dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions and future of the EUROCOM project The EUROCOM project delivered a set of European NEE estimates at a 0. 5 • , monthly resolution at the disposal of the scientific community  (Monteil et al. , 2020). The data can be used as a comparison and validation dataset for both bottom-up and inverse modellers. The input datasets (observations and prior fluxes) remain available for inverse modelling groups willing to submit additional inversions, and we expect the size and robustness of the ensemble to grow over time. An extension of the inversions until 2019 is currently ongoing. Our best posterior estimate (ensemble median) of the longterm mean annual terrestrial European NEE of -0. 15 ± 0. 08 Pg C yr -1 over the years 2006-2015 is comparable to the median value of -0. 3±0. 11 Pg C yr -1 from our prior estimates as well as recent estimates from other studies (e.
g. Scholze et al. , 2019; Crowell et al. , 2019 , albeit for a slightly different domain). Since our domain here does not cover the European part of Russia, the area that is postulated to contribute most to the large European carbon sink (see for example  Reuter et al. , 2017) , we cannot resolve this controversy here with our intercomparison. We deliberately kept the requirements in the intercomparison protocol (i. e. use of prescribed common datasets or inversion set-ups) to a minimum (namely, prescribed fossil fuel emissions and common domain) to encourage the participation of voluntary contributions from regional atmospheric inverse modelling groups. Such an intercomparison approach, where a large number of parameters influencing results of the inversions vary from one system to another, presents the advantage that the resulting distribution of results provides a good approximation of the distribution of uncertainties on the net European terrestrial carbon flux.
We thank ICOS-ERIC for financial support and providing the collaboration platforms for data sharing and analysis. Finally, we thank the data providers from the GLOBALVIEW-plus v3. 2 product and from the WDCGG for the atmospheric CO 2 observations used in the inversions, and the ICOS Atmospheric Thematic Center for providing the CO 2 measurements from CarboEurope-IP, GHG-Europe and ICOS Preparatory Phase. Specifically, the data were provided by NOAA Global Monitoring Division (BAL, BSC, CIB, HPB, LMP, OXK and STM); Laboratoire des Sciences du Climat et de l'Environnement (GIF, MHD, OPE, PUY and TRN); Institut de Ciencia i Tecnologia Ambientals, Universitat Autonoma de Barcelona (ELL, LMU, SSC and VAC); Atmospheric Chemistry Research Group, School of Chemistry University of Bristol (RGL, TTA and TAC); Max Planck Institute for Biogeochemistry (BIK and OXK); Finnish Meteorological Institute (PAL and PUI); Umweltbundesamt (SSL and WES);  Review statement.
Acknowledgements. We thank the  Swedish Research Council  for funding the  EUROCOM  project (Dnr  349-2014-6576 ). Marko Scholze  and  Guillaume Monteil  acknowledge support from the three Swedish strategic research areas ModElling the Regional and Global earth system (MERGE), the e-science collaboration (eSSENCE), and  Biodiversity and Ecosystems in a Changing Climate (BECC). Guillaume Monteil  thanks the  NSC at Lindköping University  (part of the  Swedish National Infrastructure for Computing, SNIC ) for providing computer resources for the LUMIA simulations. Grégoire Broquet  and  Jerôme Tarniewicz  acknowledge the support by  Léonard Rivier  (for the transmission of pre-ICOS data),  Frédéric Chevallier  and  Isabelle Pison  (for the continuous development and maintenance of the PYVAR-CHIMERE system).
Frank- Thomas Koch ,  Christian Rödenbeck , and  Christoph Gerbig  thank the  Deutsches Klimarechenzentrum (DKRZ)  for use of the high-performance computing facilities. Naomi E. Smith  and  Ingrid T. Luijkx  benefited from computing resources from the  Netherlands Organization for Scientific Research (NWO ; grant no. SH-312 ,  17616 ). Naomi E. Smith was funded by  NWO/OCW  for Ruisdael/ICOS-NL. Ingrid T. Luijkx was funded by a  NWO   Veni grant  ( 016. Veni. 171. 095 ). Emily White was funded by the  UK Natural Environment Research Council (NERC )  GW4+   Doctoral Training Partnership. Anita L. Ganesan  is funded through a  NERC Independent Research Fellowship   NE/L010992/1. Matt Rigby was supported by  NERC  grants  NE/K002236/1  and  NE/S004211/1.
Data availability. The prior and posterior fluxes from the EU-ROCOM ensemble of inversions are available for download at the ICOS Carbon Portal (https://doi. org/10. 18160/G068-1T09, Monteil et al. , 2020 ; https://doi. org/10. 18160/KNWQ-9397, Thompson, 2019; https://doi. org/10. 18160/A7M2-TM1V, Koch and Gerbig, 2020; https://doi. org/10. 18160/RF8X-8RJ2, Monteil, 2020; https://doi. org/10. 18160/6179-A02U, White et al. , 2019a;   https://doi. org/10. 18160/3YGA-X0HR, Lang and Broquet, 2019; https://doi. org/10. 18160/ZA4Q-MHF4, Smith et al. , 2020). Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/acp-20-12063-2020-supplement.
Acknowledgements: This research received financial support from the GINOP-2. 3. 2-15-2016-00009 research program and the ELTE Institutional Excellence Program (1783-3/2018/FEKUTSRAT) managed by the Hungarian Ministry of Human Capacities. This work has been com- pleted with the support of the Lendület Research Grant to the MTA CSFK Lendület Pannon LitH 2 Oscope Research Group. Jaroslav Lexa,.
This is largely due to the susceptibility of the elderly to become ill and it is also due to the prevalence of polypharmacy in this population. In a 2008 study, the use of the STOPP list identified IPs in 35% of a cohort of elderly patients; one third of these IPs were associated with an adverse drug event  [8]. Another study involving randomized hospitalized patients showed that the occurrence of IP was 35% lower in patients who were prescribed drugs according to STOPP/START criteria than in patients for whom usual pharmaceutical criteria were used  [9]. Pediatric prescription is also in need of additional securing; for this reason, a first IP tool in pediatrics called POPI (Pediatrics: Omission of Prescriptions and Inappropriate prescriptions) has been developed in France. POPI was composed of a list of inappropriate prescriptions and omissions linked to pediatric health problems, identified in 2010 according to the frequency of hospitalization related to them and their prevalence according to pediatric data extracted from the French National Health Insurance Fund for Employees.
For each of the chosen pediatric health problems, recommendations that were both backed up by evidence and published after 2000 were identified. Based on these recommendations, a consensual survey allowed us to develop the POPI tool  [10]. However, POPI was constructed to satisfy French standards, established by national experts, with a strong reliance on French databases, drug availability and unique problematics. Since the need for such a tool has been identified internationally, our aim is to adapt POPI at the international level, using health professionals from different countries to identify which items could be of worldwide use.
Acknowledgments The authors would like to thank every experts for sharing their knowledge:  Abrogoua Danho Pascal  (pharmacist),  Bedard Pascal (pharmacist) ,  Cavalcanti Da Silva Izabel Cristina  (physician),  Choonara Imti  (physician),  Chua Siew Siang  (pharmacist),  Costa Alves Manuela  (physician),  Da Silva Desmothenes  (pharmacist),  Dalgic Nazan  (physician),  Desmet Sophie  (pharmacist),  Di Paolo Ermindo  (pharmacist),  Fortunato Ana  (pharmacist),  Kleiber Niina  (physician),  Ming Lai Nai  (physician),  Nguyen Hoang Phuong Khanh  (pharmacist),  Nguyen Thi My Phuong  (physician),  Pauchard Jean-Yves  (physician),  Sammons Helen  (physician),  Sancar Mesut  (pharmacist),  Semple Diarmaid  (pharmacist),  Zhao Wei  (pharmacist).
Aged accidental fall patient readmission systematic review a b s t r a c t Objectives: Falls are an important issue in older adults as they are frequent, deleterious, and often lead to repeated consultations at the emergency department (ED) and unplanned hospitalizations. Our principal objective was to provide an inventory of interventions designed to prevent unplanned readmissions or ED visits of older patients presenting to hospital with a fall. Design: Systematic review performed on February 11, 2019 in MEDLINE via PubMed, EMBASE, Cochrane Central Register of Controlled Trials, and Web of Science, without date or language restriction. We manually updated this search in August 1, 2019. Study selection, data extraction and risk of bias assessment were conducted independently by 2 reviewers.
Enrolment and informed consent procedure Prior to enrolment, all community health workers, nurse research officers and MoH medical staff implicated in the study were trained on the trial protocol, standardised operating procedures and the correct use of tools developed for data collection. Nurse research officers were specifically trained to enrol and randomise study participants, and monitor home visits and outpatient visits at the health centre. Children were recruited through monthly active mass malnutrition screenings in each of the 60 villages. Concomitantly, children attending outpatient consultations at the four study health centres underwent routine passive malnutrition screening and were enrolled in the trial if eligible. In both active and passive screening, a nurse research officer, assisted by a community health worker, collected anthropometric (weight, height, MUAC, WHZ) and clinical (presence of oedema) information on eligible children.
Data collection and management After obtaining individual informed consent, all sociodemographic characteristics, anthropometric and clinical data collected during follow-up were documented in the case report forms by the research officers and the healthcare providers trained specifically for this study. All data entered into the database were securely transferred and stored on a server hosted by PAC-CI, a satellite for the French National Agency for Research on AIDS and Viral Hepatitis in Abidjan, Côte d'Ivoire which served as the methodology and coordinating centre for this study. All data and any adverse events, including deaths and hospitalisations, were rigorously monitored both on-site and remotely, according to the data monitoring plan. To ensure patient safety and data integrity, the methodology and coordinating centre continuously supervised data management activities, and the senior scientific project leader and investigators performed field visits on a regular basis.
Statistical analyses All statistical analyses will be performed using RStudio Software (Boston, Massachusetts, USA) as specified by the data analysis plan published on ClinicalTrials. gov prior to performing any analysis. Statistical tests will be Open access carried out bilaterally with an alpha risk of 5% and unilaterally with an alpha risk of 2. 5% for the non-inferiority analysis. Qualitative variables will be described in terms of numbers, percentages and provided with CIs when relevant. If necessary, comparisons of qualitative variables will be made using χ 2 or Fisher exact tests. Quantitative variables will be described in terms of mean, SD and CI or median, range and IQR. If necessary, comparisons of quantitative variables will be made using Student's, Wilcoxon's or the Kruskal-Wallis tests, depending on the distribution of the variable of interest.
Safety The trial was monitored monthly by an international steering committee and quarterly by a national steering committee where any adverse events were presented. No interim analysis was planned before the final analyses. The data safety monitoring board could have requested Open access an interim analysis if it deemed it necessary for patient safety. A child in intervention arm could be removed from the study for two reasons: (1) if he or she had two episodes of >5% weight loss during the course of treatment and (2) if he or she was not SAM at inclusion but deteriorated to SAM during RUTF supplementation.
Acknowledgements We are indebted to the women and children who participate in the study. The authors wish to particularly acknowledge the ALIMA operational team on the ground who managed the study and the nutrition programme on a day-to-day basis. The authors also acknowledge the MoH of the DRC through the commitment of key representatives from the  Kamuesha Health Zone  and the  National Nutrition Programme. We acknowledge the implementing partners of the interagency Nutrition Cluster Kasaï Province, in particular representatives from  UNICEF  and the  World Food Programme. We also acknowledge  Maguy Daures  ( Inserm UMR 1219, Bordeaux ),  Valérie Journot  ( Inserm UMR 1219, Bordeaux ) and  Claire Levy-Marchal  ( ALIMA, Paris ) for having advising the study team on the trial methodology. This study was developed as part of the Clinical and  Operational Research Alliance (CORAL).
LIB, GTS coordinate the MoH staff working in the trial. CC, VH, HB, LIB, GTS, AB, CY and RB organise and supervise data collection. CY created the software tool for randomisation and developed the database. CC, VH, DG, XA, SS and RB developed the statistical analysis strategy. CC wrote the first draft of the manuscript. SS and on March 8, 2021 by guest. Protected by copyright. http://bmjopen. bmj. com /BMJ Open : first published as 10. 1136/bmjopen-2020-041213 on 2 December 2020. Downloaded from.
Ethics and dissemination Ethics approvals were obtained from the  National Health Ethics Committee of the Democratic Republic of Congo  and from the  Ethics Evaluation Committee of Inserm , the  French National Institute for Health and Medical Research draft  and had a substantial writing contribution to the development of the final manuscript. Funding The study was supported by the  Innocent Foundation (London, UK) , grant number  ALIMA-2018-DRC , and received additional funding from  European Commission  through the  European Civil Protection and Humanitarian Aid Operations  ( ECHO, Brussels, Belgium ), grant number  ECHO/COD/BUD/2018/91023. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. This document covers humanitarian aid activities implemented with the financial assistance of the  European Union.
Strengths and limitations of this study  Linking death certification codes with service use in the 12 months before death allowed us to analyse the impact of different illnesses on unscheduled care service use.  We linked all five unscheduled NHS services (telephone advice, primary care, ambulances, emergency department and hospital admission) into Continuous Unscheduled Pathways (CUPs) and identified common patterns of unscheduled care for people.  This innovative, population based method provided a broad understanding of how different demographic factors affected use of unscheduled care throughout Scotland.  Only one of the datasets, primary care out-of-hours, contained information that could indicate whether a person was identified for palliative care.  Costs were calculated using weighted averages and were therefore approximate.
Summary: Objectives To analyse patterns of use and costs of unscheduled NHS services for people in the last year of life. Design Retrospective cohort analysis of national datasets with application of standard UK costings Participants and setting All people who died in Scotland in 2016 aged 18 or over  (n= 56,407)  Main outcome measures Frequency of use of the five unscheduled NHS services in the last 12 months of life by underlying cause of death; patient demographics; Continuous Unscheduled Care pathways (CUPs) followed by patients during each care episode; total NHS and per-patient costs. Results 53,509 patients (94. 9%) had at least one contact with an unscheduled care service during their last year of life ( 472,360 contacts) with 34. 2% in the last month of life. By linking patient contacts during each episode of care, we identified 206,841 Continuous Unscheduled Care pathways (CUPs); with 133,980 (64.
However, palliative care integration into unscheduled care services has proven particularly challenging. [9, 10]  National datasets can be used to monitor and improve care. They have underutilised potential to improve end-of-life care. [11] [12] [13] [14] [15]  In Scotland, death registry data, and activity data from hospitals, the ambulance service, and out-of-hours primary care services are collected routinely. These national datasets contain a unique identifier-the Community Health Index (CHI). We set out to link these data to analyse patterns of unscheduled care services use and costs by underlying cause of death and patient demographics.
Methods We linked three datasets. The National Records of Scotland (NRS) deaths dataset was used to identify all adults (aged 18+) who died in Scotland in 2016. From this dataset we extracted underlying cause of death and usual place of residence. From the General Acute Inpatient and Day Case -Scottish Morbidity Record (SMR01) we extracted all unscheduled hospital activity for the last 12 months life for the cohort. Thirdly, we extracted data from the Scottish Unscheduled Care Datamart (UCD) covering four unscheduled care services: the telephone advice line (NHS24), primary care out-of-hours (PCOOH), the Scottish ambulance service (SAS), and emergency department attendances (ED). [16]  The UCD does not include in-hours, unscheduled primary care. The ICD codes (v 2010) for underlying cause of death extracted from the NRS dataset were classified into five groups: cancer, organ failure, frailty/progressive neurological conditions, various other causes, and external causes.
[17]  People in the first three groups were considered potentially to have had palliative care needs during their last year of life. Details of this coding allocation had been agreed previously by an expert international panel. [18]  (See online supplementary Table  1 ) Postcodes of usual place of residence were extracted from the NRS dataset. We used the Scottish Index of Multiple Deprivation (SIMD 2016) to infer quintiles of deprivation. [19]  Rurality was based on the Scottish Government Urban-Rural Classification as applied to the postcodes. [20]  In order to understand how multiple services were accessed during a single healthcare episode, we used Continuous Unscheduled Pathways (CUPs) as defined in the Scottish unscheduled care datamart. A CUP is a linked set of contacts with one or more unscheduled care services.
[16]  Each CUP represents a single patient journey. The frequencies of the different types of CUP were tabulated to identify key patterns. We categorised a CUP as 'out-of-hours' if it started at weekends, on public holidays or on weeknights from 6pm to 8am. There is no limit to the duration of each CUP so a CUP could start out-of-hours but end during the in-hours period and vice-versa. Therefore, only the start date and time of the CUP was used to categorise it. In the Unscheduled Care Dataset, each service component of a CUP is assigned a code letter: Cost estimations: Standard UK price weighting methodology was applied to estimate the costs of each unscheduled service: see online supplementary Table  2  to explain how this was calculated. We did not attribute exact pricing to different forms of inpatient admission or account for differences due to patient demographics hence mean population values were applied.
Limitations The structure and scope of unscheduled care services in Scotland influenced how those services were used so comparisons with different countries and healthcare systems will need care. Lack of national data for in-hours, unscheduled primary care was limiting. Some CUPs recorded as out-of-hours may have started with an undocumented, urgent primary care contact in-hours. Timing of acute hospital admissions is not recorded so could not be separated by starting point. Costs were calculated using weighted averages and were therefore approximate. We acknowledge limitations in relying on ICD-10 recorded diagnoses. We had intended to look for evidence that patients had been identified for palliative care. Unfortunately, only the primary care out-of-hours dataset had a palliative care code or recorded access to the Scottish electronic care plan (Key Information Summary) used by primary care teams to coordinate palliative and anticipatory care planning.
Conclusions The extent of unscheduled care delivered to people in their last year of life is significantly greater and more varied than reported previously. People with diverse urgent care needs are accessing these services at high levels, particularly in their final month of life. More should be done to take account of underlying illness trajectories and social determinants of health, including better public understanding of how to access the right care in timely and effective ways. Systematic approaches to care planning combined with effective recording and sharing of key information, including a palliative care code where appropriate, is vital and should be recorded in routine healthcare datasets. The authors acknowledge the support of National Services Scotland for their involvement of obtaining approvals, provisioning and data linkage.
Participants and procedure A total of 165 unemployed people participated in this study. According to the guidelines of the International Labour Organization, an unemployed person is a mature person without work who is actively looking for a job  (Eurostat, 2019). Participants were addressed personally at the Agence pour le Développment de l'EMploi (ADEM), the Public Employment Services (PES) in Luxembourg. They were informed that the questionnaire was part of an academic study conducted by the University of Luxembourg. Additionally, participants had to give their consent that the data could be used for research purposes, and they had to consent to the publication of the results of the study. Participation was voluntary and confidential. Modalities for data collection have been accepted by both the FNR experts and the public employment services' partners in France (Pôle emploi) and Luxembourg (ADEM).
| Study design and population This study is part of a larger population-based cohort study (Effective Perinatal Intensive Care in Europe, EPICE) on the use of evidencebased interventions for the care of VP infants in Europe. 11 All births occurred from 22  +0  to 31 +6 weeks GA between June 2011 and May 2012 were included. Follow-up data were recorded at two years CA using a postal parent-report questionnaire or telephone interview. In the three participating Italian regions (Lazio, Emilia-Romagna and Marche), 732 questionnaires were collected (response rate 75. 6%). In these regions in 2011, there were approximately 100 000 live births, corresponding to about 19% of total live births in Italy. Ethics Committee approval and parental informed consent were obtained according to national rules.
| Measurements Data describing the infants' perinatal health risks were abstracted from clinical records using common definitions and a pre-coded form. GA was the best obstetric estimate based on information on the last menstrual period and ultrasound measures. Small for gestational age was defined as birth weight <10th percentile using the intrauterine growth charts obtained from the Hadlock's foetal growth equation and adapted to our population using the sex-specific mean and standard deviation of birth weight at 40 weeks GA in Italy in 2010. 12 Severe congenital anomalies were those reported by the EUROCAT network. 13 Recorded morbidities in NICU included necrotising enterocolitis (NEC), culture-confirmed sepsis, intraventricular haemorrhage grade 3°-4°, cystic periventricular leukomalacia, retinopathy of prematurity stage III-IV and bronchopulmonary dysplasia (BPD), defined as oxygen supplementation at 36 weeks GA.