Complications of Elongating Intramedullary Rods in the Treatment of Lower Extremity Fractures for Osteogenesis Imperfecta: A Meta-Analysis of 594 Patients in 40 Years
Bibliographic record
Abstract
BACKGROUND: Osteogenesis imperfecta is a collagen mutation-related disease characterized by bone fragility and other extraskeletal manifestations. Intramedullary fixation for deformity correction or fracture is the standard care. Elongating rods are designed to accommodate growth, with the aim of preventing additional operations and/or complications associated with nonelongating rods. Although elongating rods have been in use for many years, estimates of the clinical outcomes vary. We conducted a systematic review and meta-analysis to synthesize the literature on outcomes of elongating rods and nonelongating rods. Meta-analysis was used to compare the complication rates and reoperation rates. METHODS: We conducted the literature search, systematic review, and meta-analysis in accordance with Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) guidelines. Comparative cohort studies and large case series detailing complication rates and reoperation rates of elongating and nonelongating rods were included. Random effect models were used to summarize the complication rates and reoperation rates of intramedullary rod procedures. RESULTS: A total of 397 studies were identified and 24 studies were included in the final cohort. Compared with rates from nonelongating rods, osteogenesis imperfecta Patients using elongating rods had a complication rate of 61% and a reoperation rate of 78%. Reoperation rates dropped with succeeding generations of elongating rods. Pooling data from 600 patients, we identified a 9% complication rate per rod per follow up year and 5% reoperation rate per rod and per follow up year in the cohort of elongating rod fixation. The Bailey-Dubow rod had the highest complication rate per rod per follow up year (12%), largely because of its T piece relate problems. The most popular fixator Fassier-Duval rod had a complication rate per rod per follow up year of 9%. About 68% of complications were mechanical-biological related. CONCLUSION: Pooling data from published literature demonstrates the advantage of elongating rods over nonelongating rods. However, as high as 9% complication rate per rod per follow up year was associated with elongating fixation. Notably, most complications are both mechanical and biological related. LEVEL OF EVIDENCE: Level III.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.047 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".