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Record W2105895350 · doi:10.1186/1471-2431-14-158

Systematic review of outcome measures in trials of pediatric anaphylaxis treatment

2014· review· en· W2105895350 on OpenAlexafffund
Tamar N. Rubin, J K Clayton, Denise Adams, Hsing Jou, Sunita Vohra

Bibliographic record

VenueBMC Pediatrics · 2014
Typereview
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsMedicineAnaphylaxisMEDLINEIntensive care medicinePediatricsAllergyImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Considerable heterogeneity has been observed in the selection and reporting of disease-specific pediatric outcome measures in randomized controlled trials (RCTs). This makes interpretation of results and comparison across trials challenging. Outcome measures in pediatric anaphylaxis trials have never previously been systematically assessed. This systematic review (SR) identified and assessed outcome measures used in RCTs of anaphylaxis treatment in children. As a secondary objective, this SR assessed the evidence for current treatment modalities for anaphylaxis in the pediatric population. METHODS: We searched MEDLINE, EMBASE, The Cochrane Library, Cochrane Central Register of Controlled Trials (CENTRAL), and CINAHL from 2001 until December 2012. We also searched websites listing ongoing trials. We included randomized and controlled trials of anaphylaxis treatment in patients 0-18 years of age. Two authors independently assessed articles for inclusion. RESULTS: No published studies fulfilled the inclusion criteria. CONCLUSIONS: There is an alarming absence of RCTs evaluating the treatments for anaphylaxis in children. High quality studies are needed and are possible to design, despite the severe and acute nature of this condition. Consensus about the selection and validation of appropriate outcome measures will enhance the quality of research and improve the care of children with anaphylaxis. TRIAL REGISTRATION: CRD42012002685.

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)0.009
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.156
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0160.004
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.209
GPT teacher head0.439
Teacher spread0.230 · 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.

Study designSystematic review
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

Citations7
Published2014
Admission routes2
Has abstractyes

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