Trajectory of Short- and Long-Term Recovery of Tibial Shaft Fractures After Intramedullary Nail Fixation
Bibliographic record
Abstract
OBJECTIVE: To determine the trajectory of recovery after tibial shaft fracture treated with intramedullary nail over the first 5 years and to evaluate the magnitude of the changes in functional outcome at various time intervals. DESIGN: Prospective cohort study. SETTING: A Level 1 trauma center. PATIENTS/PARTICIPANTS: One hundred thirty-two patients with tibial shaft fracture (OTA 42-A, B, C) were enrolled into the Center's prospective orthopaedic trauma database between January 2005 and February 2010. Functional outcome data were collected at baseline, 6 months, 1 year, and 5 years. INTERVENTION: Enrolled patients were treated acutely with intramedullary nailing of their tibia. MAIN OUTCOME MEASUREMENTS: Evaluation was performed using the Short Form-36 and Short Musculoskeletal Function Assessment (SMFA). RESULTS: Mean SF-36 physical component scores improved between 6 and 12 months (P = 0.0008) and between 1 and 5 years (P = 0.0029). Similarly, mean SMFA dysfunction index scores improved between 6 and 12 months (P = 0.0254) and between 1 and 5 years (P = 0.0106). In both scores, the rate or slope of this improvement is flatter between 1 and 5 years than it is between 6 and 12 months. Furthermore, SF-36 and SMFA scores did not reach baseline at 5 years (SF-36 P < 0.0001, SMFA P = 0.0026). A significant proportion of patients were still achieving a minimal clinically important difference in function between 1 and 5 years (SF-36 = 54%, SMFA = 44%). CONCLUSIONS: The trajectory of functional recovery after tibial shaft fracture is characterized by an initial decline in function, followed by improvement between 6 and 12 months. There is still further improvement beyond 1 year, but this is of flatter trajectory. The 5-year results indicate that function does not improve to baseline by 5 years after injury. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".