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Record W2163679898 · doi:10.1007/s00167-013-2747-x

Use of cell‐free collagen type I matrix implants for the treatment of small cartilage defects in the knee: clinical and magnetic resonance imaging evaluation

2013· article· en· W2163679898 on OpenAlexaff
Karl F. Schüttler, Hanno Schenker, Christina Theisen, Markus D. Schofer, Alan Getgood, Philip P. Roessler, Johannes Struewer, Marga B. Rominger, Turgay Efe

Bibliographic record

VenueKnee Surgery Sports Traumatology Arthroscopy · 2013
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsFowler Kennedy Sport Medicine ClinicWestern University
Fundersnot available
KeywordsMedicineCartilageVisual analogue scaleMagnetic resonance imagingImplantSurgeryArticular cartilage repairRadiological weaponOsteoarthritisDemineralized bone matrixArticular cartilageNuclear medicineRadiologydBmAnatomyPathology

Abstract

fetched live from OpenAlex

PURPOSE: Articular cartilage defects of the knee are a common condition for which several repair techniques have been described. The aim of the present study was to assess medium-term results of a one-step procedure using a cell-free collagen type I matrix. METHODS: Fifteen patients with articular cartilage defects of the knee were treated with an 11-mm-diameter cell-free collagen type 1 matrix implant. The matrices were implanted in a press-fit manner into the defect after careful debridement down to the subchondral bone but without penetration of this margin. Follow-up examinations were carried out at 6 weeks, 6 months, and at 12, 24, 36, and 48 months after implantation. Clinical assessment included the visual analogue scale (VAS), the Tegner activity scale, and the International Knee Documentation Committee (IKDC) score. Radiological assessment for graft attachment and tissue regeneration was performed using the magnetic observation of cartilage repair tissue (MOCART) score. RESULTS: A total of 15 patients (males: n = 6 and females: n = 9) with a mean age of 26.4 years (range 19-40) were treated. The mean VAS improved significantly when compared to the preoperative values (P < 0.05). Six weeks after implantation, IKDC values were slightly lower than the preoperative values (n.s.), but increased significantly at final follow-up (P < 0.05). At 24 months, there were no significant differences in the median Tegner score between the post-operative values and the preoperative values (n.s.). However, after 36 months, a significant improvement was noted that lasted at least up to 48 months (P < 0.05). The MOCART score improved consistently up to 4 years after implantation, with significant improvements already observed after 12 months (P < 0.05). No correlation between the clinical scores and the MOCART score could be perceived. CONCLUSION: The present study showed that the use of cell-free collagen type I matrix implants led to a significant and durable improvement in all the clinical and imaging scores investigated 4 years after implantation. LEVEL OF EVIDENCE: IV.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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

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 head0.054
GPT teacher head0.315
Teacher spread0.261 · 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 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

Citations55
Published2013
Admission routes1
Has abstractyes

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