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Record W2734976743 · doi:10.1213/ane.0000000000002272

Comparison of Registered and Reported Outcomes in Randomized Clinical Trials Published in Anesthesiology Journals

2017· article· en· W2734976743 on OpenAlexaffabout
Philip M. Jones, Jeffrey Chow, Miguel Arango, Jason A. Fridfinnson, Nan Gai, Kevin Lam, Timothy P. Turkstra

Bibliographic record

VenueAnesthesia & Analgesia · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineAnesthesiologyRandomized controlled trialTrial registrationClinical trialMEDLINEProtocol (science)Alternative medicineAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Randomized clinical trials (RCTs) provide high-quality evidence for clinical decision-making. Trial registration is one of the many tools used to improve the reporting of RCTs by reducing publication bias and selective outcome reporting bias. The purpose of our study is to examine whether RCTs published in the top 6 general anesthesiology journals were adequately registered and whether the reported primary and secondary outcomes corresponded to the originally registered outcomes. METHODS: Following a prespecified protocol, an electronic database was used to systematically screen and extract data from RCTs published in the top 6 general anesthesiology journals by impact factor (Anaesthesia, Anesthesia & Analgesia, Anesthesiology, British Journal of Anaesthesia, Canadian Journal of Anesthesia, and European Journal of Anaesthesiology) during the years 2007, 2010, 2013, and 2015. A manual search of each journal's Table of Contents was performed (in duplicate) to identify eligible RCTs. An adequately registered trial was defined as being registered in a publicly available trials registry before the first patient being enrolled with an unambiguously defined primary outcome. For adequately registered trials, the outcomes registered in the trial registry were compared with the outcomes reported in the article, with outcome discrepancies documented and analyzed by the type of discrepancy. RESULTS: During the 4 years studied, there were 860 RCTs identified, with 102 RCTs determined to be adequately registered (12%). The proportion of adequately registered trials increased over time, with 38% of RCTs being adequately registered in 2015. The most common reason in 2015 for inadequate registration was registering the RCT after the first patient had already been enrolled. Among adequately registered trials, 92% had at least 1 primary or secondary outcome discrepancy. In 2015, 42% of RCTs had at least 1 primary outcome discrepancy, while 90% of RCTs had at least 1 secondary outcome discrepancy. CONCLUSIONS: Despite trial registration being an accepted best practice, RCTs published in anesthesiology journals have a high rate of inadequate registration. While mandating trial registration has increased the proportion of adequately registered trials over time, there is still an unacceptably high proportion of inadequately registered RCTs. Among adequately registered trials, there are high rates of discrepancies between registered and reported outcomes, suggesting a need to compare a published RCT with its trial registry entry to be able to fully assess the quality of the study. If clinicians base their decisions on evidence distorted by primary outcome switching, patient care could be negatively affected.

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)0.639
metaresearch head score (Gemma)0.478
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.6390.478
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0260.004
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0030.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.852
GPT teacher head0.644
Teacher spread0.208 · 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
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

Citations65
Published2017
Admission routes2
Has abstractyes

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