Porous cementless cups combined with trabecular metal augments in revision hip arthroplasty: mid-term outcomes
Bibliographic record
Abstract
Reconstruction of acetabular bone defects represents one of the most technically demanding aspects of revision total hip arthroplasty. Although numerous implant options and surgical techniques have been proposed, porous acetabular components combined with trabecular metal augments have gained widespread acceptance as a contemporary reconstructive strategy. The present study aims to assess implant survivorship and to report mid-term clinical and radiographic outcomes associated with this technique. We identified 69 revision total hip arthroplasties (69 patients) performed at the Department of Joint Arthroplasty of the Priorov National Medical Research Center of Traumatology and Orthopedics between January 2016 and June 2022, using porous acetabular cups in combination with trabecular metal augments. Among these patients, 46 (66.6%) were female and 23 (33.4%) were male. The mean patient age was 59.9 years (± 12.4), with a mean follow-up duration of 4.9 years (± 1.78), ranging from a minimum of 2.6 years to a maximum of 9 years. Functional outcomes were assessed using the Harris Hip Score (HHS), Visual Analogue Scale (VAS), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), while implant survival was evaluated using Kaplan-Meier analysis. The overall HHS significantly improved from a preoperative mean of 32.9 (± 9.8) to a postoperative mean of 86.7 (± 4.9). VAS scores decreased from 8.1 (± 0.5) to 3.4 (± 0.5), WOMAC scores decreased from 61.3 (± 4.7) to 24.7 (± 2.4), indicating favorable clinical and functional outcomes (p < 0.00001 for each scale). Kaplan-Meier survival analysis demonstrated a 9 years (109.7 months) cumulative implant survivorship rate of 98.55%. The results indicate that porous acetabular cups combined with trabecular metal augments represent an effective option in revision hip arthroplasty, demonstrating excellent mid-term outcomes in terms of both implant survivorship and functional improvement.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".