Previous knee surgery increases risks of revision, infection, pain and stiffness after knee replacement arthroplasty: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Knee replacement arthroplasty(KRA), including Total knee arthroplasty (TKA) and Unicompartmental knee arthroplasty (UKA), is the primary method for treating end-stage knee osteoarthritis (KOA). However, a history of previous knee surgeries (such as knee arthroscopy, ligament reconstruction, meniscectomy, high tibial osteotomy, etc.) may potentially affect functional recovery and complication risks after knee replacement. Although some studies have proposed such associations, the existing evidence remains controversial, and there is a lack of systematic quantitative analysis. This study aims to assess the impact of previous knee surgery on functional outcomes and complications following KRA. METHODS: Following the PRISMA Guidelines, a systematic search was conducted in PubMed, Embase, Cochrane Library, and Web of Science databases up to August 4, 2024, for relevant studies. Demographic data, postoperative complications, and functional changes after primary KRA were evaluated in patients with and without a history of previous knee surgery. Statistical analysis of the included studies was performed using Stata 15.1 software. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the studies. RESULTS: This meta-analysis included 28 studies with 703,103 patients (35,535 with a history of previous knee surgery and 667,568 primary KRA patients). Compared to the primary knee surgery group, the previous knee surgery group had significantly higher rates of prosthetic aseptic revision (RR(95%CI) = 1.45 (1.18-1.78)) (relative risk, RR; Confidence Interval, CI), infection (RR(95%CI) = 1.36 (1.11-1.67)), knee stiffness (RR(95%CI) = 1.73 (1.02-2.96)), and knee pain (RR(95%CI) = 1.21 (1.08-1.34)). However, there were no significant differences in changes in Knee Society Score (KSS) function (WMD(95%CI) = -0.51 (-1.73 to 0.72)) (weighted mean difference, WMD), KSS pain score (WMD(95%CI) = 0.41 (-2.97 to 3.79)), or other knee function scores. CONCLUSION: Patients with a history of previous knee surgery have a higher likelihood of prosthetic revision, a greater risk of surgical site infections or periprosthetic infections, and a significantly higher incidence of knee stiffness and knee pain following KRA.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".