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 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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".