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Record W2955825503 · doi:10.1177/0363546519857589

Outcomes and Patient Satisfaction With Arthroscopic Partial Meniscectomy for Degenerative and Traumatic Tears in Middle-Aged Patients With No or Mild Osteoarthritis

2019· article· en· W2955825503 on OpenAlexaboutno aff
Alejandro Lizaur-Utrilla, Francisco A. Miralles‐Muñoz, Santiago González-Parreño, Fernando A. Lopez‐Prats

Bibliographic record

VenueThe American Journal of Sports Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisWOMACPatient satisfactionTearsUnivariate analysisSurgeryProspective cohort studyBody mass indexCohortOdds ratioMultivariate analysisCohort studyPhysical therapyInternal medicinePathology

Abstract

fetched live from OpenAlex

Background: There is controversy about the benefit of arthroscopic partial meniscectomy (APM) for degenerative lesions in middle-aged patients. Purpose: To compare satisfaction with APM between middle-aged patients with no or mild knee osteoarthritis (OA) and a degenerative meniscal tear and those with a traumatic tear. Study Design: Cohort study; Level of evidence, 2. Methods: A comparative prospective study at 5 years of middle-aged patients (45-60 years old) with no or mild OA undergoing APM for degenerative (n = 115) or traumatic (n = 143) tears was conducted. Patient satisfaction was measured by a 5-point Likert scale and functional outcomes by the Knee injury and Osteoarthritis Outcome Score (KOOS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Univariate and multivariate regression analyses were used to identify factors correlating with patient-reported satisfaction at 5 years postoperatively. Results: Baseline patient characteristics were not different between groups. At the 5-year evaluation, the satisfaction rate in the traumatic and degenerative groups was 68.5% versus 71.3%, respectively ( P = .365). Patient satisfaction was significantly associated with functional outcomes ( r = 0.69; P = .024). In the degenerative group, 43 patients (37.4%) had OA progression to Kellgren-Lawrence (K-L) grade 2 or 3, but only 24 patients (20.8%) had a symptomatic knee at final follow-up. Multivariate regression analysis for patient dissatisfaction at 5-year follow-up showed the following significant independent factors: female sex (odds ratio [OR], 1.6 [95% CI, 1.1-2.3]; P = .018), body mass index >30 kg/m 2 (OR, 2.6 [95% CI, 1.7-4.9]; P = .035), lateral meniscal tears (OR, 0.6 [95% CI, 0.1-0.9]; P = .039), and OA progression to K-L grade ≥2 at final follow-up (OR, 1.4 [95% CI, 1.2-2.6]; P = .014). At the final evaluation, there were no significant differences between groups in pain scores ( P = .648), WOMAC scores ( P = .083), or KOOS-4 scores ( P = .187). Likewise, there were no significant differences in the KOOS subscores for Pain ( P = .144), Symptoms ( P = .097), or Sports/Recreation ( P = .150). Although the degenerative group had significantly higher subscores for Activities of Daily Living ( P = .001) and Quality of Life ( P = .004), the differences were considered not clinically meaningful. Conclusion: There were no meaningful differences in patient satisfaction or clinical outcomes between patients with traumatic and degenerative tears and no or mild OA. Predictors of dissatisfaction with APM were female sex, obesity, and lateral meniscal tears. Our findings suggested that APM was an effective medium-term option to relieve pain and recover function in middle-aged patients with degenerative meniscal tears, without obvious OA, and with failed prior physical therapy.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.246
Teacher spread0.238 · 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".

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Citations32
Published2019
Admission routes1
Has abstractyes

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