Outcomes of total hip arthroplasty using dual mobility components in patients with a femoral neck fracture
Bibliographic record
Abstract
Aims Dislocation is the most common indication for further surgery following total hip arthroplasty (THA) when undertaken in patients with a femoral neck fracture. This study aimed to assess the complication rates of THA with dual mobility components (THA-DMC) following a femoral neck fracture and to compare outcomes between THA-DMC, conventional THA, and hemiarthroplasty (HA). Methods We performed a systematic review of all English language articles on THA-DMC published between 2010 and 2019 in the MEDLINE, EMBASE, and Cochrane databases. After the application of rigorous inclusion and exclusion criteria, 23 studies dealing with patients who underwent treatment for a femoral neck fracture using THA-DMC were analyzed for the rate of dislocation. Secondary outcomes included reoperation, periprosthetic fracture, infection, mortality, and functional outcome. The review included 7,189 patients with a mean age of 77.8 years (66.4 to 87.6) and a mean follow-up of 30.9 months (9.0 to 68.0). Results THA-DMC was associated with a significantly lower dislocation rate compared with both THA (OR 0.26; 95% CI 0.08 to 0.79) and HA (odds ratio (OR) 0.27; 95% confidence interval (CI) 0.15 to 0.50). The rate of large articulations and of intraprosthetic dislocation was 1.5% (n = 105) and 0.04% (n = 3) respectively. Conclusion THA-DMC when used in patients with a femoral neck fracture is associated with a lower dislocation rate compared with conventional arthroplasty options. There was no increase in the rates of other complication when THA-DMC was used. Future cost analysis and prospective, comparative studies are required to assess the potential benefit of using THA-DMC in these patients. Cite this article: Bone Joint J 2020;102-B(7):811–821.
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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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".