Revision Total Hip Arthroplasty in Solid Organ Transplant Patients: A Propensity Score-Matched Cohort Study for Aseptic and Infected Revisions
Bibliographic record
Abstract
Background Previous studies have demonstrated that solid organ transplant (SOT) patients undergoing primary total hip arthroplasty (THA) are at an increased risk of postoperative complications. The purpose of this study is to use a large, national database to investigate revision THA (rTHA) outcomes in SOT patients. Methods Nationwide Readmissions Database (NRD) from 2010-2018 was used, and ICD-9 and ICD-10 codes were used to identify all patients who underwent rTHA, including those with history of SOT. Propensity score matching (PSM) was used to analyze rTHA outcomes in SOT patients comparted to matched controls. Separate analysis performed for patients undergoing rTHA for prosthetic joint infection (PJI) vs other causes. Results A total of 414,756 rTHA, with 1837 of those being performed in SOT patients, were identified. Of these, 65,961 and 276 were performed for PJI in non-SOT and SOT patients, respectively. For non-PJI patients, SOT patients had higher 90-day all-cause readmission rates (24.0% vs 19.4%, P = .03) but lower rate for readmission related to rTHA (6.0% vs 9.2%, P = .03), but no difference readmission for specific rTHA complications, mortality (0.6% vs 1.3%, P = .20), or revision rTHA. Of PJI patients, SOT patients had no difference in overall 90-day readmission (38.6 vs 31.3%, P = .280), readmission for specific rTHA complications, re-revision, or mortality (4.7% vs 6.0%, P = .63). Conclusions SOT patients undergoing rTHA for aseptic reasons are higher risk of overall readmission but lower risk of readmission related to rTHA than appropriately matched controls. SOT PJI patients undergoing had similar rates of readmission, mortality, and revision surgery compared to matched non-SOT PJI patients.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".