Combination Therapy Versus Exercise and Orthotic Support in the Management of Pain in Plantar Fasciitis: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: This study aimed at estimating the effectiveness of two commonly used modalities-extracorporeal shock wave therapy (ESWT) and low-level laser therapy (LLLT)-each combined with usual care (exercises and orthotic supports) in comparison to only usual care to relieve pain in patients with plantar fasciitis (PF). METHODS: for 3 sessions, once a week; LLLT group received gallium-aluminum-arsenide laser with 850 nm wavelength for 10 sessions, 3 times a week. Pain was measured by Foot Function Index-pain subscale (FFI-p) and Numerical Rating Scale for pain (NRS-p). The scores were recorded at baseline, third week, and third month after the treatment. Analysis was performed using repeated measures ANOVA. RESULTS: There was a significant improvement in pain over the 3 months in all groups on both FFI-p ( P < .001) and NRS-p ( P < .001). In NRS-p, LLLT group had significantly lower pain than ESWT ( P = .002) at the third week and control ( P = .043) and ESWT ( P = .003) at third month. In FFI-p total score, ESWT group had higher pain than LLLT ( P = .003) and control ( P = .035) groups at third week and LLLT ( P = .010) group at third month. CONCLUSION: When LLLT and ESWT were combined with usual care, LLLT was found to be more effective than ESWT in reducing pain in PF at short-term follow-up. LEVEL OF EVIDENCE: Level II, comparative study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".