Patients with low back pain differ from those who also have leg pain or signs of nerve root involvement – a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Leg pain associated with low back pain (LBP) is recognized as a risk factor for a poor prognosis, and is included as a component in most LBP classification systems. The location of leg pain relative to the knee and the presence of a positive straight leg raise test have been suggested to have clinical implications. To understand differences between such leg pain subgroups, and whether differences include potentially modifiable characteristics, the purpose of this paper was to describe characteristics of patients classified into the Quebec Task Force (QTF) subgroups of: 1) LBP only, 2) LBP and pain above the knee, 3) LBP and pain below the knee, and 4) LBP and signs of nerve root involvement. METHODS: Analysis of routine clinical data from an outpatient department. Based on patient reported data and clinical findings, patients were allocated to the QTF subgroups and described according to the domains of pain, activity limitation, work participation, psychology, general health and clinical examination findings. RESULTS: A total of 2,673 patients aged 18-95 years (median 47) who were referred for assessment of LBP were included. Increasing severity was consistently observed across the subgroups from LBP only to LBP with signs of nerve root involvement although subgroup differences were small. LBP patients with leg pain differed from those with LBP only on a wide variety of parameters, and patients with signs of nerve root involvement had a more severe profile on almost all measures compared with other patients with back-related leg pain. CONCLUSION: LBP patients with pain referral to the legs were more severely affected than those with local LBP, and patients with signs of nerve root involvement were the ones most severily affected. These findings underpin the concurrent validity of the Quebec Task Force Classification. However, the small size of many between-subgroup differences amid the large variability in this sample of cross-sectional data also underlines that the heterogeneity of patients with LBP is more complex than that which can be explained by leg pain patterns alone. The implications of the observed differences also require investigation in longitudinal studies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".