A Scoping Review of Total Hip Arthroplasty Survival and Reoperation Rates in Patients of 55 Years or Younger: Health Services Implications for Revision Surgeries
Bibliographic record
Abstract
Background: Total hip arthroplasty (THA) in younger patients is projected to increase by a factor of 5 by 2030 and will have important implications for clinical practice, policymaking, and research. This scoping review aimed to synthesize and summarize THA implants' survival, reoperation, and wear rates and identify indications and risk factors for reoperation following THA in patients ≤55 years old. Material and methods: Standardized scoping review methodology was applied. We searched 4 electronic databases (Medline, Embase, CINAHL, and Web of Science) from January 1990 to May 2019. Selection criteria were patients aged ≤55 years, THA survival, reoperation, and/or wear rate reported, a minimum of 20 reoperations included, and minimum level III based on the Oxford Level of Evidence. Two authors independently reviewed the citations, extracted data, and assessed quality. Results: Of the 2255 citations screened, 35 retrospective cohort studies were included. Survival rates for THA at 5 and 20 years were 90%-100% and 60.4%-77.7%, respectively. Reoperation rates at ≤5-year post THA ranged from 1.6% to 5.4% and increased at 10-20 years post THA (8.2%-67%). Common causes for reoperation were aseptic loosening of hip implants, osteolysis, wear, and infection. Higher reoperation and lower survival rates were seen with hip dysplasia and avascular necrosis than with other primary diagnoses. Conclusions: Over time, THA prosthetic survival rates decreased, and reoperation increased in patients ≤55 years. Aseptic loosening of hip implants, osteolysis, wear, and infection were the most frequent reasons for the reoperation.
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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 | 0.018 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.039 | 0.045 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".