MétaCan
Menu
Back to cohort
Record W4396722203 · doi:10.1136/bmjopen-2023-081118

Sex and gender-based analysis and diversity metric reporting in acute care trials published in high-impact journals: a systematic review

2024· review· en· W4396722203 on OpenAlexafffund
David Granton, Myanca Rodrigues, Valeria Raparelli, Kimia Honarmand, Arnav Agarwal, Jan O. Friedrich, Benedetta Perna, Riccardo Spaggiari, Valeria Fortunato, Gianluca Risdonne, Michelle E. Kho, Sandra VanderKaay, Dipayan Chaudhuri, Carolina Gomez-Builes, Frédérick D’Aragon, Daniel Wiseman, Vincent Lau, Celina Lin, Julie C. Reid, Vatsal Trivedi, Varuna Prakash, Emilie P. Belley‐Côté, Maha Al Mandhari, Lehana Thabane, Louise Pilote, Karen E. A. Burns

Bibliographic record

VenueBMJ Open · 2024
Typereview
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsUniversity of AlbertaMcGill University Health CentreCentre Hospitalier Universitaire de SherbrookeMcMaster UniversityUniversité de SherbrookeSt. Joseph’s Healthcare HamiltonMcGill UniversityImpactUniversity of Toronto
FundersUniversity of TorontoOntario Ministry of Health and Long-Term CareMcMaster UniversityHeart and Stroke Foundation of CanadaCanadian Institutes of Health ResearchAmerican Thoracic Society
KeywordsMedicineMetric (unit)Diversity (politics)MEDLINEGender diversityAlternative medicineFamily medicinePathologyLaw

Abstract

fetched live from OpenAlex

OBJECTIVE: To characterise sex and gender-based analysis (SGBA) and diversity metric reporting, representation of female/women participants in acute care trials and temporal changes in reporting before and after publication of the 2016 Sex and Gender Equity in Research guideline. DESIGN: Systematic review. DATA SOURCES: We searched MEDLINE for trials published in five leading medical journals in 2014, 2018 and 2020. STUDY SELECTION: Trials that enrolled acutely ill adults, compared two or more interventions and reported at least one clinical outcome. DATA ABSTRACTION AND SYNTHESIS: 4 reviewers screened citations and 22 reviewers abstracted data, in duplicate. We compared reporting differences between intensive care unit (ICU) and cardiology trials. RESULTS: We included 88 trials (75 (85.2%) ICU and 13 (14.8%) cardiology) (n=111 428; 38 140 (34.2%) females/women). Of 23 (26.1%) trials that reported an SGBA, most used a forest plot (22 (95.7%)), were prespecified (21 (91.3%)) and reported a sex-by-intervention interaction with a significance test (19 (82.6%)). Discordant sex and gender terminology were found between headings and subheadings within baseline characteristics tables (17/32 (53.1%)) and between baseline characteristics tables and SGBA (4/23 (17.4%)). Only 25 acute care trials (28.4%) reported race or ethnicity. Participants were predominantly white (78.8%) and male/men (65.8%). No trial reported gendered-social factors. SGBA reporting and female/women representation did not improve temporally. Compared with ICU trials, cardiology trials reported significantly more SGBA (15/75 (20%) vs 8/13 (61.5%) p=0.005). CONCLUSIONS: Acute care trials in leading medical journals infrequently included SGBA, female/women and non-white trial participants, reported race or ethnicity and never reported gender-related factors. Substantial opportunity exists to improve SGBA and diversity metric reporting and recruitment of female/women participants in acute care trials. PROSPERO REGISTRATION NUMBER: CRD42022282565.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.216
metaresearch head score (Gemma)0.600
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.967

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2160.600
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0140.015
Bibliometrics0.0260.026
Science and technology studies0.0020.004
Scholarly communication0.0100.011
Open science0.0040.005
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.555
GPT teacher head0.591
Teacher spread0.036 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designSystematic review
DomainReporting
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

Citations21
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueBMJ OpenSame topicSex and Gender in HealthcareFrench-language works237,207