Background: Significant resource constraints and critical care training gaps are responsible for the limited development of intensive care units (ICUs) in resource limited settings. We describe the implementation of a...Background: Significant resource constraints and critical care training gaps are responsible for the limited development of intensive care units (ICUs) in resource limited settings. We describe the implementation of an ICU in Haiti and report the successes and difficulties encountered throughout the process. We present a consecutive case series investigating an anesthesiologist, emergency, and critical care physician implemented endotracheal intubation and mechanical ventilation protocol in an austere environment with the assistance of telemedicine. Methods: A consecutive case series of fifteen patients admitted to an ICU at St. Luc Hospital located in Portau-Prince, Haiti, between the months of February 2012 to April 2014 is reported. Causes of respiratory failure and the clinical course are presented. Patients were followed to either death or discharge. Results: Fifteen patients (eight women and seven men) were included in the study with an average age of 37.7 years. The mean duration of ventilation was three days. Of the fifteen patients intubated, five patients (33.3%) survived and were discharged from the ICU. Of the five surviving patients, two were intubated for status epilepticus, one for status asthmaticus and one for hyperosmolar coma associated with intracerebral hemorrhage. Of the patients dying on the ventilator, four patients died from pneumonia, two from renal failure, and one from tetanus. The remaining three died from strokes and cardiac arrests. Conclusions: Mortality of mechanically ventilated patients in a resource-limited country is significant. Focused training in core critical care skills aimed at increasing the endotracheal intubation and ventilatory management capacity of local medical staff should be a priority in order to continue to develop ICUs in these austere environments. Collaborative educational and training efforts directed by anesthesiologists, emergency, and critical care physicians, and aided by telemedicine can facilitate realizing this goal.展开更多
随着 VoIP 逐渐成为消费者和企业通讯的主要方式,服务供应商正努力搜集客户意见,希望从客户端设备上吸取经验以便改良下一代产品,进而提升 VoIP使用感受。有线电视供应商、提供 ADSL 服务的传统电信供应商以及未提供宽带服务的 VoIP 新...随着 VoIP 逐渐成为消费者和企业通讯的主要方式,服务供应商正努力搜集客户意见,希望从客户端设备上吸取经验以便改良下一代产品,进而提升 VoIP使用感受。有线电视供应商、提供 ADSL 服务的传统电信供应商以及未提供宽带服务的 VoIP 新创公司分别采取不同策略争取同一客户群,这将对 VoIP 客户端设备的设计造成重大影响。展开更多
The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implem...The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implementations,but provide guidance for improving Findability,Accessibility,Interoperability and Reusability of digital resources.This has likely contributed to the broad adoption of the FAIR principles,because individual stakeholder communities can implement their own FAIR solutions.However,it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations.Thus,while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways,for true interoperability we need to support convergence in implementation choices that are widely accessible and(re)-usable.We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible,robust,widespread and consistent FAIR implementations.Any self-identified stakeholder community may either choose to reuse solutions from existing implementations,or when they spot a gap,accept the challenge to create the needed solution,which,ideally,can be used again by other communities in the future.Here,we provide interpretations and implementation considerations(choices and challenges)for each FAIR principle.展开更多
The FAIR guiding principles aim to enhance the Findability,Accessibility,Interoperability and Reusability of digital resources such as data,for both humans and machines.The process of making data FAIR(“FAIRification...The FAIR guiding principles aim to enhance the Findability,Accessibility,Interoperability and Reusability of digital resources such as data,for both humans and machines.The process of making data FAIR(“FAIRification”)can be described in multiple steps.In this paper,we describe a generic step-by-step FAIRification workflow to be performed in a multidisciplinary team guided by FAIR data stewards.The FAIRification workflow should be applicable to any type of data and has been developed and used for“Bring Your Own Data”(BYOD)workshops,as well as for the FAIRification of e.g.,rare diseases resources.The steps are:1)identify the FAIRification objective,2)analyze data,3)analyze metadata,4)define semantic model for data(4a)and metadata(4b),5)make data(5a)and metadata(5b)linkable,6)host FAIR data,and 7)assess FAIR data.For each step we describe how the data are processed,what expertise is required,which procedures and tools can be used,and which FAIR principles they relate to.展开更多
In order to provide responsible access to health data by reconciling benefits of data sharing with privacy rights and ethical and regulatory requirements,Findable,Accessible,Interoperable and Reusable(FAIR)metadata sh...In order to provide responsible access to health data by reconciling benefits of data sharing with privacy rights and ethical and regulatory requirements,Findable,Accessible,Interoperable and Reusable(FAIR)metadata should be developed.According to the H2020 Program Guidelines on FAIR Data,data should be"as open as possible and as closed as necessary","open"in order to foster the reusability and to accelerate research,but at the same time they should be"closed"to safeguard the privacy of the subjects.Additional provisions on the protection of natural persons with regard to the processing of personal data have been endorsed by the European General Data Protection Regulation(GDPR),Reg(EU)2016/679,that came into force in May 2018.This work aims to solve accessibility problems related to the protection of personal data in the digital era and to achieve a responsible access to and responsible use of health data.We strongly suggest associating each data set with FAIR metadata describing both the type of data collected and the accessibility conditions by considering data protection obligations and ethical and regulatory requirements.Finally,an existing FAIR infrastructure component has been used as an example to explain how FAIR metadata could facilitate data sharing while ensuring protection of individuals.展开更多
Since their publication in 2016 we have seen a rapid adoption of the FAIR principles in many scientific disciplines where the inherent value of research data and,therefore,the importance of good data management and da...Since their publication in 2016 we have seen a rapid adoption of the FAIR principles in many scientific disciplines where the inherent value of research data and,therefore,the importance of good data management and data stewardship,is recognized.This has led to many communities asking“What is FAIR?”and“How FAIR are we currently?”,questions which were addressed respectively by a publication revisiting the principles and the emergence of FAIR metrics.However,early adopters of the FAIR principles have already run into the next question:“How can we become(more)FAIR?”This question is more difficult to answer,as the principles do not prescribe any specific standard or implementation.Moreover,there does not yet exist a mature ecosystem of tools,platforms and standards to support human and machine agents to manage,produce,publish and consume FAIR data in a user-friendly and efficient(i.e.,“easy”)way.In this paper we will show,however,that there are already many emerging examples of FAIR tools under development.This paper puts forward the position that we are likely already in a creolization phase where FAIR tools and technologies are merging and combining,before converging in a subsequent phase to solutions that make FAIR feasible in daily practice.展开更多
文摘Background: Significant resource constraints and critical care training gaps are responsible for the limited development of intensive care units (ICUs) in resource limited settings. We describe the implementation of an ICU in Haiti and report the successes and difficulties encountered throughout the process. We present a consecutive case series investigating an anesthesiologist, emergency, and critical care physician implemented endotracheal intubation and mechanical ventilation protocol in an austere environment with the assistance of telemedicine. Methods: A consecutive case series of fifteen patients admitted to an ICU at St. Luc Hospital located in Portau-Prince, Haiti, between the months of February 2012 to April 2014 is reported. Causes of respiratory failure and the clinical course are presented. Patients were followed to either death or discharge. Results: Fifteen patients (eight women and seven men) were included in the study with an average age of 37.7 years. The mean duration of ventilation was three days. Of the fifteen patients intubated, five patients (33.3%) survived and were discharged from the ICU. Of the five surviving patients, two were intubated for status epilepticus, one for status asthmaticus and one for hyperosmolar coma associated with intracerebral hemorrhage. Of the patients dying on the ventilator, four patients died from pneumonia, two from renal failure, and one from tetanus. The remaining three died from strokes and cardiac arrests. Conclusions: Mortality of mechanically ventilated patients in a resource-limited country is significant. Focused training in core critical care skills aimed at increasing the endotracheal intubation and ventilatory management capacity of local medical staff should be a priority in order to continue to develop ICUs in these austere environments. Collaborative educational and training efforts directed by anesthesiologists, emergency, and critical care physicians, and aided by telemedicine can facilitate realizing this goal.
文摘随着 VoIP 逐渐成为消费者和企业通讯的主要方式,服务供应商正努力搜集客户意见,希望从客户端设备上吸取经验以便改良下一代产品,进而提升 VoIP使用感受。有线电视供应商、提供 ADSL 服务的传统电信供应商以及未提供宽带服务的 VoIP 新创公司分别采取不同策略争取同一客户群,这将对 VoIP 客户端设备的设计造成重大影响。
基金The work of A.Jacobsen,C.Evelo,M.Thompson,R.Cornet,R.Kaliyaperuma and M.Roos is supported by funding from the European Union’s Horizon 2020 research and innovation program under the EJP RD COFUND-EJP N°825575.The work of A.Jacobsen,C.Evelo,C.Goble,M.Thompson,N.Juty,R.Hooft,M.Roos,S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista is supported by funding from ELIXIR EXCELERATE,H2020 grant agreement number 676559.R.Hooft was further funded by NL NWO NRGWI.obrug.2018.009.N.Juty and C.Goble were funded by CORBEL(H2020 grant agreement 654248)N.Juty,C.Goble,S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista were funded by FAIRplus(IMI grant agreement 802750)+13 种基金N.Juty,C.Goble,M.Thompson,M.Roos,S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista were funded by EOSClife H2020-EU(grant agreement number 824087)C.Goble was funded by DMMCore(BBSRC BB/M013189/)M.Thompson,M.Roos received funding from NWO(VWData 400.17.605)S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista have been funded by grants awarded to S-A.Sansone from the UK BBSRC and Research Councils(BB/L024101/1,BB/L005069/1)EU(H2020-EU 634107H2020-EU 654241,IMI(IMPRiND 116060)NIH Data Common Fund,and from the Wellcome Trust(ISA-InterMine 212930/Z/18/ZFAIRsharing 208381/A/17/Z)The work of A.Waagmeester has been funded by grant award number GM089820 from the National Institutes of Health.M.Kersloot was funded by the European Regional Development Fund(KVW-00163).The work of N.Meyers was funded by the National Science Foundation(OAC 1839030)The work of M.D.Wilkinson is funded by Isaac Peral/Marie Curie cofund with the Universidad Politecnica de Madrid and the Ministerio de Economia y Competitividad grant number TIN2014-55993-RMThe work of B.Magagna,E.Schultes,L.da Silva Santos and K.Jeffery is funded by the H2020-EU 824068The work of B.Magagna,E.Schultes and L.da Silva Santos is funded by the GO FAIR ISCO grant of the Dutch Ministry of Science and CultureThe work of G.Guizzardi is supported by the OCEAN Project(FUB).M.Courtot received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No.802750.R.Cornet was further funded by FAIR4Health(H2020-EU grant agreement number 824666)K.Jeffery received funding from EPOS-IP H2020-EU agreement 676564 and ENVRIplus H2020-EU agreement 654182.
文摘The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implementations,but provide guidance for improving Findability,Accessibility,Interoperability and Reusability of digital resources.This has likely contributed to the broad adoption of the FAIR principles,because individual stakeholder communities can implement their own FAIR solutions.However,it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations.Thus,while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways,for true interoperability we need to support convergence in implementation choices that are widely accessible and(re)-usable.We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible,robust,widespread and consistent FAIR implementations.Any self-identified stakeholder community may either choose to reuse solutions from existing implementations,or when they spot a gap,accept the challenge to create the needed solution,which,ideally,can be used again by other communities in the future.Here,we provide interpretations and implementation considerations(choices and challenges)for each FAIR principle.
基金The work of A.Jacobsen,R.Kaliyaperumal,M.Roos and M.Thompson is supported by funding from the European Union’s Horizon 2020 research and innovation program under the EJP RD COFUND-EJP N°825575The work of A.Jacobsen,R.Kaliyaperumal,M.Roos and M.Thompson is supported by funding from ELIXIR EXCELERATE,H2020 grant agreement number 676559.M.Roos and M.Thompson received funding from NWO(VWData 400.17.605)H2020-EU 824087.The work of B.Mons and L.O.Bonino da Silva Santos is funded by the H2020-EU 824068 and the GO FAIR ISCO grant of the Dutch Ministry of Science and Culture.
文摘The FAIR guiding principles aim to enhance the Findability,Accessibility,Interoperability and Reusability of digital resources such as data,for both humans and machines.The process of making data FAIR(“FAIRification”)can be described in multiple steps.In this paper,we describe a generic step-by-step FAIRification workflow to be performed in a multidisciplinary team guided by FAIR data stewards.The FAIRification workflow should be applicable to any type of data and has been developed and used for“Bring Your Own Data”(BYOD)workshops,as well as for the FAIRification of e.g.,rare diseases resources.The steps are:1)identify the FAIRification objective,2)analyze data,3)analyze metadata,4)define semantic model for data(4a)and metadata(4b),5)make data(5a)and metadata(5b)linkable,6)host FAIR data,and 7)assess FAIR data.For each step we describe how the data are processed,what expertise is required,which procedures and tools can be used,and which FAIR principles they relate to.
基金Part of this work is funded by the NWA program(project VWData-400.17.605)by the Netherlands Organization for Scientific Research(NWO)by the European Joint Program Rare Diseases(grant agreement#825575)and ELIXIR-EXCELERATE(H2020-INFRADEV-1-2015-12).
文摘In order to provide responsible access to health data by reconciling benefits of data sharing with privacy rights and ethical and regulatory requirements,Findable,Accessible,Interoperable and Reusable(FAIR)metadata should be developed.According to the H2020 Program Guidelines on FAIR Data,data should be"as open as possible and as closed as necessary","open"in order to foster the reusability and to accelerate research,but at the same time they should be"closed"to safeguard the privacy of the subjects.Additional provisions on the protection of natural persons with regard to the processing of personal data have been endorsed by the European General Data Protection Regulation(GDPR),Reg(EU)2016/679,that came into force in May 2018.This work aims to solve accessibility problems related to the protection of personal data in the digital era and to achieve a responsible access to and responsible use of health data.We strongly suggest associating each data set with FAIR metadata describing both the type of data collected and the accessibility conditions by considering data protection obligations and ethical and regulatory requirements.Finally,an existing FAIR infrastructure component has been used as an example to explain how FAIR metadata could facilitate data sharing while ensuring protection of individuals.
基金Part of this work is funded by the NWA program(project VWData-400.17.605)by the Netherlands Organization for Scientific Research(NWO)+1 种基金by the European Joint Program Rare Diseases(grant agreement#825575)ELIXIR-EXCELERATE(H2020-INFRADEV-1-2015-12).
文摘Since their publication in 2016 we have seen a rapid adoption of the FAIR principles in many scientific disciplines where the inherent value of research data and,therefore,the importance of good data management and data stewardship,is recognized.This has led to many communities asking“What is FAIR?”and“How FAIR are we currently?”,questions which were addressed respectively by a publication revisiting the principles and the emergence of FAIR metrics.However,early adopters of the FAIR principles have already run into the next question:“How can we become(more)FAIR?”This question is more difficult to answer,as the principles do not prescribe any specific standard or implementation.Moreover,there does not yet exist a mature ecosystem of tools,platforms and standards to support human and machine agents to manage,produce,publish and consume FAIR data in a user-friendly and efficient(i.e.,“easy”)way.In this paper we will show,however,that there are already many emerging examples of FAIR tools under development.This paper puts forward the position that we are likely already in a creolization phase where FAIR tools and technologies are merging and combining,before converging in a subsequent phase to solutions that make FAIR feasible in daily practice.
