The lumbar stabilization exercise and balance training in low-grade degenerative lumbar spondylolisthesis - a prospective, clinical trial
Bibliographic record
Abstract
BACKGROUND: Patients with degenerative lumbar spondylolisthesis (DLS) may have low back pain (LBP), radicular pain and spinal instability. Current programs emphasize intervention of spinal stabilization exercise. However, no prospective, randomized studies have elucidated standardized treatment for DLS. OBJECTIVE: To examine the effect of spinal stabilization exercise and Biodex balance system (BBS) training in patients with DLS. METHODS: It was a prospective, clinical trial. Participants were allocated into three groups: (1) DLS-balance group treated with balance training (DLSB), (2) DLS non-balance training group (DLSNB), and (3) lumbar spondylosis without spondylolisthesis (SC). ALL patients underwent a rehabilitation program with lumbar stabilization exercises. The evaluation included the Numeric Pain Scale, the BBS, the Quebec back pain disability scale and Oswestry disability index. RESULTS: LBP was significantly different among three groups. Radicular pain was significantly different in the DLSB and SC groups. In post-hoc analysis, only the DLSB group had greater pain relief than the DLSNB group. Fall risk significantly decreased in the DLSB group. CONCLUSIONS: Lumbar stabilization exercise were beneficial for DLS. BBS could provide more pain relief than lumbar stabilization exercise alone. BBS also enhanced balance in DLS patients, thereby reducing fall risks. Findings could provide a clinical reference for designing rehabilitation programs.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".