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Record W2099706385 · doi:10.1080/165019701300006515

PHYSICAL MEASUREMENTS AND QUESTIONNAIRES AS DIAGNOSTIC TOOLS IN CHRONIC LOW BACK PAIN

2001· article· en· W2099706385 on OpenAlexaboutno aff
Pekka Rantanen

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2001
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsReceiver operating characteristicMedicinePhysical therapyIsometric exercisePhysical medicine and rehabilitationTrunkLow back painTest (biology)Area under the curveDiagnostic accuracyInternal medicinePathology

Abstract

fetched live from OpenAlex

The objective of this study was to assess the diagnostic value of common questionnaires and measures of physical performance in low back pain (LBP) syndrome. One hundred and fourteen patients with LBP classified according to the Quebec Task Force were compared with 50 patients with different pain syndromes but without apparent LBP. The discriminating value of each variable was estimated by calculating the area under the receiver operating characteristics (ROC) curve. The diagnostic value of the Million and Oswestry disability questionnaires was evident, with the area under the ROC curve varying between 0.73 and 0.88. The isometric trunk extension-flexion strength test with concomitant reaction-time test could not distinguish between patients (area under ROC curve 0.50-0.68). Sensitivity of pain drawing was excellent but specificity was low: 47% for men and 39% for women. In conclusion, disability questionnaires have discriminating power. The trunk muscle strength test does not perform well as a diagnostic tool. The area under the ROC curve and the use of other patients as controls make it easier to assess the diagnostic specificity of a particular method.

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)0.046
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 score0.322
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.046
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 head0.021
GPT teacher head0.327
Teacher spread0.306 · 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

Citations33
Published2001
Admission routes1
Has abstractyes

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