Leg-length discrepancy in revision total hip arthroplasty
Bibliographic record
Abstract
Aims: Leg-length discrepancy (LLD) following total hip arthroplasty (THA) is a source of patient dissatisfaction and morbidity. The objectives of this study were to characterize LLD following revision THA (rTHA) and evaluate the difference in LLD between navigated and non-navigated rTHA. Methods: This retrospective cohort study included 202 patients treated with rTHA performed between 2017 and 2021. An a priori power analysis determined that 101 patients in each group were required. Navigated and non-navigated rTHA were compared with regard to LLD (absolute value), re-revision rate, and patient-reported outcome measures (PROMs). Results: Mean postoperative LLD was 4.3 mm (SD 4.6) in all patients. In navigated rTHA, mean postoperative LLD of 3.7 mm (SD 4.7) was lower than preoperative LLD (7.5 mm (SD 6.1); p < 0.001). In non-navigated rTHA, postoperative LLD of 4.9 mm (SD 4.3) was lower than preoperative LLD (7.8 mm (SD 6.6); p < 0.001). Postoperative LLD was significantly lower in navigated compared with non-navigated rTHA in all patients and in sub-groups with preoperative LLD < 5 mm (1.7 mm vs 3.5 mm), < 10 mm (2.8 mm vs 3.9 mm), < 15 mm (3.0 mm vs 4.1 mm), and < 20 mm (3.3 mm vs 4.7 mm), respectively (p < 0.05). Based on revision type, postoperative LLD was significantly lower in navigated rTHA compared to non-navigated rTHA in those with both-component and acetabular component-only revisions (p < 0.05). Subsequent re-revision was required in three navigated rTHAs (3%) and eight non-navigated rTHAs (8%, p = 0.121). Changes in patient-reported Hip injury and Osteoarthritis Outcome Score Joint Replacement, Lower Extremity Activity Scale, and pain were not significantly different between navigated and non-navigated patients. Conclusion: Postoperative LLD was improved relative to preoperative LLD in rTHA with and without the use of navigation. Postoperative LLD was significantly lower in navigated rTHA compared with non-navigated rTHA. There was no significant difference in PROMs between groups. Based on these results, computer-assisted navigation seems to optimize leg-length correction and should be considered for use in rTHA involving the acetabular component, including both-component and acetabular component-only revisions. Of note, the present study was not designed to validate all aspects of all parameters of computer navigation; rather, it was specifically designed to assess LLDs when using navigation. Therefore, the present results only cover the topic of LLD when using navigation in comparison with manual techniques.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".