Morbidity resulting from the treatment of tibial nonunion with the Ilizarov frame.
Bibliographic record
Abstract
OBJECTIVE: To determine the sources and magnitude of residual morbidity after successful treatment of tibial nonunion using the Ilizarov device and techniques. DESIGN: A retrospective cohort study. SETTING: A level 1 trauma centre. PATIENTS: Sixteen patients with healed tibial nonunion. INTERVENTION: Application of the Ilizarov device and techniques to obtain union of a previous ununited tibial fracture. MAIN OUTCOME MEASURES: Patient satisfaction and sources of morbidity through clinical review and a visual analogue scale. Two disease-specific outcome measurement scales were used to assess ankle dysfunction. Radiographs were examined to determine the presence of arthrosis. RESULTS: Residual pain was present in over 90% of patients at a mean follow-up of 39 months: in 80% the worst pain was in the ankle, less than 10% felt the worst pain in the knee or at the fracture site. Mean ankle osteoarthritis scores were 3.4 for pain and 4.0 for disability, compared with 0.76 and 0.90 respectively for age-matched controls. Mean ankle-hindfoot scores were between 64 and 100. CONCLUSION: Ankle pain with disability is the major source of residual disability after successful use of the Ilizarov device for the treatment of tibial nonunion.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".