Path Analysis of Factors for Delayed Healing and Nonunion in 416 Operatively Treated Tibial Shaft Fractures
Why this work is in the frame
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Bibliographic record
Abstract
UNLABELLED: A prospective observational study was done in 41 trauma centers. Four hundred sixteen patients with tibial shaft fractures were treated operatively and followed up for at least 6 months. Fifty-two (13%) cases of delayed healing or nonunion were reported. In such nonrandomized observational studies, multiple interrelationships exist between prognostic factors and patient outcomes. We used path analyses to investigate prognostic factors associated with the occurrence of delayed healing or nonunion. The most important factors were identified using multivariate regression analyses, and interrelationships between factors were illustrated using a path diagram. Fractures with open injuries less than and greater than 5 cm were 3.6 and 5.7 times as likely, respectively, to have delayed healing or nonunion as fractures with no skin injuries. The Müller-AO classification of fractures did not provide additional prognostic information. The risk of healing problems was doubled for fractures of the distal shaft and for fractures showing a postoperative diastasis. Treatment options showed an indirect effect on outcome with the occurrence of diastasis. A model for predicting delayed healing or nonunion is proposed. We encourage the use of path analysis in orthopaedics as a powerful visual technique to interpret data from observational studies. LEVEL OF EVIDENCE: Prognostic study, Level II-1 (retrospective study). See the Guidelines for Authors for a complete description of levels of evidence.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it