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Record W4386467140 · doi:10.5606/tftrd.2023.12106

Comparison of shock wave therapy and corticosteroid injection in the treatment of greater trochanteric pain syndrome: A single-blind, randomized study

2023· article· en· W4386467140 on OpenAlexaboutno aff
Hanife Çağlar Yagcı, İlker Yağcı, Fatih Bağcıer

Bibliographic record

VenueTurkish Journal of Physical Medicine and Rehabilitation · 2023
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisVisual analogue scaleWOMACRandomized controlled trialAnesthesiaPhysical therapySurgery

Abstract

fetched live from OpenAlex

Objectives: The aim of this study was to compare the efficacy of the corticosteroid (CS) injection and shock wave therapy (SWT) in the treatment of greater trochanteric pain syndrome (GTPS). Patients and methods: Between 2020 September and 2021 October, a total of 60 patients with GTPS (12 males, 48 females; mean age: 50.8±8.5 years; range, 34 to 65 years) were included. The patients were randomly assigned to two groups as the SWT group (n=32) receiving one session of SWT per week for a total of three weeks and CS injection group (n=28) receiving CS and local anesthetic. Both groups were evaluated using the Short Form-36 (SF-36) at baseline and three months and using the Visual Analog Scale (VAS) and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) at baseline, three weeks, and three months. Results: The mean VAS, greater trochanter tenderness, and WOMAC scores of both groups were similar at baseline, while the third-week and three-month scores were significantly lower in both groups compared to baseline (p<0.05). There was no significant difference in the treatment efficacy between the groups (p>0.05). There was a similar improvement in SF-36 physical function, physical role difficulty, and pain subscales in both groups (p<0.05). Conclusion: Our study results show that both CS injection and SWT are effective modalities and none of the treatments is superior to each other.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.223

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.059
GPT teacher head0.354
Teacher spread0.295 · 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 designObservational
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

Citations5
Published2023
Admission routes1
Has abstractyes

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