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Record W7075591092

Enrollment challenges in multicenter, international studies: The example of the GAS trial

2019· article· en· W7075591092 on OpenAlexaboutno aff

Bibliographic record

VenueEUR Research Repository (Erasmus University Rotterdam) · 2019
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsContraindicationDescriptive statisticsRandomized controlled trialClinical trialInformed consentInclusion and exclusion criteria
DOInot available

Abstract

fetched live from OpenAlex

Introduction Randomized trials are important for generating high‐quality evidence, but are perceived as difficult to perform in the pediatric population. Thus far there has been poor characterization of the barriers to conducting trials involving children, and the variation in these barriers between countries remains undescribed. The General Anesthesia compared to Spinal anesthesia (GAS) trial, conducted in seven countries between 2007 and 2013, provides an opportunity to explore these issues. Methods We undertook a descriptive analysis to evaluate the reasons for variation in enrollment between countries in the GAS trial, looking specifically at the number of potential subjects screened, and the subsequent application of four exclusion criteria that were applied in a hierarchical order. Results A total of 4023 patients were screened by 28 centers in seven countries. Australia and the USA screened the most subjects, accounting for 84% of all potential trial participants. The percentage of subjects eliminated from the screened pool by each exclusion criterion varied between countries. Exclusion due to a predefined condition (H1) eliminated only 5% of potential subjects in Italy and the UK, but 37% in Canada. Exclusions due to a contraindication or a physician's refusal most impacted enrollment in Australia and the USA. The patient being “too large for spinal anesthesia” was the most commonly cited by anesthetists who refused to enroll a patient (64% of anesthetist refusals). The majority of surgeon refusals came from the USA, where surgeons preferred the patient to receive a general anesthetic. The percentage of approached parents refusing to consent ranged from a low of 3% in Italy to a high of 70% in the USA and Netherlands. The most frequently cited reason for parent refusal in all countries was a preference for general anesthesia (median: 43%, range: 32%‐67%). However, a sizeable proportion of parents in all countries had a contrasting preference for spinal anesthesia (median: 25%, range: 13%‐31%), and 23% of U.S. parents expressed concern about randomization. Conclusion The GAS trial highlights enrollment challenges that can occur when conducting multicenter, international, pediatric studies. Investigators planning future trials should be aware of potential differences in screening processes across countries, and that exclusions by anesthetists and surgeons may vary in reason, in frequency, and by country. Furthermore, investigators should be aware that the U.S. centers encountered particularly high surgeon and parental refusal rates and that U.S. parents were uniquely concerned about randomization. Planning trials that address these difficulties should increase the likelihood of successfully recruiting subjects in pediatric trials.

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)0.616
metaresearch head score (Gemma)0.676
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.616
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.6160.676
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.007
Science and technology studies0.0040.012
Scholarly communication0.0100.010
Open science0.0040.009
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0050.001

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 head0.153
GPT teacher head0.351
Teacher spread0.197 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations3
Published2019
Admission routes1
Has abstractyes

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