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Record W2768039145 · doi:10.1177/0363546517738000

Autologous Chondrocyte Implantation “Sandwich” Technique Compared With Autologous Bone Grafting for Deep Osteochondral Lesions in the Knee

2017· article· en· W2768039145 on OpenAlexaboutno aff
Tom Minas, Takahiro Ogura, Jeff Headrick, Tim Bryant

Bibliographic record

VenueThe American Journal of Sports Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteochondritis dissecansSurgeryAutologous chondrocyte implantationOsteoarthritisAvascular necrosisCohortArticular cartilageInternal medicineFemoral head

Abstract

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BACKGROUND: Treating symptomatic osteochondral defects is challenging, especially in young adults with deep (>8-10 mm) empty defects after osteochondritis dissecans (OCD) or collapsed condyles secondary to avascular necrosis (AVN). For this population, osteoarthritis (OA) is inevitable if articular congruence is not restored. PURPOSE: To describe the autologous chondrocyte implantation (ACI) "sandwich" technique with autologous bone grafting (ABG) and compare it with ABG alone for restoration of the osteochondral unit. The midterm to long-term outcomes in patients after the treatment for OCD and AVN will be reported and compared. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: The outcomes for a consecutive cohort of 24 patients who underwent combined ABG with the ACI sandwich technique between 2001 and 2013 (ACI sandwich group) was compared with a historical control group of 17 consecutive patients who underwent ABG alone between 1995 and 2002 (ABG group) by a single surgeon for symptomatic deep (>8 mm) osteochondral lesions. Patients who were followed up with a minimum of 2 years were included in this study. The modified Cincinnati Knee Rating System, the Western Ontario and McMaster Universities Osteoarthritis Index, a visual analog scale (VAS), the Short Form-36, and a patient satisfaction survey were used to evaluate clinical outcomes. Survival analysis was performed using the Kaplan-Meier method, with no clinical improvement, graft failure, or conversion to prosthetic arthroplasty as the endpoint (failure). Kellgren-Lawrence (K-L) grading to assess OA progression was also performed. RESULTS: In the ABG group, 13 of 17 patients (76%) were available with a mean follow-up of 15.7 years postoperatively (range, 5-21 years). In the ACI sandwich group, all 24 patients were available with a mean follow-up of 7.8 years postoperatively (range, 2-15 years). No significant differences were observed between the groups in terms of age, sex, side of the operated knee, body mass index, lesion type, lesion size, lesion depth, lesion location, or the need for realignment osteotomy. Eight patients (62%) were considered failures in the ABG group, while 3 patients (13%) were considered failures in the ACI sandwich group. The survival rate was significantly better in the ACI sandwich group than the ABG group (87% vs 54% at 5 years, respectively; P = .0025). All functional scores in patients with retained grafts significantly improved in the ACI sandwich group, whereas only the VAS score showed significant improvement in the ABG group. The patient satisfaction survey showed a very high satisfaction rate in the ACI sandwich group, with over 90% of patients reporting their knees as good or excellent and being satisfied with the procedure. In the ACI sandwich group, K-L grading demonstrated no significant OA progression from preoperatively to a mean 5.1 years postoperatively. CONCLUSION: Our study showed that the ACI sandwich technique provided excellent and superior survival rates compared to ABG alone and significant improvements over midterm to long-term follow-up. This unique treatment offers native joint preservation for conditions that naturally will progress to OA and eventually require prosthetic arthroplasty.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.017
GPT teacher head0.294
Teacher spread0.276 · 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
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

Citations74
Published2017
Admission routes1
Has abstractyes

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