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Record W2048942170 · doi:10.5152/tjr.2010.24

Tramadol Iontophoresis Added to Treatment of Knee Osteoarthritis

2010· article· en· W2048942170 on OpenAlexaboutno aff
Ayşe Dicle Turhanoğlu, Hayal Güler, Deniz İnanoğlu, Kerem İnanoğlu, Selim Turhanoğlu

Bibliographic record

VenueArchives of Rheumatology · 2010
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsIontophoresisTramadolMedicineTranscutaneous electrical nerve stimulationOsteoarthritisAnesthesiaAnalgesicRadiology

Abstract

fetched live from OpenAlex

Objective: The objective of the present study was to investigate whether tramadol iontophoresis added to therapy is superior to the therapy methods alone (transcutaneous electrical nerve stimulation (TENS), hot pack, ultrasound, and exercise therapy) in patients with knee OA. Materials and Methods: A total of 72 patients who admitted to the outpatient clinic of Physical Medicine and Rehabilitation were included in this study. The diagnosis was based on the American College of Rheumatology (ACR) criteria for knee OA. The patients were randomly separated into two groups. Group 1 received physical therapy and Group 2 received tramadol iontophoresis in addition to the therapy for a period of two weeks. Patients were evaluated according to pain and functional capacity assessed using visual analogue scale (VAS) and Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) before therapy and following the 10th session, and at 1 and 3 months. Results: The mean age and duration of the knee pain were 58.53±8.38, 5.00±2.66 years in the control group and 58.15±7.70, 4.71±2.70 years in the tramadol iontophoresis group. There were no significant differences between groups in the mean age and duration of the knee pain, body mass index (BMI), VAS and WOMAC scores before therapy. Following the 10th session, and after 1 and 3 months, VAS and WOMAC scores were significantly decreased in both groups when compared with the baseline values (p

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.009
GPT teacher head0.247
Teacher spread0.238 · 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 designBench or experimental
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

Citations6
Published2010
Admission routes1
Has abstractyes

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