Subacute Clinical Features After Arthroscopy Surgical Reconstruction of Complete Anterior Cruciate Ligament Rupture: A Case-Control Study
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to describe the clinical features in the subacute phase after surgical reconstruction of complete anterior cruciate ligament rupture (ACLR) with respect to healthy participants. METHODS: A case-control observational study was performed. A total sample of 80 participants was recruited from an outpatient clinic and divided into case (n = 40 patients after ACLR reconstruction in subacute phase) and control (n = 40 healthy participants) groups. Outcomes, including pain intensity, range of motion (ROM), stability, and functionality were assessed by the visual analogue scale, universal goniometer, the Star Excursion Balance Test, and the Western Ontario and McMaster Universities Osteoarthritis Index, respectively. RESULTS: There were no statistically significant differences (P > .05) for sex, side, age, and body mass index between patients with ACLR after reconstruction surgery and healthy participants. Statistically significant differences (P < .001) with a large effect size (Rosenthal r) from -0.86 to -0.93 were shown for ROM (median ± interquartile range [IQR], -70.00° ± 10.00°) and Star Excursion Balance Test (mean ± standard deviation, -38.31 cm ± 4.52 cm) reduction, as well as higher visual analogue scale (median ± IQR, 7.00 ± 1.00) and Western Ontario and McMaster Universities Osteoarthritis Index (median ± IQR, 68.77 ± 6.29) scores in favor of the ACLR reconstructed group, with respect to the healthy control group. CONCLUSIONS: Measurable clinical differences of functionality, stability, and ROM should be considered during the evaluation of patients at a subacute period after complete ACLR reconstruction surgery with respect to healthy matched controls.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".