Significance of sub grouping patients with chronic low back pain in management decisions: A prospective study
Bibliographic record
Abstract
Background: The Quebec Task Force classification (QTF) was originally designed to help in making a clinical decision and to aid in determining the prognosis. However, the predictive validity and prognostic significance of the classification was debated. We conducted the study to determine the discriminative and prognostic significance of the modified Quebec Task Force classification in chronic low back pain patientsMaterials & Methods: 183 consecutive chronic low back pain(>7 weeks of continuous pain) patients in the age groups of 18-65 years who presented to a tertiary care centre in South India and followed up for a minimum of 6 months were included in the study. Patients were assigned to one of the four QTF categories after a detailed history and examination. Pain severity and functional disability were assessed using LBPRS and RMDQ respectively. The patients were then put on the common specific rehabilitation protocol and analgesics, and followed up every six weeks to look for compliance with the treatment. The scores (LBPRS, RMDQ) were noted again at 3 and 6 months. The comparison of scores was done among the 4 QTF categories at the time of presentation, at 3 months and at 6 months Result: There were no significant differences in the distribution of age, sex, occupation or educational status among different QTF categories. Non-parametric tests using Wilcoxon Signed Rank test showed significant improvement in LBPRS and RMDQ scores with time in each category(p value
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".