Patellofemoral Ağrısı Olan Hastalarda Ayak Egzersizlerinin Ağrı, Alt Ekstremite Biyomekanisi ve Fonksiyonelliği Üzerine Etkileri
Bibliographic record
Abstract
KISACIK, P. The Effects of Foot Exercises on Pain, Lower Extremity \nBiomechanics, and Functionality in Patients with Patellofemoral Pain. \nHacettepe University Instutute of Health Science Doctor of Philosophy Thesis in \nPhysical Therapy and Rehabilitation Program, Ankara, 2017. The aim of this \nstudy was to investigate the effects of short foot exercise (SFE) on pain, lower \nextremity biomechanics and functioning in patients with patellofemoral pain (PFP). \nTwenty-two PFP patients aged between 25 to 60 years were included in this study. \nThey were randomly divided into two groups. The first group (SEEP) was followed \nunder the exercise program including knee and hip exercises, and the second group \n(AKEP) was followed under SFE in addition to the exercise program including knee \nand hip exercises 2 days per week for 6 weeks. At the beginning and the end of the \nstudy, for pain at sitting, squatting, climbing stairs Visual Analogue Scale (VAS); for \nother symptoms Kujala Patellofemoral Symptom Scale (KPSS); for lower extremity \nbiomechanics measurement of Q angle, Navicular Drop Test (NDT), Calcaneo-tibial \nangle (CTA) and Foot Posture Index (FPI); for functionality test of muscle strength \nwith hand dynamometer, Timed Up&Go test (TUG), Y balance test (YBT), Foot \nFunction Index (FFI), Western Ontario and McMaster Universities Arthritis Index \n(WOMAC) were performed. As a result of this study, it was found that all \nparameters were improved in both groups, whereas the improvements in the pain \nintensity of sitting and stair activities, values of NDT and KTA, hip extensor and \nabductor muscle strength were statistically significant in AKEP group compared to \nSEEF group (p<0.05). In conclusion, it was shown that SFE has a positive effect on \npain, lower extremity biomechanics and functionality in patients with PFP. At this \npoint, SFE is an exercise approach in order to increase the success of the \nrehabilitation program in patients with PFP.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".