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Record W4386307777 · doi:10.1002/mdc3.13874

Therapeutic Benefit of Sensory Trick in Cervical Dystonia

2023· article· en· W4386307777 on OpenAlexaboutno aff
Abhimanyu Mahajan, David Andrés González, Glenn T. Stebbins, Cynthia Comella

Bibliographic record

VenueMovement Disorders Clinical Practice · 2023
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCervical dystoniaSpasmodic TorticollisBotulinum toxinDystoniaRating scaleMedicineMultivariate analysisInternal medicinePsychologyPhysical therapyPhysical medicine and rehabilitationAnesthesiaPsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Background Sensory tricks (STs) are voluntary maneuvers that dampen the abnormal movement in cervical dystonia (CD). Objectives To investigate the effect of ST on CD severity and treatment. Methods Data on 1039 individuals with a modified Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) score were extracted from the CD Patient Registry for Observation of OnabotulinumtoxinA (onabotA) Efficacy study. Univariate and multivariate models evaluated the direct and indirect impact of ST on CD severity and treatment, while controlling for confounds. Results Complete ST was associated with a 10% lower mean onabotA dose. Absence of complete ST was associated with a higher onabotA dose after controlling for dystonia severity (OR = 1.37, P = 0.04). ST moderated the relationship between dystonia severity and toxin dose ( β = −0.16, P = 0.02). Conclusions ST is related to lower CD severity and toxin dose. It may have a direct effect on lowering toxin dose, independent of CD severity.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.063
GPT teacher head0.394
Teacher spread0.330 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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