Background: While the PRISMA 2020 statement is intended to guide the reporting of original systematic reviews, updated systematic reviews, and living systematic reviews (LSRs), its explanation and elaboration document notes that additional considerations for updated systematic reviews and LSRs may need to be addressed. This paper reports the protocol for developing an extension of the PRISMA 2020 statement for LSRs. Methods: We will follow the EQUATOR Network\'s guidance for developing health research reporting guidelines. We will review the literature to identify possible items of the PRISMA 2020 checklist that need modification, as well as new items that need to be added. Then, we will survey representatives of different stakeholder groups for their views on the proposed modifications of the PRISMA 2020 checklist. We will summarize, present, and discuss the results of the survey in an online meeting, aiming to reach consensus on the content of the LSR extension. We will then draft the checklist, explanation and elaboration for each item, and flow diagram for the PRISMA 2020 extension. Then, we will share these initial documents with stakeholder representatives for final feedback and approval. Discussion: We anticipate that the PRISMA 2020 extension for LSRs will benefit LSR authors, editors, and peer reviewers of LSRs, as well as different users of LSRs, including guideline developers, policy makers, healthcare providers, patients, and other stakeholders.

The living systematic review (LSR) approach is based on ongoing surveillance of the literature and continual updating. Most currently available guidance documents address the conduct, reporting, publishing, and appraisal of systematic reviews (SRs), but are not suitable for LSRs per se and miss additional LSR-specific considerations. In this scoping review, we aim to systematically collate methodological guidance literature on how to conduct, report, publish, and appraise the quality of LSRs and identify current gaps in guidance.
A standard scoping review methodology was used. We searched MEDLINE (Ovid), EMBASE (Ovid), and The Cochrane Library on August 28, 2021. As for searching gray literature, we looked for existing guidelines and handbooks on LSRs from organizations that conduct evidence syntheses. The screening was conducted by two authors independently in Rayyan, and data extraction was done in duplicate using a pilot-tested data extraction form in Excel. Data was extracted according to four pre-defined categories for (i) conducting, (ii) reporting, (iii) publishing, and (iv) appraising LSRs. We mapped the findings by visualizing overview tables created in Microsoft Word.
Of the 21 included papers, methodological guidance was found in 17 papers for conducting, in six papers for reporting, in 15 papers for publishing, and in two papers for appraising LSRs. Some of the identified key items for (i) conducting LSRs were identifying the rationale, screening tools, or re-revaluating inclusion criteria. Identified items of (ii) the original PRISMA checklist included reporting the registration and protocol, title, or synthesis methods. For (iii) publishing, there was guidance available on publication type and frequency or update trigger, and for (iv) appraising, guidance on the appropriate use of bias assessment or reporting funding of included studies was found. Our search revealed major evidence gaps, particularly for guidance on certain PRISMA items such as reporting results, discussion, support and funding, and availability of data and material of a LSR.
Important evidence gaps were identified for guidance on how to report in LSRs and appraise their quality. Our findings were applied to inform and prepare a PRISMA 2020 extension for LSR.

UNASSIGNED: Knowledge of current and ongoing studies is critical for identifying research gaps and enabling evidence-based decisions for individualized treatment. However, the increasing number of scientific publications poses challenges for healthcare providers and patients in all medical fields to stay updated with the latest evidence. To overcome these barriers, we aim to develop a living systematic review and open-access online evidence map of surgical therapy for bladder cancer (BC), including meta-analyses.
UNASSIGNED: Following the guidelines provided in the Cochrane Handbook for Systematic Reviews of Interventions and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement, a systematic literature search on uro-oncological therapy in BC will be performed across various literature databases. Within the scope of a meta-analysis and living systematic review, relevant randomized controlled trials will be identified. Data extraction and quantitative analysis will be conducted, along with a critical appraisal of the quality and risk of bias of each study. The available research evidence will be entered into an open-access framework (www.evidencemap.surgery) and will also be accessible via the EVIglance app. Regular semi-automatic updates will enable the implementation of a real-living review concept and facilitate resource-efficient screening.
UNASSIGNED: A regularly updated evidence map provides professionals and patients with an open-access knowledge base on the current state of research, allowing for decision-making based on recent evidence. It will help identify an oversupply of evidence, thus avoiding redundant work. Furthermore, by identifying research gaps, new hypotheses can be formulated more precisely, enabling planning, determination of sample size, and definition of endpoints for future trials.

To evaluate an approach using automation and crowdsourcing to identify and classify randomized controlled trials (RCTs) for rheumatoid arthritis (RA) in a living systematic review (LSR).
Records from a database search for RCTs in RA were screened first by machine learning and Cochrane Crowd to exclude non-RCTs, then by trainee reviewers using a Population, Intervention, Comparison, and Outcome (PICO) annotator platform to assess eligibility and classify the trial to the appropriate review. Disagreements were resolved by experts using a custom online tool. We evaluated the efficiency gains, sensitivity, accuracy, and interrater agreement (kappa scores) between reviewers.
From 42,452 records, machine learning and Cochrane Crowd excluded 28,777 (68%), trainee reviewers excluded 4,529 (11%), and experts excluded 7,200 (17%). The 1,946 records eligible for our LSR represented 220 RCTs and included 148/149 (99.3%) of known eligible trials from prior reviews. Although excluded from our LSRs, 6,420 records were classified as other RCTs in RA to inform future reviews. False negative rates among trainees were highest for the RCT domain (12%), although only 1.1% of these were for the primary record. Kappa scores for two reviewers ranged from moderate to substantial agreement (0.40-0.69).
A screening approach combining machine learning, crowdsourcing, and trainee participation substantially reduced the screening burden for expert reviewers and was highly sensitive.

Researchers performing high-quality systematic reviews search across multiple databases to identify relevant evidence. However, the same publication is often retrieved from several databases. Identifying and removing such duplicates (\"deduplication\") can be extremely time-consuming, but failure to remove these citations can lead to the wrongful inclusion of duplicate data. Many existing tools are not sensitive enough, lack interoperability with other tools, are not freely accessible, or are difficult to use without programming knowledge. Here, we report the performance of our Automated Systematic Search Deduplicator (ASySD), a novel tool to perform automated deduplication of systematic searches for biomedical reviews.
We evaluated ASySD\'s performance on 5 unseen biomedical systematic search datasets of various sizes (1845-79,880 citations). We compared the performance of ASySD with EndNote\'s automated deduplication option and with the Systematic Review Assistant Deduplication Module (SRA-DM).
ASySD identified more duplicates than either SRA-DM or EndNote, with a sensitivity in different datasets of 0.95 to 0.99. The false-positive rate was comparable to human performance, with a specificity of > 0.99. The tool took less than 1 h to identify and remove duplicates within each dataset.
For duplicate removal in biomedical systematic reviews, ASySD is a highly sensitive, reliable, and time-saving tool. It is open source and freely available online as both an R package and a user-friendly web application.

The objectives of this study are to describe the characteristics of living systematic reviews (LSRs) and to understand their life cycles.
We conducted a comprehensive search up to April 2021 then selected articles and abstracted data in duplicate and independently. We undertook descriptive analyses and calculated delay in version update and delay since the last published version.
We included 76 eligible LSRs with a total of 279 eligible versions. The majority of LSRs was from the clinical field (70%), was COVID-19 related (63%), and had a funding source specified (62%). The median number of versions per LSR was 2 (interquartile range (IQR) 1-4; range 1-19). The median and IQR for the ratio of the actual period of update to the planned period of update was 1.12 (0.81; 1.71). Out of all reviews with a \'planned period of update\' and at least one update (N = 19), eight LSRs (42%) had a period since last published version greater than 3 times the planned period of update. No LSR included a \'retirement notice\' in their latest published version.
While most LSR complied with the planned period of producing updates, a substantive proportion lagged since their last update.

The aim of this study is to describe and pilot a novel method for continuously identifying newly published trials relevant to a systematic review, enabled by combining artificial intelligence (AI) with human expertise.
We used RobotReviewer LIVE to keep a review of COVID-19 vaccination trials updated from February to August 2021. We compared the papers identified by the system with those found by the conventional manual process by the review team.
The manual update searches (last search date July 2021) retrieved 135 abstracts, of which 31 were included after screening (23% precision, 100% recall). By the same date, the automated system retrieved 56 abstracts, of which 31 were included after manual screening (55% precision, 100% recall). Key limitations of the system include that it is limited to searches of PubMed/MEDLINE, and considers only randomized controlled trial reports. We aim to address these limitations in future. The system is available as open-source software for further piloting and evaluation.
Our system identified all relevant studies, reduced manual screening work, and enabled rolling updates on publication of new primary research.

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This is a protocol for developing a guideline to establish the evidence ecosystem of acupuncture. It describes all steps that will be followed in line with the World Health Organization Handbook for Guideline Development and the Reporting Items for practice Guidelines in Healthcare (RIGHT). The key steps included guideline protocol development, guideline registration, systematic review of acupuncture evidence issues, systematic review of methods for establishing evidence ecosystem, survey of acupuncture stakeholders regarding potential acupuncture evidence issues, development of potential items for guidelines, Delphi method for guideline item development, consensus meeting, drafting guideline, peer review, approval, and publishing. This future guideline will help to establish evidence ecosystem of acupuncture, which will facilitate the application of acupuncture in clinical practice.

Background: The living systematic review (LSR) approach is based on an ongoing surveillance of the literature and continual updating. A few guidance documents address the conduct, reporting, publishing and appraisal of systematic reviews (SRs), but the methodology described is either not up-to date or not suitable for LSRs and misses additional LSR-specific considerations. The objective of this scoping review is to systematically collate methodological literature and guidance on how to conduct, report, publish and appraise the quality of LSRs. The scoping review will allow the mapping of the existing evidence on the topic to support LSRs authors seeking guidance and identify related gaps.  Methods: To achieve our objectives, we will conduct a scoping review to survey and evaluate existing evidence, using the standard scoping review methodology. We will search MEDLINE, EMBASE, and Cochrane using the OVID interface. The search strategy was developed by a researcher experienced in developing literature search strategies with the help of an information specialist. As for searching grey literature, we will seek existing guidelines and handbooks on LSRs from organizations that conduct evidence syntheses using the Lens.org website. Two review authors will extract and catalogue the study data on LSR methodological aspects into a standardized and pilot-tested data extraction form. The main categories will reflect proposed methods for (i) conducting LSRs, (ii) reporting of LSRs, (iii) publishing and (iv) appraising the quality of LSRs. Data synthesis and conclusion: By collecting these data from methodological surveys and papers, as well as existing guidance documents and handbooks on LSRs, we might identify specific issues and components lacking within current LSR methodology. Thus, the systematically obtained findings of the scoping review could be used as basis for the revision of existing methods tools on LSR, for instance a PRISMA statement extension for LSRs.