Effect of Customized Foot Orthotics in Addition to Usual Care for the Management of Chronic Low Back Pain Following Work-Related Low Back Injury
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to compare the effect of customized foot orthotics in addition to usual care (UC) compared with UC alone for the treatment of patients with chronic low back pain after work-related injury. METHODS: Sixty-two consecutive patients presenting with chronic (>3 months), nonspecific, low back pain following work-related low back injury were included in the study. A total of 30 patients in the UC group were given a 6-week exercise therapy program along with prescription analgesics. The intervention group, composed of 32 patients, received UC in addition to customized foot orthotics (orthotics group). All subjects completed the Oswestry Disability Index at the initiation of the study and at 8-week follow-up. Work disability, as defined by working at usual, preinjury job labor level, was recorded at baseline and 8-week follow-up. RESULTS: A total of 28 subjects in the UC group and 32 in the orthotics group completed the study. The 2 groups were well matched in terms of age, sex distribution, and duration of low back pain as well as baseline Oswestry Disability Index score. At 8 weeks, both groups had improved. The orthotics group had a lower Oswestry Disability Index than the UC group (P < .01), with a smaller proportion of the orthotics group using any form of prescribed analgesics for back pain (P < .05). CONCLUSIONS: The findings showed that patients in this study with chronic, nonspecific low back pain following work-related low back injury had greater improvement in short-term outcomes with orthotics and UC than with UC alone.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".