Bridging the osteoarthritis treatment gap with the KineSpring Knee Implant System: early evidence in 100 patients with 1-year minimum follow-up
Bibliographic record
Abstract
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
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".