Does bariatric surgery really benefit patients before total knee arthroplasty? A systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: At present, whether bariatric surgery before total knee arthroplasty (TKA) affects the prognosis of subsequent TKA has been a topic of debate in the academic community. The primary purpose of this systematic review and meta-analysis was to investigate the effect of previous bariatric surgery on prosthetic revisions and postoperative complications after TKA. METHODS: We included prospective and observational studies published in English involving patients who had undergone bariatric surgery prior to TKA and compared them with morbidly obese patients with no history of bariatric surgery. The Newcastle-Ottawa Scale was used to assess the methodological quality of non-randomized case-control studies. The outcomes included revisions, infections, venous thromboembolism (VTE), blood transfusion, mortality, stiffness or manipulation under anesthesia (MUA), and medical complications. RESULTS: Of the 9 included studies with 166047 patients, 4 were matched cohort studies, 2 were unmatched cohort, and 3 were database studies. Methodological quality was high in ten studies and moderate in thirteen studies. Our analysis demonstrated that patients with TKA who had undergone prior bariatric surgery were associated with increased risks of long-term revision, long-term infection, long-term stiffness or MUA and blood transfusions, whereas prior bariatric surgery did not increase the risk of short-term complications and short-term revision. CONCLUSION: This meta-analysis highlights the risks of bariatric surgery prior to TKA and suggests that prior bariatric surgery may increase the risk of perioperative blood transfusion and also the risk of revision and infection in long-term follow-up. Surgeons can use this information to help counsel patients undergoing bariatric surgery before primary TKA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.046 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".