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Record W2601624871 · doi:10.1177/0363546520904017

Determining the Patient Acceptable Symptomatic State for Patients Undergoing Arthroscopic Partial Meniscectomy in the Knee

2020· article· en· W2601624871 on OpenAlexaffabout
Tim Dwyer, Thomas Zochowski, Darrell Ogilvie‐Harris, John Theodoropoulos, Daniel B. Whelan, Jaskarndip Chahal

Bibliographic record

VenueThe American Journal of Sports Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsSt. Michael's HospitalToronto Western HospitalWomen's College HospitalUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineOsteoarthritisSurgeryArthroscopyTearsReceiver operating characteristicOrthopedic surgeryPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Background: Arthroscopic partial meniscectomy is one of the most common procedures in orthopaedic surgery. The patient acceptable symptomatic state (PASS), which defines a level of symptoms above which patients consider themselves well, remains to be well-defined in this population. Purpose: Using an anchor-based approach, our goal was to determine the 1-year PASS for the Knee injury and Osteoarthritis Outcome Score (KOOS), the International Knee Documentation Committee (IKDC) Subjective Knee Form, the Western Ontario Meniscal Evaluation Tool (WOMET), and the Marx Activity Scale (MAS) in patients who were treated with partial knee meniscectomy. Study Design: Case series; Level of evidence, 4. Methods: A consecutive series of patients with knee meniscal tears and a Kellgren-Lawrence grade of 0 to 2 treated with arthroscopic partial meniscectomy were eligible. The KOOS (0-100), IKDC (0-100), WOMET (0-100), and MAS (0-16) were administered at baseline and 12 months postoperatively. An external anchor question at 1 year postoperatively was used to determine PASS values. A receiver operating characteristic curve (ROC) analysis was used to determine the PASS value at which patients considered their status to be satisfactory. Results: The study included 110 patients (mean ± SD age, 53.8 ± 12.0 years), 57.3% were male, and the follow-up rate was 82%. In total, 70% of patients had an Outerbridge arthroscopic grade of 2 or lower. Based on ROC analysis, the 1-year postoperative PASS values (sensitivity, specificity) were 64.3 (47.8, 100.0) for KOOS Symptoms, 81.6 (71.6, 100.0) for KOOS Pain, 82.4 (82.1, 86.4) for KOOS Function in Daily Living, 71.0 (62.7, 81.8) for KOOS Function in Sport and Recreation, 51.0 (83.6, 95.5) for KOOS Knee-Related Quality of Life, 56.2 (82.1, 100.0) for IKDC, 58.5 (79.1, 100.0) for WOMET, and 7.0 (44.8, 68.2) for MAS. Baseline scores did not affect the PASS threshold across the different instruments. However, patients with higher baseline scores were more likely to achieve the PASS for the KOOS Symptoms (odds ratio [OR], 2.808; P = .047), IKDC (OR, 4.735; P = .006), and WOMET (OR, 2.985; P = .036). Age, sex, and cartilage status were not significantly related to the odds of achieving the PASS for any of the patient-reported outcome measures. Conclusion: These findings allow researchers and clinicians to determine whether partial meniscectomy is meaningful to patients at the individual level and will be helpful for responder analysis in future trials related to the treatment of meniscal abnormality.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.274
Teacher spread0.263 · 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

Citations20
Published2020
Admission routes2
Has abstractyes

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