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Record W4283590428 · doi:10.21203/rs.3.rs-1708331/v2

Impact of soft tissue around the knee on the efficacy of extracorporeal shockwave therapy in knee osteoarthritis

2022· preprint· en· W4283590428 on OpenAlexaboutno aff
Yu Liu, Chunhu Wu, Changsong Chen, Lianhe Zhang, Gengyan Xing, Kun Wu, Zhe Zhao, Huan Geng, Huadong Yin, Xiaohua Hu, Yuhai Ma

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisWOMACVisual analogue scaleBody mass indexKnee JointExtracorporeal shockwave therapyKnee painPhysical therapySurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract Background: Knee osteoarthritis (KOA) is the leading cause of knee pain in middle-aged and older individuals. In recent years, extracorporeal shockwave therapy (ESWT) has been applied to treat patients with KOA to reduce pain and improve function. We aimed to determine the association between the distribution of tissue around the knee joint and the efficacy of ESWT in KOA treatment. We were also interested in studying KOA pathogenesis from the perspective of imaging evaluation. Materials and methods: Patients (n=123) diagnosed with KOA who received ESWT were selected to participate in this study, and were grouped according to their body mass index (BMI). The treatment parameters were as follows: 8000 pulses, 2.0 bar, 0.25 mJ/mm 2 , and 6 Hz/s once per week for 8 weeks. The visual analog scale (VAS), Lequesne index, and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) were measured before and after treatment to assess knee pain and functional recovery in all patients and according to BMI groups. Radiographs were used to measure the richness of the soft tissue around the knee joint. The correlation between the distribution of tissue, pain, and functional improvement was analyzed using the receiver operator characteristic (ROC) curve. The effect of BMI and the distribution of tissue around the knee joint on the efficacy of ESWT treatment in KOA patients were evaluated. Results: A total of 123 patients were enrolled; 59 were in the normal or below normal BMI (<25 kg/m 2 ) category (NBB group) and 64 were classified as overweight and above (BMI ≥ 25 kg/m 2 ) (OAB group). All the patients showed a reduction in pain after treatment compared to that before treatment (P <0.01). As measured by VAS, after the intervention, pain in the OAB group decreased to a greater extent than that in the NBB group (P < 0.01). As measured by the Lequesne and WOMAC indexes, after the intervention, the functional index of the OAB group improved to a greater extent than that of the NBB group (P < 0.01). We determined through the area under the curve (AUC) that, with VAS as the demarcation criterion, when the tibial plateau soft tissue ratio (TPSTR), femoral intercondylar apex soft tissue ratio (FIASTR), and medial tibial soft tissue ratio (MTSTR) exceeded 1.538, 1.534, and 1.296, respectively, the patient's pain relief was more pronounced the ESWT treatment was better. With pain in WOMAC as the demarcation criterion, the TPSTR, FIASTR, and MTSTR also are positively correlated with pain relief in patients. When the Lequesne and WOMAC scores were the demarcation criteria, the patients' function improved significantly when the the patella apical soft tissue ratio (PASTR) exceeded 2.401 and 2.635, respectively. Conclusion: ESWT can effectively alleviate pain and improve knee function in patients with KOA, and the efficacy of ESWT is closely related to the abundance around the knee joint; the soft tissue around the knee joint should also be an important reference factor and the focus of research in KOA treatment.

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 categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.417
Teacher spread0.345 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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