MétaCan
Menu
Back to cohort
Record W2134920435 · doi:10.1016/j.jmpt.2012.12.011

Chiropractic Management of Benign Paroxysmal Positional Vertigo Using the Epley Maneuver: A Case Series

2013· article· en· W2134920435 on OpenAlexaff
Sandy Sajko, Kent Stuber, Timothy N. Welsh

Bibliographic record

VenueJournal of Manipulative and Physiological Therapeutics · 2013
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsUniversity of TorontoCanadian Memorial Chiropractic CollegeCanadian Chiropractic Association
Fundersnot available
KeywordsMedicineChiropracticBenign paroxysmal positional vertigoVertigoPhysical therapyPhysical medicine and rehabilitationSurgeryAlternative medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this case series is to describe the management of benign paroxysmal positional vertigo in a chiropractic clinical setting. CLINICAL FEATURES: Eight patients (4 women, 4 men) with symptoms of persistent benign paroxysmal positional vertigo presented for chiropractic care. The outcome measures included self-reported resolution of vertigo, a Short Form 12 Health Survey, Measure Yourself Medical Outcome Profile, and the Dix-Hallpike maneuver. Outcome measures were assessed at initial assessment, 6 days, 30 days, and 3 months postintervention. INTERVENTION AND OUTCOME: The patients underwent one or more canalith repositioning procedures (Epley maneuver). Scores in each of the categories decreased from the initial to 6-day assessment and then again at the 30-day assessment. The effects of the treatment on the Short Form 12 scores showed changes between the initial assessment and 30 days posttreatment. CONCLUSION: The patients in this case series demonstrated reduction in symptoms with chiropractic management.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.342
GPT teacher head0.356
Teacher spread0.014 · 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 designCase report
Domainnot available
GenreEmpirical

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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Manipulative and Physiological TherapeuticsSame topicVestibular and auditory disordersFrench-language works237,207