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Record W2048889383 · doi:10.1590/0004-282x20140044

The physical, social and emotional aspects are the most affected in the quality of life of the patients with cervical dystonia

2014· article· en· W2048889383 on OpenAlexaboutno aff
Roberta Weber Werle, Sibele Yoko Mattozo Takeda, Marise Bueno Zonta, Ana Tereza Bittencourt Guimarães, Hélio Afonso Ghizoni Teive

Bibliographic record

VenueArquivos de Neuro-Psiquiatria · 2014
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCervical dystoniaSpasmodic TorticollisQuality of life (healthcare)DystoniaPhysical therapyFeelingRating scaleBotulinum toxinPsychologyPhysical medicine and rehabilitationMedicinePsychiatryAnesthesiaPsychotherapistDevelopmental psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Describe the functional, clinical and quality of life (QoL) profiles in patients with cervical dystonia (CD) with residual effect or without effect of botulinum toxin (BTX), as well as verify the existence of correlation between the level of motor impairment, pain and QoL. METHOD: Seventy patients were assessed through the Craniocervical dystonia questionnaire-24 (CDQ-24) and the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS). RESULTS: The greater the disability, pain and severity of dystonia, the worse the QoL (p<0.0001). Greater severity relates to greater disability (p<0.0001). Pain was present in 84% of the sample, being source of disability in 41%. The most frequent complaints were: difficulty in keeping up with professional and personal demands (74.3%), feeling uneasy in public (72.9%), hindered by pain (68.6%), depressed, annoyed or bitter (47.1%), lonely or isolated (32.9%). CONCLUSION: The physical, social and emotional aspects are the most affected in the QoL of these patients.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.261
Teacher spread0.246 · 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 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

Citations48
Published2014
Admission routes1
Has abstractyes

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