MétaCan
Menu
Back to cohort
Record W3112309390 · doi:10.11124/jbies-20-00171

Hypersensitivity in patients receiving metal implants: a scoping review protocol

2020· review· en· W3112309390 on OpenAlexaff
Dzifa Dordunoo, Judith A. Anaman‐Torgbor, Catherine Smith, Ajijoon Shaik, Michelle Hass, Carol Gordon, Minjeong An, Martha L. Aviles-G, Miriam Weinzierl

Bibliographic record

VenueJBI Evidence Synthesis · 2020
Typereview
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsCamosun CollegeUniversity of the Fraser ValleyUniversity of Victoria
Fundersnot available
KeywordsMedicineSystematic reviewProtocol (science)Hypersensitivity reactionMEDLINEPathologyAlternative medicineImmunology

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this scoping review is to gather the available evidence on metal hypersensitivity to determine the extent of the problem and identify gaps in the evidence about screening practices. INTRODUCTION: Hypersensitivity to metal was first reported in 1966. Since this time, the use of metal in prosthetic devices has increased with an associated rise in reported hypersensitivity reaction to other metals. Symptoms of metal hypersensitivity can be subtle, and it is unclear whether clinicians are aware of or routinely ask patients about metal hypersensitivity when documenting allergies. This can lead to a delay in diagnosis, which puts patients at risk of poor outcomes. Hence, there is a need to map the available evidence on hypersensitivity reaction in people who receive metallic device implantation. INCLUSION CRITERIA: The review will consider studies that include patients who undergo procedures involving metal implantation. The concept to be explored is hypersensitivity following a procedure that involves the implementation of a device with metal components. Implementation is defined as permanent integration of a foreign (non-biological) object into the human body to restore function. METHODS: The proposed scoping review will be conducted in accordance with JBI methodology for scoping reviews. Searches will be generated in multiple databases and updated as needed. Gray literature and organizational websites will also be searched. Titles, abstracts, and full articles will be screened according to the inclusion criteria. Studies published in English from 1960 to the present will be included. Data will be extracted and findings will be presented in tabular form with a narrative summary.

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)0.077
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.077
Threshold uncertainty score0.407

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0770.055
Meta-epidemiology (narrow)0.0050.004
Meta-epidemiology (broad)0.0140.013
Bibliometrics0.0170.011
Science and technology studies0.0050.004
Scholarly communication0.0080.009
Open science0.0060.007
Research integrity0.0100.005
Insufficient payload (model declined to judge)0.0500.011

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 head0.042
GPT teacher head0.376
Teacher spread0.334 · 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 designNot applicable
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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJBI Evidence SynthesisSame topicContact Dermatitis and AllergiesFrench-language works237,207