Humerus Lengthening with a Motorized Intramedullary Nail: A Systematic Review of Outcomes and Complications
Bibliographic record
Abstract
Aim: In the past decade, internal limb lengthening nails have gained popularity. In this study, we aim to systematically review the literature on humerus limb lengthening with a motorized intramedullary nail (MIN). We intend to assess the outcome and complications of this technique. Materials and methods: . The inclusion criteria included limb lengthening of the humerus using an intramedullary nail, clinical studies, all levels of evidence, and no restriction to the date of publication. Results: Our search yielded 239 journal articles. A total of nine articles remained relevant based on the inclusion and exclusion criteria. The total number of patients was 20, with 22 segments lengthened. The mean age of the patients was 20.8-year-old [standard deviation (SD), 12.0; range, 13-51]. The mean gained length was 5.7 cm (SD, 0.9; range, 5-7.5) with a mean distraction protocol of 0.82 mm/day (SD, 0.2; range, 0.6-1). The average duration of lengthening was 71.6 days (SD, 12.8; range, 50-93), and the mean duration of consolidation was 192.3 days (SD, 40.5; range, 120-228). Reported complications included a range of motion (ROM) limitation, hardware failure, and hypertrophic bone regeneration. Conclusion: Humeral lengthening with an MIN provides favourable outcomes with low complication rates. Future high-level studies should focus on comparing long-term outcomes of humeral lengthening utilising internal and external fixation techniques. Clinical significance: Humeral lengthening using MIN can be used safely. Each surgical approach and type of nail have different risks and benefits. These should be carefully discussed when planning the surgery. How to cite this article: . Humerus Lengthening with a Motorized Intramedullary Nail: A Systematic Review of Outcomes and Complications. Strategies Trauma Limb Reconstr 2022;17(3):165-171.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".