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Record W1648378275 · doi:10.3233/bmr-140538

Mid-term follow-up of whiplash with Bournemouth Questionnaire: The significance of the initial depression to pain ratio

2015· article· en· W1648378275 on OpenAlexaboutno aff
Rebecca Griggs, Jonathan Cook, Martin Gargan, G.C. Bannister, Rouin Amirfeyz

Bibliographic record

VenueJournal of Back and Musculoskeletal Rehabilitation · 2015
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsWhiplashDepression (economics)MedicineTerm (time)Physical therapyPhysical medicine and rehabilitationPoison controlMedical emergencyPhysicsEconomics

Abstract

fetched live from OpenAlex

INTRODUCTION: The Bournemouth Questionnaire (BQ) was used to report the short to mid-term outcome of a prospective cohort of patients who had sustained Whiplash Associated Disorder (WAD), and establish whether outcome could be predicted on initial assessment. METHODS: One hundred patients with WAD grades I-III on the Quebec Task Force Classification were referred for physiotherapy (neck posture advice, initially practised under the direct supervision of a therapist). BQ scores were recorded on the first visit, at six weeks, then at final follow-up. RESULTS: Seventy-six percent of patients were available at final follow-up, 58% women. The mean age was 43.2 years old and follow-up time 38 months (28-48). Symptoms plateaued after six weeks in the majority and improved gradually thereafter. When the individual BQ components on initial presentation were reassessed, patients who score disproportionately highly in BQ Question 5 (Depression) had a worse outcome. To quantify this, the ratio of BQ Questions 5 (Depression)/1 (Pain) was calculated. BQ5/1 ratio greater than 1 on initial presentation had an odds ratio of 2 for poor outcome (p= 0.02). CONCLUSION: The BQ can therefore be used to identify patients with a disproportionately high depression score (BQ5) who are highly likely to clinically deteriorate in the medium term.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.357
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
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)0.0000.000

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 head0.014
GPT teacher head0.291
Teacher spread0.278 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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