Radiographic and clinical outcome of tibial plateau fractures treated with bone allograft
Bibliographic record
Abstract
Abstract Background To determine the clinical outcome of patients who had been treated with bone allografts during open reduction and internal fixation (ORIF) of tibial head fractures. Methods Patients who suffered a medial, lateral, or bicondylar fracture of the tibial plateau and underwent surgical treatment by open reduction and internal fixation (ORIF) using human femoral head bone allografts were included. Patients were invited to provide information for the following: Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), EuroQol Five Dimension score (EQ-5D), Lower Extremity Functional Scale (LEFS) and Parker Mobility Score. Bone mineral density (BMD) of the allograft area and the healthy human bone tissue were measured by quantitative computed tomography. Results A total of 22 patients with a mean follow-up time of 2.88 ± 2.46 years were included in our study. The most common fractures observed in this study were classified as Schatzker II (11 patients, 50.0%) or AO/OTA 41.B3 (12 patients, 54.5%) fractures. Postoperative WOMAC total was 13.0 (IQR = 16.3, range 0–33). Median quality of life (EQ-5D) score was 0.887 ± 0.121 (range 0.361–1.000). Median Lower Extremity Functional Scale (LEFS) score was 57.5 ± 19.0 (range 33–79). Mean Parker Mobility Score was 9 (range 6–9). Median bone mineral density (BMD) for the whole group was 300.04 ± 226.02 mg/cm 3 (range − 88.68 to 555.06 mg/cm 3 ) for region of interest (ROI 5) (central), 214.80 ± 167.45 mg/cm 3 (range − 7.16 to 597.21 mg/cm 3 ) for ROI 1–4 (marginal zones: medial, lateral, ventral, dorsal) and 168.14 ± 65.54 mg/cm 3 (range 17.47–208.97 mg/cm 3 ) for healthy bone tissue (femur and tibia). Conclusion Based on WOMAC scores, LEFS, ambulatory status, and quality of life findings, it can be concluded that following tibial head ORIF with allograft bone patients has promising results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".