width and 2. 5 m height. Each canyon is projected following the four street orientations 0, 45, 90, and 135 • (degrees from geographical north, in the counter trigonometric direction).
Indeed, the way to calculate the transmissivity during multiple reflections is dissimilar between the two models (see Sect. 5. 2. 3). TEB code computes infinite isotropic reflections using a unique view factor for each facet of the canyon and mean radiative transmissivity terms. The formulation of the mean radiative transmissivity terms is based on strong hypotheses on the potential attenuation of rays: they express the ratio between the sector of canyon scanned by the view factor associated with the studied interaction and the thickness of crown contained in this canyon sector (see Appendix B). In addition, reflections from the high vegetation are constrained upwards in TEB (see Sect. 4. 4 and Appendix C for full explanations). On the contrary, SOLENE radiative scheme computes isotropic multiple reflections within the canyon for each triangular mesh, using the radiosity method.
Code availability The TEB code is available in open source via the surface modeling platform SURFEX, downloadable at http://www. cnrm-game-meteo. fr/surfex/. This Open-SURFEX will be updated at relatively low frequency (every 3 to 6 months) and developments presented here are not yet included in the last version. If you need more frequent updates, or if you need what is not in Open-SURFEX (DrHOOK, FA/LFI formats, GAUSSIAN grid), we invite you to follow the procedure to open a SVN account and to access real-time modifications of the code (see instructions in the previous link). E. C. Redon et al. : Implementation of street trees within the solar radiative exchange parameterization the mean radiative transmissivity τ 12 (see Appendix B), and the reflection is then determined according to reflective properties of (1).
Background: The recruitment of community health volunteers (CHVs) to support the delivery of health programmes is an established approach in underserved areas and in particular where there are health inequalities due to the scarcity of trained human resources. However, there is a dearth of evidence about what works to improve CHVs' performance. This review aimed to synthesise existing literature to explain why, how and under which circumstances intervention approaches to improve the performance of CHVs are more likely to be successful. Methods: We performed a realist synthesis. We identified candidate theories related to our review questions, which then guided the selection, appraisal and analysis of primary studies. Publications of interest dating from 2008 to 2012 were identified by a systematic search in PubMed and IDEAS databases.
The CHV's behaviour and work effort is influenced by the degree of motivation and metacognition, which are themselves influenced by the background and past experience of the CHV, the community setting, the social, cultural and political context of the organisational setting and the context of the intervention. The diverse influences on CHVs' performance, informed by the theoretical landscape, are illustrated in Fig. 1. Step 2-searching for evidence Following our scoping review that identified candidate theories, we undertook a search for primary evidence. The search was guided by our research questions and by the candidate theories that were identified in the scoping review. We considered all study designs to be eligible. The search was made in PubMed and IDEAS databases from 2008 to 2012, and the keywords used were community health volunteers, community health workers, lay health workers, and task shifting.
This allowed us to identify a range of primary studies dealing with our initial understanding of how and under what circumstances CHVs may perform well. We decided to focus our search strategy this way because of the huge number of primary studies and some capacity constraints. Indeed, the process of selecting the number of articles that are potentially eligible for inclusion can only occur as the data sources are analysed in detail. As an example, we initially planned to perform a search in various databases and to review the existing evidence published since 2000. However, to provide an Fig. 1  Flow of the diverse influences on CHVs performance example, a search from 2000 to 2014 in PubMed using community health workers, community health volunteers as keyword provides 3339 items. Some articles can be easily excluded on the title or on the abstract.