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Record W4410479497 · doi:10.1186/s40814-025-01655-z

Design, analysis, and reporting of pilot and feasibility trials in anesthesiology: a methodological study

2025· review· en· W4410479497 on OpenAlexaff
Tariq Atkin-Jones, Mohamed Ali, A. C. Onuorah, Ezinne Ifeanacho, Azin Khosravirad, Kim Madden, Behnam Sadeghirad, Lawrence Mbuagbaw

Bibliographic record

VenuePilot and Feasibility Studies · 2025
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsSt. Joseph’s Healthcare HamiltonImpactMcMaster University
Fundersnot available
KeywordsAnesthesiologyResearch designMedical educationPsychologyMedicineSociologySocial sciencePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Pilot and feasibility studies are effective tools for assessing the feasibility of performing larger-scale studies. These are particularly useful in anesthesiology, where the research overlaps with several other medical and surgical fields. The objective of this meta-epidemiological study is to assess the design and methodology of pilot and feasibility randomized controlled trials (RCTs) in anesthesiology. METHODS: We searched for pilot and feasibility RCTs in anesthesiology indexed in PubMed during a 5-year span between January 1, 2018, and December 31, 2022. We extracted bibliographic information, field of study, type of intervention, trial duration, trial design, use of qualitative data, use of progression criteria, whether the primary objective and primary outcome were related to feasibility, reported feasibility outcomes, and sample size justification. We conducted logistic regression to determine the factors associated with using progression criteria, having primary feasibility outcomes, and using feasibility outcomes to justify the sample size. We controlled for publication year, journal impact factor, source of funding, intervention type, and region. RESULTS: Our search retrieved 3015 trials, of which 248 were ultimately included and analyzed. Less than a third of studies stated feasibility as the primary objective (n = 77, 31.0%). Feasibility was a primary outcome in 46 (18.6%) studies, progression criteria were used in 27 (10.9%) studies, a sample size justification was listed in 134 (54.0%) studies, and 24 (9.7%) studies used qualitative data. We did not find any statistically significant association between progression criteria and any of the selected variables. Recently published trials had higher odds of having primary feasibility outcomes (odds ratio [OR] 1.39; 95% CI 1.06-1.83). Studies of pharmacological interventions had lower odds primary feasibility outcomes (OR 0.41; 95% CI 0.19-0.90). Recent studies also had higher odds of having a sample size justification based on a feasibility outcome rather than a clinical outcome or similar studies (OR 1.51; 95% CI 1.06-2.15). CONCLUSIONS: More recently published pilot RCTs were significantly associated with having a primary feasibility outcome and determining sample size based on feasibility, while pharmacological studies were significantly associated with less reporting of primary feasibility outcomes. Future research addressing the factors limiting adherence to current guidelines is warranted.

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)0.669
metaresearch head score (Gemma)0.687
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: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.298
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.6690.687
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0580.003
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.987
GPT teacher head0.714
Teacher spread0.273 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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