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Record W2969990414 · doi:10.1016/j.conctc.2019.100426

The crossover design for studies of infertility employing in-vitro fertilization: A methodological survey

2019· review· en· W2969990414 on OpenAlex
Dalton Budhram, Daniel Shi, Sarah D. McDonald, Stephen D. Walter

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueContemporary Clinical Trials Communications · 2019
Typereview
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsSample size determinationPsychological interventionRigourInfertilityCrossover studyCrossoverMedicineIn vitro fertilisationMEDLINEReproductive medicineResearch designPregnancyRandomized controlled trialObservational studyClinical study designLive birthClinical trialComputer scienceAlternative medicineStatisticsBiologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Infertility has become increasingly common worldwide. There is a need for the infertility literature to evaluate new interventions with IVF. The crossover design presents many methodological advantages for IVF trials. In addition to providing a within-person comparison of outcomes, it offers participants the opportunity to potentially benefit from more than one available treatment. However, infertility studies present a unique challenge in terms of bias: successful participants do not cross over to the second treatment group. OBJECTIVES: The main objective of our study was to survey the methodological features of crossover trials for infertility with in-vitro fertilization (IVF) based interventions. A secondary focus was reporting key results. STUDY DESIGN & SETTING: We conducted a methodological survey by systematically searching Medline and Embase databases. The capture-recapture technique was used to estimate the number of relevant studies that were not retrieved by our search strategy. We employed the Cochrane risk of bias tool to assess methodological rigour. Crossover-specific methods features were summarized. Treatment effects for pregnancy outcomes across studies are also presented. RESULTS: 15 studies met inclusion criteria. Most studies were deemed to have high or unclear risks of bias, usually because of incomplete reporting of outcome data and assessment procedures. 13 studies did not employ crossover-specific methods to analyze outcome data by period, which may bias treatment effect estimates. Four studies reported pregnancy outcome data with sample sizes from both treatment periods. Of these four studies, three reported that the control intervention was favoured. CONCLUSIONS: The main limitation of our survey was the small sample size of studies. Future reviews should be larger and seek to encompass a broader range of the infertility literature. Despite the issues identified in the included trials, consideration should still be given to using the crossover design in future infertility research. Employing crossover-specific analysis methods, such as accounting for participant non-completion, along with strict adherence to CONSORT reporting guidelines, may significantly reduce the risk of bias in individual studies.

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.

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)0.114
metaresearch head score (Gemma)0.526
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1140.526
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.985
GPT teacher head0.741
Teacher spread0.244 · 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