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Record W2762166735 · doi:10.1177/2325967117729659

Outcomes and Complication Rates After Primary Anterior Cruciate Ligament Reconstruction Are Similar in Younger and Older Patients

2017· article· en· W2762166735 on OpenAlexaboutno aff
Mark E. Cinque, Jorge Chahla, Gilbert Moatshe, Nicholas N. DePhillipo, Nicholas I. Kennedy, Jonathan A. Godin, Robert F. LaPrade

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineArthrofibrosisSurgeryCohortAnterior cruciate ligamentRetrospective cohort studyOsteoarthritisAnterior cruciate ligament reconstructionWOMACRange of motionInternal medicine

Abstract

fetched live from OpenAlex

Background: Until recently, anterior cruciate ligament (ACL) tears in older patients were treated conservatively; however, these patients often experienced significant pain and instability. Purpose/Hypothesis: The purpose of this study was to compare the patient-reported outcomes, patient satisfaction, and failure rates of primary ACL reconstruction between a younger (age 20-30 years) and older (age 50-75 years) patient cohort. It was hypothesized that patients in the older cohort could achieve comparable clinical outcomes and retear rates following ACL reconstruction with a bone-tendon-bone autograft or allograft compared with the younger patients. Study Design: Cohort study; Level of evidence, 3. Methods: A retrospective analysis of prospectively collected data was performed. All patients undergoing a primary ACL reconstruction between 2010 and 2014 by a single surgeon were collated. Patients were divided into 2 groups based on age at the time of surgery: a younger cohort (20-30 years) and an older cohort (50-75 years). Patients were excluded if they were outside the desired age intervals; had revision ACL reconstructions; had a previous intra-articular infection in the ipsilateral knee; underwent prior alignment correction procedure, cartilage repair, or transplant procedure; had a concurrent posterior cruciate ligament tear; received meniscal allograft transplant; or had an intra-articular fracture. Subjective outcome scores (Tegner activity scale, Lysholm, International Knee Documentation Committee [IKDC], Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC], Short Form–12 [SF-12] mental health component summary [MCS], and SF-12 physical component summary [PCS]), retear rate, and rate of secondary arthrofibrosis surgery were documented at a minimum 2-year follow-up and were compared between groups. Results: A total of 85 patients met the inclusion criteria for this study: 52 patients (33 males, 19 females) in the younger cohort and 33 patients (14 males, 19 females) in the older cohort. No significant differences were found in any demographic factor except for age. Significant improvement in outcome scores from pre- to postoperative assessments was found in both groups. The younger cohort had significantly lower postoperative WOMAC scores ( P = .025). However, no significant differences were found between the younger and older cohorts in postoperative SF-12 PCS ( P = .487), SF-12 MCS ( P = .900), Lysholm score ( P = .660), IKDC score ( P = .256), Tegner activity score ( P = .420), or patient satisfaction ( P = .060). Within the older cohort, increasing age did not correlate with inferior postoperative outcome scores. Furthermore, no retears occurred in either group, and the rates of arthrofibrosis surgery were comparable (12% older cohort vs 13% younger cohort). Conclusion: Improved function and satisfaction, comparable to the younger age group, were achieved in patients older than 50 years undergoing ACL reconstruction. Furthermore, low failure rates can be achieved in both younger and older patients undergoing ACL reconstruction.

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 score0.312
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.270
Teacher spread0.262 · 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

Citations75
Published2017
Admission routes1
Has abstractyes

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