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Record W4392765994 · doi:10.1136/bmjopen-2023-079836

Management of long bone fractures and traumatic hip dislocations in paediatric patients: study protocol for a prospective global multicentre observational cohort registry

2024· article· en· W4392765994 on OpenAlexafffund
Bryn O Zomar, Maio Chen, Emily K. Schaeffer, Kishore Mulpuri, Alexander Joeris

Bibliographic record

VenueBMJ Open · 2024
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersI’m a HIPpy FoundationAO Foundation
KeywordsMedicineObservational studyInformed consentHumerusClinical trialPhysical therapySurgeryInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Management controversy and clinical equipoise exist in treatments of long bone fractures and traumatic hip dislocation in paediatric patients due to the lack of high-quality clinical evidence. This protocol describes the effort of a large prospective global multicentre cohort study (registry) aiming at providing quality data to assist evidence-based treatment decision-making. METHODS AND ANALYSIS: Eligible paediatric patients (N=750-1000) with open physes suffering from proximal humerus fractures, distal humerus fractures, proximal radius fractures, forearm shaft fractures, traumatic hip dislocations, femoral neck fractures or tibial shaft fractures will be recruited over a period of 24-36 months. Hospitalisation and treatment details (including materials and implants) will be captured in a cloud-based, searchable database. Outcome measures include radiographic assessments, clinical outcomes (such as range of motion, limb length discrepancies and implant removal), patient-reported outcomes (Patient Reported Outcomes Of Fracture, Patient-Reported Outcomes Measurement Information System (PROMIS) and EuroQol-5D (EQ-5D-Y)) and adverse events.Aside from descriptive statistics on patient demographics, baseline characteristics, types of fractures and adverse event rates, research questions will be formulated based on data availability and quality. A statistical analysis plan will be prepared before the statistical analysis. ETHICS AND DISSEMINATION: Ethics approval will be obtained before patients are enrolled at each participating site. Patient enrolment will follow an informed consent process approved by the responsible ethics committee. Peer-reviewed publication is planned to disseminate the study results. TRIAL REGISTRATION NUMBER: NCT04207892.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.237
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.064
GPT teacher head0.443
Teacher spread0.379 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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

Citations1
Published2024
Admission routes2
Has abstractyes

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