The surgical case report（SCARE）statement is the report checklist made by European researchers in 2016, which is specialized for surgical case report. As a reference for enhancing the research quality and transparency, the SCARE statement provides a fundamental framework for surgical case reports. The last SCARE statement was revised in 2020, and this paper interprets it to provide a practical tool for domestic researchers in surgical case report.
With the increasing availability of clinical and biomedical big data, machine learning is being widely used in scientific research and academic papers. It integrates various types of information to predict individual health outcomes. However, deficiencies in reporting key information have gradually emerged. These include issues like data bias, model fairness across different groups, and problems with data quality and applicability. Maintaining predictive accuracy and interpretability in real-world clinical settings is also a challenge. This increases the complexity of safely and effectively applying predictive models to clinical practice. To address these problems, TRIPOD+AI (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis+artificial intelligence) introduces a reporting standard for machine learning models. It is based on TRIPOD and aims to improve transparency, reproducibility, and health equity. These improvements enhance the quality of machine learning model applications. Currently, research on prediction models based on machine learning is rapidly increasing. To help domestic readers better understand and apply TRIPOD+AI, we provide examples and interpretations. We hope this will support researchers in improving the quality of their reports.
To standardize and improve the quality of reporting of patient and public involvement in health and social care research, BMJ recently published the 2nd edition of Guidance for Reporting Involvement of Patients and the Public (GRIPP 2). This paper introduces the background and process of GRIPP 2 development, and explains the core content of GRIPP 2. It is expected that GRIPP 2 will provide reference for domestic researchers carrying out patients and public involvement (PPI) research and writing PPI research report.
Structured template and reporting tool for real world evidence (STaRT-RWE) was developed by a team led by professor Shirley V Wang of Brigham and Women's Hospital, Harvard Medical School, which is to plan and report on the implementation of real world evidence (RWE) studies on the safety and efficacy of treatments. The template, published in the journal BMJ in January 2021, has been endorsed by the International Society of PharmacoEpidemiology and the Transparency Initiative promoted by the International Society of Pharmacoeconomics and Outcome Research. This article interprets its entries to promote the understanding and application of STaRT-RWE by domestic scholars engaged in real world study, and help to improve the transparency, repeatability, and accuracy of RWE research.
An intervention with clinical application must be effective and safe, therefore, when evaluating interventions, the benefit-harm ratio should be considered, and only those interventions with more benefits than harms have application value. To evaluate the benefits and harms of an intervention evidence of both benefits and harms should be reported in clinical trials. To promote better reporting of harms in randomized controlled trials, the CONSORT group had added an entry on harms in the 2001 version of the CONSORT statement, and then in 2004, the CONSORT group developed the CONSORT Harms extension; however, it has not been consistently applied and needs to be updated, the reporting of harms is still inadequate. The CONSORT group has updated《Better reporting of harms in randomized trial: an extension of the CCONSORT statement.》, published《CONSORT Harms 2022 statement, explanation, and elaboration: updated guideline for the reporting of harms in randomized trials》. This article presents and explains the Harms 2022, with the aim of helping researchers better understand and use the statement, with a view to improving the reporting quality of harms in clinical trials.
The complete, transparent, and standardized reporting of the outcome of a clinical trial is a key factor in ensuring the practicality, reproducibility, and transparency of the trial, and reducing bias in selective reporting. The consolidated standards of reporting trials (CONSORT) 2010 statement provides normative guidelines for reporting clinical trials. In December 2022, JAMA released the guidelines for reporting outcomes in trial reports (CONSORT-Outcomes) 2022 extension, aiming to explain the entries related to trial outcomes, sample size, statistical methods, and auxiliary analysis in the CONSORT 2010 statement, to further improve the standards for outcome reporting in clinical trial reports. This article combines research examples to interpret the CONSORT-Outcomes 2022 extension, in order to provide normative references for domestic scholars to report clinical research results.
The PRISMA aims to enhance the transparency and reporting quality of systematic reviews. PRISMA 2020 is an update version of PRISMA 2009, which was published in BMJ in March, 2021. This article compared the PRISMA 2020 and PRISMA 2009, interpreted PRISMA 2020 with representative examples, aiming to help Chinese scholars better understand and apply this reporting guideline, thus to improve the reporting quality of systematic reviews.
Adherence to reporting guidelines contributes to report methodology and outcomes of research distinctly and transparently. There are some checklists with specific study types related to surgery on the EQUATOR Network’s website. However, the IDEAL framework focuses on stepwise evaluation of surgical innovation through all stages with some key elements, which those existing guidelines may not mention. This likely results in the inaccuracy in reporting in studies attempting to follow the IDEAL recommendations and suggests a pressing need for IDEAL reporting guidelines. Considering these limitations, the IDEAL developed the IDEAL reporting guidelines between October 2018 and May 2019. The paper aimed to provide interpretation of IDEAL reporting guideline, and promote its understanding and use among Chinese researchers.
Based on previous evidence-based researches and teaching experience, our team conducted literature and book review, and summarized 4 requirements, 1) effect measure calculation and conversion, 2) registration of evidence-based research, 3) evidence-based research database and 4) quality evaluation tools and reporting guidelines. We developed an online platform of evidence-based medicine research helper using the front-end and back-end technology, which can be accessed using www.ebm-helper.cn. Currently, the online tool has included 46 scenarios for effect measure calculation and conversion, introduction of 7 evidence-based research registration platforms, 26 commonly used databases for evidence-based research and 29 quality evaluation tools and reporting guidelines. This online tool can help researchers to solve specific problems encountered in different stages of evidence-based medicine research. Promoting the application of this platform in evidence-based medicine will help researchers to use the tool scientifically and improve research efficiency.