Perioperative complications and mid-term outcomes in total hip and knee joint arthroplasty among solid organ transplant recipients: lowest reoperation-free survival and patient survivorship in lung transplant recipients
Bibliographic record
Abstract
INTRODUCTION: Performing total joint replacements (TJR) in patients with solid organ transplantations (SOT) is associated with an increased risk of complications and reoperation. The aim of this study is to report on implant survivorship, patient survivorship, and complication rates for total knee arthroplasty (TKA) and total hip arthroplasty (THA) performed in heart, lung, liver and kidney transplant recipients. MATERIALS AND METHODS: Forty patients with heart, lung, liver, or kidney transplants who underwent primary THA or TKA between January 1, 2013, and July 31, 2023, were included. Implant survivorship, reoperation-free survivorship, patient survivorship, and complication rates were compared between the subgroups. RESULTS: At a mean follow-up of 5.18 years, Implant survivorship and reoperation-free survival for the entire cohort at the last follow-up were 97.5% and 85%, respectively. Kaplan-Meier survival estimates demonstrated 5- and 10-year reoperation-free survival rates of 86.5% (95% CI: 76%-98.4%) and 57.6% (95% CI: 25.6%-100%), respectively. The lung transplant group had the shortest reoperation-free survival, although not statistically significant (p = 0.07), a significantly higher risk of reoperation, with a hazard ratio (HR) of 6.9 (95% CI: 1.1-41.2, p = 0.04) and both the lowest 5-year patient survivorship at 68.6% (p = 0.04) and the highest risk of death after TJR with a HR of 7 (95% CI: 1.2-45.5, p = 0.03). CONCLUSION: Patients with SOT exhibit excellent mid-term implant survivorship, with a rate of 97.5%. Lung transplant recipients show the lowest rates of both reoperation-free survival and overall patient survivorship compared to heart, kidney, and liver transplant recipients. Despite this, the 90-day complication rates are similar across all organ groups.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".