PHYSICAL MEASUREMENTS AND QUESTIONNAIRES AS DIAGNOSTIC TOOLS IN CHRONIC LOW BACK PAIN
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".