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Record W2769450134 · doi:10.2196/resprot.8343

Surgical Interventions for the Treatment of Supracondylar Humerus Fractures in Children: Protocol of a Systematic Review

2017· review· en· W2769450134 on OpenAlexvenueno aff
Oreste Lemos Carrazzone, Fábio Teruo Matsunaga, Nacime Salomão Barbachan Mansur, Marcelo Hide Matsumoto, Flávio Faloppa, Marcel Jun Sugawara Tamaoki

Bibliographic record

VenueJMIR Research Protocols · 2017
Typereview
Languageen
FieldMedicine
TopicElbow and Forearm Trauma Treatment
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsHumerusMedicineProtocol (science)Psychological interventionPhysical therapySurgeryAlternative medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: The treatment of supracondylar humerus fracture in children (SHFC) is associated with complications such as functional deficit, residual deformity, and iatrogenic neurological damage. The standard treatment is closed reduction and percutaneous Kirschner wire fixation with different configurations. Despite this fact, there is still no consensus on the most effective technique for the treatment of these fractures. OBJECTIVE: The aim of this systematic review will be to evaluate the effect of surgical interventions on the treatment of Gartland type II and III SHFC by assessing function, complications, and error as primary outcomes. Clinical outcomes such as range of motion and pain and radiographic outcomes will also be judged. METHODS: A systematic review of randomized controlled trials or quasi-randomized controlled trials evaluating the surgical treatment of SHFC will be carried out in the Cochrane Central Register of Controlled Trials, PubMed, Literatura Latino-Americana e do Caribe em Ciências da Saúde, and Excerpta Medica Database. The search will also occur at ongoing and recently completed clinical trials in selected databases. Data management and extraction will be performed using a data withdrawal form and by analyzing the following: study method characteristics, participant characteristics, intervention characteristics, results, methodological domains, and risk of bias. To assess the risk of bias of the included trials, the Cochrane Risk of Bias Tool will be used. Dichotomous outcome data will be analyzed as risk ratios, and continuous outcome data will be expressed as mean differences, both with 95% confidence intervals. Also, whenever possible, subgroup analysis, sensitivity analysis, and assessment of heterogeneity will be performed. RESULTS: Following the publication of this protocol, searches will be run and included studies will be deeply analyzed. We hope to obtain final results in the next few months and have the final paper published by the end of 2018. This study was funded by a government-based noncommercial agency, Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP). CONCLUSIONS: This study may provide surgical treatment effects evidence for SHFC. The results will assist clinical practice by demonstrating the effectiveness and potential complications of these interventions and might serve as a reference for future clinical trials on the topic. TRIAL REGISTRATION: PROSPERO CRD42014009304; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=9304 (Archived by WebCite at http://www.webcitation.org/6usiDHzD7).

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)0.060
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.060
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.057
Meta-epidemiology (narrow)0.0050.004
Meta-epidemiology (broad)0.0160.017
Bibliometrics0.0120.010
Science and technology studies0.0040.004
Scholarly communication0.0070.006
Open science0.0050.005
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0420.005

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 head0.675
GPT teacher head0.701
Teacher spread0.027 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations9
Published2017
Admission routes1
Has abstractyes

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