Reamed Versus Nonreamed Intramedullary Nailing of Lower Extremity Long Bone Fractures: A Systematic Overview and Meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To determine the effect of reamed versus nonreamed intramedullary (IM) nailing of lower extremity long bone fractures on the rates of nonunion, implant failure, malunion, compartment syndrome, pulmonary embolus, and infection. DESIGN: Quantitative systematic review of prospective, randomized controlled trials. DATA IDENTIFICATION: MEDLINE and SCISEARCH computer searches provided lists of published randomized clinical trials from 1969 to 1998. Extensive hand searches of major orthopaedic journals, bibliographies of major orthopaedic texts, and personal files identified additional studies. STUDY SELECTION AND DATA EXTRACTION: Of 676 citations initially identified, sixty proved potentially eligible, of which four published and five unpublished randomized trials met all eligibility criteria. Each of three investigators assessed study quality and abstracted relevant data. RESULTS: The pooled relative risk of reamed versus nonreamed nails (nine trials, n = 646 patients) was 0.33 [95% confidence interval (CI), 0.16 to 0.68; p = 0.004]. The absolute risk difference in nonunion rates with reamed IM nailing was 7.0 percent (95% CI, 1 to 11 percent). Thus, one nonunion could be prevented for every fourteen patients treated with reamed IM nailing [number needed to treat (NNT) = 14.28]. The risk ratios for secondary outcome measures were: implant failure, 0.30 (95% CI, 0.16 to 0.58; p < 0.001); malunion, 1.06 (95% CI, 0.32 to 3.57); pulmonary embolus, 1.10 (95% CI, 0.26 to 4.76); compartment syndrome, 0.45 (95% CI, 0.13 to 1.56); and infection, 0.98 (95% CI, 0.21 to 4.76). Sensitivity analyses suggested that reported rates of nonunion and implant failure were higher in studies of lower quality. The type of long bone fractured (tibia or femur), the degree of soft tissue injury (open or closed), study quality, and whether a study was published or unpublished did not significantly alter the relative risk of nonunion between reamed and nonreamed IM nailing. CONCLUSIONS: There is evidence from a pooled analysis of randomized trials that reamed IM nailing of lower extremity long bone fractures significantly reduces rates of nonunion and implant failure in comparison with nonreamed nailing.
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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 | 0.021 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.032 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".