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Record W2920876636 · doi:10.11124/jbisrir-d-19-00059

Interactive Summary of Findings tables: the way to present and understand results of systematic reviews

2019· review· en· W2920876636 on OpenAlexaffabout
Holger J. Schünemann, Nancy Santesso, Jan Brożek

Bibliographic record

VenueThe JBI Database of Systematic Reviews and Implementation Reports · 2019
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster UniversityImpactCochrane
Fundersnot available
KeywordsGrading (engineering)Systematic reviewStandardizationComputer scienceGuidelineInformation retrievalData scienceMEDLINEMedicineEngineering

Abstract

fetched live from OpenAlex

The JBI Database of Systematic Reviews and Implementation Reports continues to enhance its systematic reviews by including GRADE (Grading of Recommendations Assessment, Development and Evaluation) Summary of Findings (SoF) tables. Summary of Findings tables are concise, tabular summaries of the evidence that address a specific health-related question.1 They include information about the main outcomes, the type and number of studies, the relative and absolute estimates of the effect or association, important comments and a plain language summary to aid interpretation and a rating of the certainty of evidence (also known as quality of the evidence).1 Several randomized trials have shown that well designed SoF tables improve understanding and retrieval of information from a systematic review2-4 and they are a standard feature of Cochrane and are often used in other reviews.5-7 However, in the GRADE Working Group's DECIDE project (www.decide-collaboration.eu)8 and during guideline development work, it became apparent that a “flexible standardization” of presenting information in SoF tables is required to further enhance understanding and uptake of information. These observations led to the development of electronic interactive versions of SoF tables (iSoFs) that allow presenting the same underlying information in several formats that vary in content and graphical layout. These electronic versions are available on dedicated websites and, from this issue of the journal, are linked directly from the standard SoF and text of a Joanna Briggs Institute (JBI) systematic review. An example is available in Vincze et al.9 evaluating the use of nutrition for gestational and postpartum weight management in this issue of the journal. Low certainty evidence from 23 studies in 5230 patients compiled in the review suggests that nutritional interventions may reduce gestational weight gain, a continuous outcome described in this iSoF: https://bit.ly/2Ofg9Av, by 1.25 (95% confidence interval: 0.4 to 2.1) kg compared with other interventions. Authors of JBI systematic reviews will use the GRADE Working Group's official tool, GRADEpro (McMaster University/EvidencePrime, Inc., Hamilton, ON, Canada), to create these iSoF tables. The integrated GRADE Handbook provides guidance for how to create iSoFs, how to embed them in other documents, such as systematic reviews, Health Technology Assessment reports and healthcare guidelines where they can function as decision support tools and aids. Detailed guidance for how to produce SoF tables is also available in GRADE research articles that describe good practices and the process for creating accurate SoF tables for interventions and diagnostic test accuracy reviews.4,10-14 Examples of the use of iSoFs include recent European Commission Breast Cancer guidelines and American Society of Hematology guidelines where recommendations are supported by an iSoF.15-18 We are delighted that the JBI has taken this innovative step to include iSoF tables in their reviews. These steps will make for better evidence integration in decision tools and sharing globally.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.273
metaresearch head score (Gemma)0.051
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.362
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2730.051
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0290.003
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.697
GPT teacher head0.559
Teacher spread0.138 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2019
Admission routes2
Has abstractyes

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