Conservative therapy for plantar fasciitis: a narrative review of randomized controlled trials.
Bibliographic record
Abstract
A narrative literature review of RCTs only, was conducted to ascertain which conservative treatments provide the best results for plantar fasciitis patients. Stretching, prefabricated and custom-made orthotics and night splints have all been scrutinized in numerous studies with mixed results. Chiropractic manipulative therapy has been examined in one study, with favorable results. Therapeutic ultrasound and low intensity laser therapy have been examined in one study apiece with unsatisfactory results. Based on the trials reviewed a trial of therapy beginning with low-cost, patient-centered treatments is recommended, particularly stretching, over-the-counter orthotics, and patient education. Several (but not all) of the reviewed articles indicated that custom-made orthoses are more beneficial for plantar fasciitis than over-the-counter orthotics. In the event these treatments do not provide satisfactory results, use of night splints should be considered. Based on this review, there is no support for the use of magnetic insoles for plantar fasciitis. Most of the studies were found to have at least one methodological flaw, including inadequate sample sizes, high drop-out rates, comparing multiple interventions to multiple interventions (thus making it difficult to determine the effect of each individual intervention) and lack of long-term follow-up. Outcome measure use between studies was inconsistent.
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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 | 0.011 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".