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Prospective, Multi-Center, Pilot Study to Evaluate Symptom Relief in Patients with Medial Knee Osteoarthritis (OA) Treated with the KineSpring® Knee Implant for Load Reduction - The SOAR Protocol

2013· article· en· W2041387422 on OpenAlexaff
Jack Farr, Dennis C. Crawford, David R. Diduch, Elizabeth A. Arendt, C. Benjamin, Chuan Silvia Li

Bibliographic record

VenueJournal of Long-Term Effects of Medical Implants · 2013
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineOsteoarthritisImplantProspective cohort studyKnee painPhysical therapySurgery

Abstract

fetched live from OpenAlex

The study described here is designed as a prospective, multicenter, open-label, single-arm pilot study. Eligible subjects with symptomatic osteoarthritis of the medial compartment of the knee will be enrolled in the study and will receive the KineSpring® Knee Implant System. The study population will consist of adult patients between 25 and 80 years of age that have been diagnosed with medial knee osteoarthritis and have failed to improve after at least 6 months of conservative medical treatment. A patient is considered to have a clinically important change in OA pain and function with a minimum improvement of 20% compared to baseline measures. We will collect data on the safety and effectiveness of the KineSpring in patients with primarily unicompartmental medial knee osteoarthritis through 24 months of postoperative follow-up. These data will provide insights on the overall clinical success and safety outcome of KineSpring System.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.012
GPT teacher head0.292
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreProtocol

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

Citations1
Published2013
Admission routes1
Has abstractyes

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