Management of a Chronically Infected and Unstable Revision Hip Prosthesis with Total Femur Arthroplasty and Antibiotic Cement – Case Report and Review of the Literature
Bibliographic record
Abstract
Background: Infection, instability, periprosthetic fracture, and severe bone loss are troublesome issues in revision hip arthroplasty. The occurrence of all four together represents a unique therapeutic challenge. Literature Review: Total femoral arthroplasty is described following tumor resection and in revision arthroplasty with severe bone loss. In these complex cases infection remains a significant concern with rates between 0 and 47% reported. For cases with infection, 2-stage revision procedures have been developed using antibiotic beads or custom total femur antibiotic spacers. However, these techniques involve long periods of non-weight-bearing that may be poorly tolerated in an older population. Case Presentation: A patient with a chronically infected and dislocating long-stemmed revision hip arthroplasty presented with a severely comminuted distal femur fracture. A 1-stage revision was successfully performed using a modular total femur prosthesis coated with antibiotic cement. Conclusion: This is the first reported instance of a successful 1-stage revision for infection and severe bone loss using total femur prosthesis. This technique may allow for early mobilization and the avoidance of multiple surgical procedures. Keywords: Total Femur Arthroplasty, Revision Arthroplasty, Infection, 1-Stage Revision, Hip Arthroplasty. Read more →
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".