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Guidelines for Perioperative Care in Bariatric Surgery: Enhanced Recovery After Surgery (ERAS) Society Recommendations: A 2021 Update.减重手术围手术期护理指南:术后加速康复(ERAS)学会推荐意见:2021年更新版
World J Surg. 2022 Apr;46(4):729-751. doi: 10.1007/s00268-021-06394-9. Epub 2022 Jan 4.
2
De-novo FAIRification via an Electronic Data Capture system by automated transformation of filled electronic Case Report Forms into machine-readable data.通过电子数据采集系统对填写好的电子病例报告表进行自动化转换,从而实现新的 FAIR 化,将其转化为机器可读的数据。
J Biomed Inform. 2021 Oct;122:103897. doi: 10.1016/j.jbi.2021.103897. Epub 2021 Aug 26.
3
Assessing the risk of performance and detection bias in Cochrane reviews as a joint domain is less accurate compared to two separate domains.评估 Cochrane 综述中性能和检测偏倚的风险作为一个联合领域不如两个单独领域准确。
BMC Med Res Methodol. 2021 Jul 18;21(1):149. doi: 10.1186/s12874-021-01339-1.
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A cautionary note on a recently proposed sensitivity analysis for unmeasured confounding.关于最近提出的未测量混杂因素敏感性分析的警示说明。
Int J Epidemiol. 2021 Jul 9;50(3):711-716. doi: 10.1093/ije/dyaa258.
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A living mapping review for COVID-19 funded research projects: final (27 month) update.一项关于新冠病毒资助研究项目的实时图谱综述:最终(27个月)更新
Wellcome Open Res. 2023 Jul 26;5:209. doi: 10.12688/wellcomeopenres.16259.10. eCollection 2020.
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From Raw Data to FAIR Data: The FAIRification Workflow for Health Research.从原始数据到 FAIR 数据:健康研究的 FAIR 化工作流程。
Methods Inf Med. 2020 Jun;59(S 01):e21-e32. doi: 10.1055/s-0040-1713684. Epub 2020 Jul 3.
7
Assessing risk of bias judgments for blinding of outcome assessors in Cochrane reviews.评估Cochrane系统评价中结局评估者设盲的偏倚风险判断
J Comp Eff Res. 2020 Jun;9(8):585-593. doi: 10.2217/cer-2019-0181. Epub 2020 May 27.
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Evaluating FAIR maturity through a scalable, automated, community-governed framework.通过可扩展的、自动化的、社区管理的框架评估 FAIR 成熟度。
Sci Data. 2019 Sep 20;6(1):174. doi: 10.1038/s41597-019-0184-5.
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Risk of bias assessments for selective reporting were inadequate in the majority of Cochrane reviews.大多数 Cochrane 综述的选择性报告风险评估不充分。
J Clin Epidemiol. 2019 Aug;112:53-58. doi: 10.1016/j.jclinepi.2019.04.007. Epub 2019 Apr 19.
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Assessments of attrition bias in Cochrane systematic reviews are highly inconsistent and thus hindering trial comparability.对 Cochrane 系统评价中损耗偏倚的评估高度不一致,从而阻碍了试验之间的可比性。
BMC Med Res Methodol. 2019 Apr 5;19(1):76. doi: 10.1186/s12874-019-0717-9.

2016 年和 2022 年版减重手术后加速康复(ERABS)指南的差异:呼吁 FAIR 数据和创建全球减重护理与研究联盟。

Differences Between the 2016 and 2022 Editions of the Enhanced Recovery After Bariatric Surgery (ERABS) Guidelines: Call to Action of FAIR Data and the Creation of a Global Consortium of Bariatric Care and Research.

机构信息

Clinical Epidemiologist, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333 ZA, Leiden, The Netherlands.

Medical Research Institute, Alexandria University, Alexandria, Egypt.

出版信息

Obes Surg. 2022 Aug;32(8):2753-2763. doi: 10.1007/s11695-022-06132-7. Epub 2022 Jun 2.

DOI:10.1007/s11695-022-06132-7
PMID:35654929
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9162377/
Abstract

In 2016, the Enhanced Recovery After Bariatric Surgery guidelines (G16) was published, and in 2022, an update to it was released (G22). Grading of recommendations, assessment, development, and evaluations (GRADE), emphasizing the level of evidence (LoE) of both the guidelines, was performed. An overview of methodology was also performed, considering the following questions: how can research be improved, what can be done in the future using data, and how to collaborate more? Both guidelines did not explain how the LoE conclusions were derived regarding the risk of bias. There is also potential for forming a global consortium that deals with bariatric research, which can serve as a repository for all relevant data. Ensuring that this data is FAIR (findability, accessibility, interoperability, reusability) compliant and using this data to formulate future guidelines will benefit clinicians and patients alike.

摘要

2016 年,发布了减重手术后加速康复指南(G16),2022 年,对其进行了更新(G22)。对推荐分级的评估、制定与评价(GRADE)进行了分级,强调了指南的证据水平(LoE)。还对方法进行了概述,考虑了以下问题:如何改进研究,未来可以使用数据做什么,以及如何更好地合作?这两个指南都没有解释如何得出关于偏倚风险的 LoE 结论。也有可能形成一个处理减重研究的全球联盟,该联盟可以作为所有相关数据的存储库。确保这些数据符合 FAIR(可发现性、可访问性、互操作性、可重用性)标准,并使用这些数据来制定未来的指南,将使临床医生和患者都受益。