Does the Chronicity of Anterior Cruciate Ligament Ruptures Influence Patient-Reported Outcomes Before Surgery?
Bibliographic record
Abstract
BACKGROUND: The time between an anterior cruciate ligament (ACL) injury and ACL reconstruction (ACLR) may influence baseline knee-related and general health-related patient-reported outcome measures (PROMs). Despite the common use of PROMs as main outcomes in clinical studies, this variable has never been evaluated. PURPOSE: To compare baseline health-related quality of life measures and the prevalence/pattern of meniscal and articular cartilage lesions between patients who underwent acute and chronic ACLR so as to provide clinicians with benchmark PROMs in 2 different patient populations with ACL injuries. STUDY DESIGN: Cross-sectional study; Level of evidence, 3. METHODS: A total of 1192 patients from the MOON (Multicenter Orthopaedic Outcomes Network) cohort who underwent primary ACLR were eligible. "Acute" ACLR was defined as <3 months (n = 853; 71.6%) and "chronic" ACLR as >6 months (n = 339; 28.4%) from injury. Patient demographics, surgical characteristics (articular cartilage injury, medial meniscal [MM] and lateral meniscal [LM] tears), and baseline PROM scores (Marx activity rating scale, International Knee Documentation Committee [IKDC] subjective form, Knee injury and Osteoarthritis Outcome Score [KOOS], and Short Form-36 Health Survey [SF-36]) were collected to determine whether the time from injury to ACLR influences (1) baseline PROMs and (2) the pattern and prevalence of concurrent articular cartilage and meniscal injuries. Analysis of covariance models were used to adjust for confounders on baseline outcome scores (age, sex, body mass index [BMI], smoking status, competition level, education). RESULTS: ); however, the chronic group was older, had a higher BMI, and consisted of fewer collegiate athletes. A significantly greater number of partial LM tears were seen in the acute group versus the chronic group (14.2% vs 6.5%, respectively; P < .001), but there were more meniscal tears overall (73.5% vs 63.2%, respectively; P = .001), complete MM tears (49.0% vs 22.5%, respectively; P < .001), and articular cartilage injuries (54.0% vs 32.8%, respectively; P < .001) in the chronic group versus the acute group. After controlling for confounders, patients in the chronic ACLR group reported a significantly lower baseline Marx score (7.75 vs 12.10, respectively; P < .001) but higher baseline IKDC, SF-36 physical functioning, and all KOOS subscale scores except the KOOS-quality of life subscale score compared to those in the acute ACLR group; however, only the KOOS-sports and recreation subscale exceeded the minimum clinically importance difference of 8 points (62.30 vs 48.26, respectively; P < .001). CONCLUSION: After controlling for age, sex, competition level, smoking, and BMI, patients in the chronic ACLR group participated in less pivoting and cutting sports but reported better pain/function. Whether decreased activity is deliberate after an ACL injury or patients who undergo chronic ACLR are simply less active and may be treated successfully without surgery warrants further investigation. Nonrandomized studies that utilize PROMs should consider time from injury in study design and data interpretation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".