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Record W4386529731 · doi:10.1002/cre2.779

Effectiveness of intraoral splints in the treatment of migraine and tension‐type headache: A systematic review

2023· review· en· W4386529731 on OpenAlexaff
Olga Martínez‐Álvarez, E Wojtovicz, Jose Luís De la Hoz, Juan Mesa, Susan Armijo‐Olivo

Bibliographic record

VenueClinical and Experimental Dental Research · 2023
Typereview
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSplintsMedicineCochrane LibraryMEDLINEMigraineCINAHLRandomized controlled trialPhysical therapyData extractionDentistryClinical trialOrthodonticsSurgeryAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: The main objective of this systematic review was to assess the effectiveness of intraoral splints in treating migraine and tension-type headaches. MATERIAL AND METHODS: The article search was conducted within seven electronic databases (Medline, PubMed, Embase, CINAHL PLUS with full text, Cochrane Library Trials, Web of Science, and Scopus) with no date limits or language restrictions up to June 12, 2022. Strict inclusion and exclusion criteria were set for article selection. At the same time as data extraction, each study's risk of bias (RoB) was evaluated using the Cochrane tool to assess their RoB. Subsequently, the Cochrane Grading of Recommendations Assessment Development and Evaluation was used to evaluate the certainty of the evidence. RESULTS: Four controlled clinical trials were included. These trials were heterogeneous in terms of (1) diagnosis, (2) design of the intraoral splints, and (3) tools for reporting the results, which made it difficult to compile the data as well as evaluate its quality. Trials reported a reduction in the frequency of headache and pain intensity when using intraoral splints; however, this therapy was not superior to medications. CONCLUSIONS: The evidence is very low for the use of oral splints as a therapeutic alternative to medication in the treatment of migraine and/or tension-type headache.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.431
GPT teacher head0.609
Teacher spread0.178 · 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 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

Citations4
Published2023
Admission routes1
Has abstractyes

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