The Use of Combined Magnetic Field Treatment for Fracture Nonunions: A Prospective Observational Study
Bibliographic record
Abstract
This study evaluated the effectiveness and safety of bone growth stimulation using combined magnetic field (CMF) for the treatment of fracture nonunions. In this prospective multicenter study, patients were assessed monthly for 9 mo, or until they demonstrated a healed nonunion, and were assessed at a final follow-up 3 mo after treatment completion. The primary outcome was the presence or absence of fracture healing at the nonunion site, determined by clinical and radiographic assessment. Enrolled in this study were 112 patients with 116 fracture nonunions. Fifty-two (44.8%) patients demonstrated a healed nonunion between treatment initiation and 12-mo- posttreatment initiation (9 mo of treatment plus 3 mo posttreatment follow-up). Tibial nonunions had a higher percentage of healed fractures compared to other fracture types (78% vs. 46.5%, respectively; p = 0.004). This study demonstrated that noninvasive CMF technology healed 78% of tibial fracture nonunions and 45% of all fracture nonunions (p = 0.004). Additionally, pain at rest, with stress, and on weight bearing all decreased following treatment with CMF, with no adverse events reported. These results indicate that CMF is a beneficial noninvasive treatment modality for nonunions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".