Reaming Does Not Affect Functional Outcomes after Open and Closed Tibial Shaft Fractures: The Results of a Randomized Controlled Trial
Bibliographic record
Abstract
© Copyright 2015 Wolters Kluwer Health, Inc. All rights reserved. Objectives: We sought to determine the effect of reaming on 1-year 36-item short-form general health survey (SF-36) and short musculoskeletal function assessment (SMFA) scores from the Study to Prospectively Evaluate Reamed Intramedullary Nails in patients with Tibial Fractures. Design: Prospective randomized controlled trial.1319 patients were randomized to reamed or unreamed nails. Fractures were categorized as open or closed. Setting: Twenty-nine academic and community health centers across the US, Canada, and the Netherlands. Patients/Participants: One thousand three hundred and nineteen skeletally mature patients with closed and open diaphyseal tibia fractures. Intervention: Reamed versus unreamed tibial nails. Main Outcome Measurements: SF-36 and the SMFA. Outcomes were obtained during the initial hospitalization to reflect preinjury status, and again at the 2-week, 3-month, 6-month, and 1-year follow-up. Repeated measures analyses were performed with P < 0.05 considered significant. Results: There were no differences between the reamed and unreamed groups at 12 months for either the SF-36 physical component score [42.9 vs. 43.4, P 0.54, 95% Confidence Interval for the difference (CI) -2.1 to 1.1] or the SMFA dysfunction index (18.0 vs. 17.6, P 0.79. 95% CI, -2.2 to 2.9). At one year, functional outcomes were significantly below baseline for the SF-36 physical componentf score, SMFA dysfunction index, and SMFA bothersome index (P < 0.001). Time and fracture type were significantly associated with functional outcome. Conclusions: Reaming does not affect functional outcomes after intramedullary nailing for tibial shaft fractures. Patients with open fractures have worse functional outcomes than those with a closed injury. Patients do not reach their baseline function by 1 year after surgery.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".