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Record W4214895790 · doi:10.1097/corr.0000000000002158

The Knee Injury and Osteoarthritis Outcome Score Does Not Have Adequate Structural Validity for Use With Young, Active Patients With ACL Tears

2022· article· en· W4214895790 on OpenAlexaffabout
Hana Marmura, Paul F. Tremblay, Alan Getgood, Dianne Bryant

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2022
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsImpactFowler Kennedy Sport Medicine ClinicMcMaster UniversityLondon Health Sciences CentreLawson Health Research InstituteWestern University
Fundersnot available
KeywordsMedicineTearsOsteoarthritisAnterior cruciate ligamentReturn to sportPhysical therapySports medicineACL injuryOrthopedic surgerySurgeryPhysical medicine and rehabilitationPathologyRehabilitationAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The Knee Injury and Osteoarthritis Outcome Score (KOOS) is well known and commonly used to assess young, active patients with ACL injuries. However, this application of the outcome measure has been called into question. There is currently no evidence supporting the structural validity of the KOOS for this patient population. Structural validity refers to whether a questionnaire meant to provide scores on different subscales behaves as intended in the populations of interest. Structural validity should be assessed for all questionnaire measures with multiple items or subscales. QUESTIONS/PURPOSES: Does the KOOS demonstrate adequate structural validity in young, active patients with ACL tears, when evaluated using (1) exploratory and (2) confirmatory factor analyses? METHODS: Between January 2014 and March 2017, 1033 patients were screened for eligibility in the Stability 1 randomized controlled trial from nine centers in Canada and Europe. Patients were eligible if they had an ACL deficient knee, were between 14 and 25 years old, and were thought to be at higher risk of reinjury based on the presence of two or more of the following factors: participation in pivoting sports, presence of a Grade 2 pivot shift or greater, generalized ligamentous laxity (Beighton score of 4 or greater), or genu recurvatum greater than 10°. Based on this criteria, 367 patients were ineligible and another 48 declined to participate. In total, 618 patients were randomized into the trial. Of the trial participants, 98% (605 of 618) of patients had complete baseline KOOS questionnaire data available for this analysis. Based on study inclusion criteria, the baseline KOOS data from the Stability 1 trial represents an appropriate sample to investigate the structural validity of the KOOS, specifically for the young, active ACL deficient population.A cross sectional retrospective secondary data analysis of the Stability 1 baseline KOOS data was completed to assess the structural validity of the KOOS using exploratory and confirmatory factor analyses. Exploratory factor analysis investigates how all questionnaire items group together based on their conceptual similarity in a specific sample. Confirmatory factor analysis is similar but used often in a second stage to test and confirm a proposed structure of the subscales. These methods were used to assess the established five-factor structure of the KOOS (symptoms [seven items], pain [nine items], activities of daily living [17 items], sport and recreation [five items], and quality of life [four items]) in young active patients with ACL tears. Incremental posthoc modifications, such as correlating questionnaire items or moving items to different subscales, were made to the model structure until adequate fit was achieved. Model fit was assessed using chi-square, root mean square error of approximation (RMSEA) and an associated 90% confidence interval, comparative fit index (CFI), Tucker-Lewis index (TLI), as well as standardized root mean square residual (SRMR). Adequate fit was defined as a CFI and TLI > 0.9, and RMSEA and SRMR < 0.08. RESULTS: Structural validity of the KOOS was not confirmed when evaluated using (1) exploratory or (2) confirmatory factor analyses. The exploratory factor analysis, where the 42 KOOS items were allowed to group naturally, did not reflect adequate fit for a five-factor model (TLI = 0.828). Similarly, the confirmatory factor analysis used to investigate the KOOS structure as it was originally developed, revealed inadequate fit in our sample (RMSEA = 0.088 [90% CI 0.086 to 0.091]). Our analysis suggested a modified four-factor structure may be more appropriate in young, active ACL deficient patients; however, the final version presented here is not appropriate for clinical use because of the number and nature of post-hoc modifications required to reach adequate fit indices. CONCLUSION: The established five-factor structure of the KOOS did not hold true in our sample of young, active patients undergoing ACL reconstruction, indicating poor structural validity. CLINICAL RELEVANCE: We question the utility and interpretability of KOOS subscale scores for young, active patients with ACL tears with the current form of the KOOS. A modified version of the KOOS, adjusted for this patient population, is needed to better reflect and interpret the outcomes and recovery trajectory in this high-functioning group. A separate analysis with a defined a priori development plan would be needed to create a valid alternative.

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)0.010
metaresearch head score (Gemma)0.016
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.082
GPT teacher head0.398
Teacher spread0.316 · 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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Citations21
Published2022
Admission routes2
Has abstractyes

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