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Record W1996436028 · doi:10.2147/orr.s48629

Bridging the osteoarthritis treatment gap with the KineSpring Knee Implant System: early evidence in 100 patients with 1-year minimum follow-up

2013· article· en· W1996436028 on OpenAlexaboutno aff
Jon E. Block, London London, Smith, Larry E. Miller

Bibliographic record

VenueOrthopedic Research and Reviews · 2013
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACMedicineOsteoarthritisImplantPhysical therapyOrthopedic surgerySurgeryAlternative medicine

Abstract

fetched live from OpenAlex

Abstract: Almost 4 million Americans are within the knee osteoarthritis (OA) treatment gap, the period from unsuccessful exhaustion of conservative treatment to major surgical intervention. New treatment alternatives for symptomatic knee OA are greatly needed. The purpose of this report was to assess outcomes of a joint-unloading implant (KineSpring ® Knee Implant System) in patients with symptomatic medial knee OA. A total of 100 patients enrolled in three clinical trials were treated with the KineSpring System and followed for a minimum of 1 year. All devices were successfully implanted and activated, with no operative complications. Knee pain severity improved 60% ( P < 0.001) at 1 year, with 76% of patients reporting a minimum 30% improvement in pain severity. All Western Ontario and McMaster Universities Arthritis Index (WOMAC) subscores significantly improved at 1 year, with a 56% improvement in pain, 57% improvement in function, and a 39% improvement in stiffness (all P < 0.001). The percentage of patients experiencing a minimum 20% improvement in WOMAC subscores was 74% for pain, 83% for function, and 67% for stiffness. During follow-up, six (6%) patients required additional surgery, including four total knee arthroplasties and two high tibial osteotomies. The KineSpring System effectively bridges the treatment gap between failed conservative care and surgical joint-modifying procedures. Keywords: implant, KineSpring, knee, medial, osteoarthritis, unloading

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.387

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 science0.0000.000
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 head0.068
GPT teacher head0.318
Teacher spread0.250 · 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 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

Citations6
Published2013
Admission routes1
Has abstractyes

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