Early versus late intramedullary nailing for traumatic femur fracture management: meta-analysis
Bibliographic record
Abstract
INTRODUCTION: There is no consensus yet on the impact of timing of femur fracture (FF) internal fixation on the patient outcomes. This meta-analysis was conducted to evaluate the contemporary data in patients with traumatic FF undergoing intramedullary nail fixation (IMN). METHODS: English language literature was searched with publication limits set from 1994 to 2016 using PubMed, Scopus, MEDLINE (OVID), EMBASE (OVID), Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL). Studies included randomized controlled trials (RCTs), prospective observational or retrospective cohort studies, and case-control studies comparing early versus late femoral shaft fractures IMN fixation. Variable times were used across studies to distinguish between early and late IMN, but 24 h was the most frequently used cutoff. The quality assessment of the reviewed studies was performed with two instruments. Observational studies were assessed with the Newcastle-Ottawa Quality Assessment Scale. RCTs were assessed with the Cochrane Risk of Bias Tool. RESULTS: We have searched 1151 references. Screening of titles and abstracts eliminated 1098 references. We retrieved 53 articles for full-text screening, 15 of which met study eligibility criteria. CONCLUSIONS: This meta-analysis addresses the utility of IMN in patients with FF based on the current evidence; however, the modality and timing to intervene remain controversial. While we find large pooled effects in favor of early IMN, for reasons discussed, we have little confidence in the effect estimate. Moreover, the available data do not fill all the gaps in this regard; therefore, a tailored algorithm for management of FF would be of value especially in polytrauma patients.
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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 | 0.022 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.057 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".