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Record W2800063159 · doi:10.1177/0363546518768753

Change in KOOS and WOMAC Scores in a Young Athletic Population With and Without Anterior Cruciate Ligament Injury

2018· article· en· W2800063159 on OpenAlexfundaboutno aff
Ivan J. Antosh, Steven J. Svoboda, Karen Y. Peck, E’Stephan J. Garcia, Kenneth L. Cameron

Bibliographic record

VenueThe American Journal of Sports Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
FundersMcMaster University
KeywordsMedicineAnterior cruciate ligamentPhysical therapyWOMACMinimal clinically important differenceOsteoarthritisACL injuryPopulationCohortCohort studyProspective cohort studyOrthopedic surgeryRandomized controlled trialSurgeryInternal medicine

Abstract

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BACKGROUND: Several studies have examined changes in patient-reported outcome measures (PROMs) after anterior cruciate ligament (ACL) injury, but no studies to date have prospectively evaluated changes from preinjury baseline through injury and follow-up among ACL-injured patients compared to the baseline and follow-up changes of uninjured patients. PURPOSE: To examine changes in PROMs over time from preinjury baseline to at least 2 years after ACL reconstruction and to compare these changes with those of an uninjured control group having similar physical activity requirements. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: The authors conducted a prospective cohort study with a nested case-control analysis at a US service academy. All incoming first year students were recruited to participate in this study. Consenting participants completed a baseline questionnaire that included the KOOS (Knee injury and Osteoarthritis Outcome Score), WOMAC (Western Ontario and McMaster Universities Osteoarthritis Index), and MARS (Marx Activity Rating Scale). Participants who sustained a subsequent ACL injury completed assessments at the time of surgery and at 6, 12, and 24 months after surgery. Healthy participants were recruited to repeat the baseline assessments within 1 year of graduation. Inter- and intragroup differences at these time points were evaluated with dependent and independent t tests, respectively. We also compared these results with established minimum clinically important difference (MCID) values. RESULTS: Of 1268 first year students entering the academy, 1005 with no previous injuries consented to participate in this study (82% male, mean ± SD age 19 ± 1 years). Of those enrolled, 30 suffered an ACL injury and met the inclusion criteria for this study. Ninety uninjured control students who met the inclusion criteria completed follow-up assessments. There were statistically significant differences across all KOOS and WOMAC subscales between ACL-injured group and uninjured group at the time of the final follow-up assessment. Four KOOS subscales (Pain, Symptoms, Sports and Recreation Function, and Knee-Related Quality of Life) and the WOMAC Stiffness subscale demonstrated >8-point differences between groups, which exceeded the established MCID for these instruments. There were no significant differences between the ACL-injured group and uninjured groups noted for the MARS ( P = .635). At the time of final follow-up, the ACL-injured group also reported significant deficits on the WOMAC Stiffness subscale ( P = .032), the MARS ( P = .030), and all KOOS subscales, with the exception of Functional Activities of Daily Living, as compared with their preinjury baseline scores. These deficits exceeded the established MCID values for 3 KOOS subscales and the MARS. CONCLUSION: Patients with ACL injuries reported significant deficits on PROMs at least 2 years after surgical reconstruction in relation to preinjury baseline scores and an uninjured control group. Many of these deficits exceeded established MCID values.

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 score0.270
Threshold uncertainty score0.346

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 studies0.0000.001
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 head0.009
GPT teacher head0.295
Teacher spread0.286 · 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

Citations52
Published2018
Admission routes2
Has abstractyes

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