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Record W2046119426 · doi:10.1111/papr.12282

Low Pain Catastrophization and Disability Predict Successful Outcome to Radiofrequency Neurotomy in Individuals with Chronic Whiplash

2015· article· en· W2046119426 on OpenAlexaff
Ashley Smith, Gwendolen Jull, G. Schneider, Bevan Frizzell, R. Allen Hooper, Michele Sterling

Bibliographic record

VenuePain Practice · 2015
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineWhiplashPain catastrophizingPhysical therapyLogistic regressionNeurotomyChronic painProspective cohort studyPhysical medicine and rehabilitationInternal medicineSurgeryPoison control

Abstract

fetched live from OpenAlex

OBJECTIVES: Physical and psychological symptoms of individuals with chronic whiplash-associated disorders (WAD) are modulated by successful treatment with cervical radiofrequency neurotomy (cRFN). However, not all individuals respond to cRFN, and it is unknown which clinical features predict successful response to cRFN. METHODS: This prospective cohort study investigated 53 individuals with chronic WAD (36 female, 17 male; mean age = 44.7 ± 10.9 (SD) years) who underwent cRFN. Predictor variables measured at baseline (prior to RFN) included self-reported pain (VAS), disability (NDI), post-traumatic stress symptoms (PDS), pain catastrophizing (PCS), and measures of sensory hypersensitivity (pressure and cold pain thresholds). The outcome measure was perceived Global Rating of Change (where scores ≥ 4 were classified as a successful response) 3 months post-cRFN. RESULTS: Univariate logistic regression demonstrated that lower levels of disability and pain catastrophizing were associated with successful response of cRFN (both P < 0.05). Multivariable logistic regression demonstrated that low levels of pain catastrophizing and disability remained significant predictors of a successful response to cRFN (both P < 0.05). CONCLUSIONS: Low levels of pain catastrophizing and disability independently predicted a successful response to cRFN in patients with chronic WAD.

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)0.004
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.319
Teacher spread0.294 · 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.

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

Citations16
Published2015
Admission routes1
Has abstractyes

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