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Record W2784015270 · doi:10.1177/1071100717747590

Combination Therapy Versus Exercise and Orthotic Support in the Management of Pain in Plantar Fasciitis: A Randomized Controlled Trial

2018· article· en· W2784015270 on OpenAlexaff
Eda Çınar, Shikha Saxena, Fatma Uygur

Bibliographic record

VenueFoot & Ankle International · 2018
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicinePlantar fasciitisLow level laser therapyRandomized controlled trialPhysical therapyExtracorporeal shock wave therapyVisual analogue scaleRepeated measures designLaser therapyHeelSurgery

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.291
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations41
Published2018
Admission routes1
Has abstractyes

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