Comparison of the Efficiency and Safety of Total Ankle Replacement and Ankle Arthrodesis in the Treatment of Osteoarthritis: An Updated Systematic Review and Meta‐analysis
Bibliographic record
Abstract
Abstract While osteoarthritis is a common degenerative disease, ankle osteoarthritis is a subdivision that has received little attention. Two effective ways to treat osteoarthritis of the ankle are total ankle replacement (TAR) and ankle arthrodesis (AAD). Whether TAR or AAD is more beneficial for treatment is controversial. The purpose of this meta‐analysis was to compare the efficiency (clinical outcome and patient satisfaction) and safety (complications and survival) of these two procedures. The Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) statement was performed as a guideline for this study. Three electronic databases, PubMed, Web of Science, and Cochrane Library, were searched up to May 2019, with no language restrictions. Prospective or retrospective comparative studies were identified. The outcomes included clinical outcome, patient satisfaction, complications, and survival. Review Manager (Revman) 5.3 software was used to conduct the data analysis. We only selected literature from the past 5 years (no earlier than 2015). Seven comparative studies were included. There were six cohort studies and one cross‐sectional study. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of cohort studies, and The Agency for Healthcare Research and Quality (AHRQ) checklist was chosen to assess the quality of cross‐sectional studies. No significant difference was observed for efficiency and safety. Clinical outcome was included in five studies with four different scoring systems. Two of them used the American Orthopaedic Foot & Ankle Society (AOFAS) questionnaire scores to assess the two procedures (mean difference, −4.26; 95% confidence interval [CI], −11.37–2.85; P = 0.24; I2 = 1%). Patient satisfaction (risk ratio [RR], 0.96; 95% CI, 0.65–1.40; P = 0.82; I2 = 54%), complications (RR, 1.15; 95% CI, 0.16–8.21; P = 0.89; I2 = 84%), and survival (RR, 1.91; 95% CI, 0.33–11.08; P = 0.47; I2 = 90%) showed no significant difference between the TAR group and the AAD group. This meta‐analysis showed no statistically significant difference between TAR and AAD in clinical outcome, patient satisfaction, complications, and survival. This revealed that TAR and AAD could appear to have similar results in these aspects. Therefore, the present results are not sufficient to conclude which of these two methods is better. Further studies are needed to obtain more clues.
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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 | 0.031 | 0.068 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.048 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".