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Record W4294604759

Is USG-guided aspiration more effective than physiotherapy in the treatment of Baker’s cyst?

2022· article· en· W4294604759 on OpenAlexaboutno aff
Nurmuhammet Taş, Hülya Uzkeser, Akın Erdal

Bibliographic record

VenueDergiPark (Istanbul University) · 2022
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal synovial abnormalities and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyCystPhysical medicine and rehabilitationRadiology
DOInot available

Abstract

fetched live from OpenAlex

Aim: Previous publications have described various therapeutic modalities for symptomatic cysts, including non-steroidal anti-inflammatory drugs, cystostomy, physical therapy, and exercises. The objective of thise study was to elucidate the effectiveness of shrinking the cyst without steroidal injection and to compare aspiration with classic physiotherapy and exercises.Material and Method: This randomized, controlled trial involved 40 patients with Baker’s cyst. The participants were randomized into two groups, (I) an aspiration group (n=20) and (II) a control group (n=20). In the aspiration group, Baker’s cyst content was aspirated percutaneously under USG guidance, while no aspiration was performed in the control group. Pain was evaluated with a visual analog scale, while the Lysholm knee scoring scale and Cincinnati knee rating system were employed to determine functional status. Quality of life and disability were evaluated using the Nottingham Health Profile and the Western Ontario and McMaster Universities Arthritis Index .Results: Differences were observed in USG measurements (width, length, and area) and clinical parameters before and after treatment in both groups. However, although these differences were greater in the aspiration group, they were not statistically significant.Conclusion: Our results indicate that cyst aspiration performed with USG provides no additional effect to those of physical exercises and cold application. Exercise therapy and cold application should be considered before proceeding with an invasive procedure.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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 designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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