PAPER 189: EVALUATION OF PEDIATRIC FEMUR FRACTURE TECHNIQUES: TROCHANTERIC ANTEGRADE VS. FLEXIBLE FEMUR NAILING IN PEDIATRIC FEMUR FRACTURES
Bibliographic record
Abstract
Purpose: Femur fractures in children have a significant impact on families and the hospital system in Canada. There are several methods for treating femur fractures in children. The purpose of this study was to determine which of two techniques: Flexible Femoral Nailing (FFN) or Trochanteric Antegrade Nail (TAN), are the most safe and efficacious. Method: Hospital charts for all paediatric femur fracture patients between 1984 and 2006 treated with either FFN or TAN were reviewed. Demographic, clinical, radiographic and hospital stay data were collected and analyzed. Results: Ninety-seven children (100 fractures) were reviewed. The average age of patients was 11.9 years (SD = 4.4). Fifty-two fractures were treated with FFN and 48 fractures were treated with TAN. No serious complications were encountered in either group, including AVN. Minor complications in the FFN group included three patients with mal-alignment, and one with shortening of the limb. Two patients in the TAN group had shortening of the fractured limb. No radiographic differences were noted. The median length of stay for patients treated with FFN was 3 days (IQR = 2) and for patients treated with TAN was 3 days (IQR = 2). Overall, there were no significant differences in the clinical findings (including complications), radiographic evaluations, or length of stay between FFN and TAN cohorts. The only significant difference between the groups was length of surgical time (p value Conclusion: TAN is as safe and efficacious a treatment as FFN but requires addition operating room time, and hence hospital resources.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".