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Record W2314728175 · doi:10.2106/jbjs.n.00529

Cautious Optimism

2014· letter· en· W2314728175 on OpenAlexaboutno aff
Samuel A. Taylor, Robert G. Marx

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2014
Typeletter
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnterior cruciate ligamentPerioperativeLigamentSurgery

Abstract

fetched live from OpenAlex

Commentary Surgeons must balance the infection risk associated with fresh-frozen allograft tissue with the potential biomechanical inferiority of terminally irradiated tissue. The authors of the present study have made strides toward identifying a compromise between sterility and stability. We would suggest to the readers, however, that these are biomechanical results from the laboratory and do not represent patient outcomes. Thus, before the implementation of electron beam (e-beam) sterilization strategies, in vivo animal models should be investigated for biomechanical durability and histologic incorporation. ACL (anterior cruciate ligament) reconstruction involving allograft tissue has seen marked fluctuation with regard to use, acceptance, and excitement. Initially, allografts seemed to be the answer to reducing perioperative pain, limiting morbidity, and hastening recovery. This early enthusiasm has more recently been tempered by studies reporting significantly higher revision rates for ACL reconstructions performed with allograft compared with autograft tissue. The MOON group determined that use of allograft was a predictor of worse outcomes for the IKDC (International Knee Documentation Committee) questionnaire and KOOS (Knee injury and Osteoarthritis Outcome Score)1 and that the odds of revision were four times higher among those who underwent ACL reconstruction with allograft compared with autograft2. A meta-analysis of 5182 patients reported a threefold increase in the rerupture rate for BTB (bone-patellar tendon-bone) allograft reconstruction (12.7%) compared with BTB autograft (4.4%)3. A Canadian study involving nearly 13,000 ACL reconstructions indicated that allograft use was an independent risk factor for revision within five years4. Another study of 122 military cadets who had undergone ACL reconstruction prior to matriculation demonstrated that those who underwent allograft reconstruction were 7.7 times more likely to undergo subsequent revision5. When reading the above studies, it is important to remember that these were often mixed cohorts with regard to graft fixation and, perhaps more importantly, allograft processing. The critical question remains: Is the problem the allograft tissue itself or the manner in which it is processed? Although this answer remains elusive, the authors of the present study have made a valiant effort to address this question. It would appear that processing does play a role in graft failure. For example, high-dose gamma irradiation has been demonstrated to have detrimental effects on the biomechanical properties of grafts6-10. In response, some surgeons have traded the biomechanical risk for infection and immunologic risks—turning to fresh-frozen, nonirradiated, allograft tissue. This exodus is supported by several recent clinical outcomes studies. A systematic review, for example, revealed no difference between autograft and non-chemically processed, nonirradiated allograft. Mariscalco et al.11 identified nine prospective or retrospective comparative studies that compared autograft with nonirradiated allograft ACL reconstruction and failed to identify any significant differences between graft types with regard to failure, instrumented laxity, or subjective outcome measures. Another study of a younger population (less than twenty-five years old) retrospectively compared fifty-three patients who underwent BTB autograft with twenty-eight patients who underwent nonprocessed BTB allograft reconstruction and also found no difference with regard to the aforementioned outcome measures12. Guo et al.13 identified three cases of acute synovitis that they believed were secondary to immunologic rejection among thirty-three patients who underwent fresh-frozen allograft ACL reconstruction. Is there a compromise that could reduce infection and immunogenicity while preserving mechanical properties? Perhaps e-beam irradiation is the solution. In fact, e-beam irradiation was shown previously to more closely preserve graft properties compared with gamma irradiation14. The follow-up study, however, demonstrated adverse biomechanical effects of high-dose e-beam irradiation in an in vivo sheep ACL model15. Other investigators found that allografts treated with low16,17, moderate18, and even high-dose gamma irradiation16 had comparable biomechanical properties to nonprocessed allograft in the laboratory, but the clinical outcomes in patients have not supported this method for allograft sterilization1-5. Although the present study uses sound methodology and does a very good job investigating a clinically relevant question, we would caution against the implementation of e-beam sterilization for clinical use, at least until additional animal studies validate these interesting laboratory findings.

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)0.017
metaresearch head score (Gemma)0.110
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.110
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0050.017
Scholarly communication0.0110.016
Open science0.0070.007
Research integrity0.0350.071
Insufficient payload (model declined to judge)0.0250.016

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 head0.027
GPT teacher head0.246
Teacher spread0.219 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2014
Admission routes1
Has abstractyes

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