How Are We Measuring Patient Satisfaction After Anterior Cruciate Ligament Reconstruction?
Bibliographic record
Abstract
BACKGROUND: Reconstruction of the anterior cruciate ligament (ACL) is one of the most common orthopaedic operations in the United States. The long-term impact of ACL reconstruction is controversial, however, as longer term data have failed to demonstrate that ACL reconstruction helps alter the natural history of early onset osteoarthritis that occurs after ACL injury. There is significant interest in evaluating the value of ACL reconstruction surgeries. PURPOSE: To examine the quality of patient satisfaction reporting after ACL reconstruction surgery. STUDY DESIGN: Systematic review; Level of evidence, 4. METHODS: A systematic review of the MEDLINE database was performed using the PubMed interface. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines as well as the PRISMA checklist were employed. The initial search yielded 267 studies. The inclusion criteria were: English language, US patient population, clinical outcome study of ACL reconstruction surgery, and reporting of patient satisfaction included in the study. Study quality was assessed using the Newcastle-Ottawa scale. RESULTS: A total of 22 studies met the inclusion criteria. These studies comprised a total of 1984 patients with a mean age of 31.9 years at the time of surgery and a mean follow-up period of 59.3 months. The majority of studies were evidence level 4 (n = 18; 81.8%), had a mean Newcastle-Ottawa scale score of 5.5, and were published before 2006 (n = 17; 77.3%); 5 studies (22.7%) failed to clearly describe their method for determining patient satisfaction. The most commonly used method for assessing satisfaction was a 0 to 10 satisfaction scale (n = 11; 50.0%). Among studies using a 0 to 10 scale, mean satisfaction ranged from 7.4 to 10.0. Patient-reported outcome and objective functional measures for ACL stability and knee function were positively correlated with patient satisfaction. Degenerative knee change was negatively correlated with satisfaction. CONCLUSION: The level of evidence for studies reporting patient satisfaction is low, and the methodologies for reporting patient satisfaction are variable. Additionally, within the past decade there has been a significant decline in the inclusion of this outcome measure within published ACL studies. As sports surgeons are increasingly called on to demonstrate the value of operative procedures, attention should be paid to understanding and reporting patient satisfaction.
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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 | 0.100 | 0.288 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".