Does open or closed reduction with internal fixation reduces the incidence of complications in neck of femur fractures in pediatrics: a meta-analysis and systematic review
Bibliographic record
Abstract
The neck of femur fracture (FNF) in children is a rare injury with a high incidence of complications such as avascular necrosis (AVN), coxa-vara and nonunion. The aim of this review is to compare the incidence of complications between open reduction with internal fixation (ORIF) and closed reduction with internal fixation (CRIF) of FNF in children. Two independent reviewers searched EMBASE, MEDLINE, COCHRANE and PUBMED databases from inception until April 2022 according to the preferred reporting items for systematic reviews and meta-analyses guidelines. Studies included comparison of complications between open and closed approaches with fixation of FNF in patients less than 18 years old. Publication bias was assessed using Egger's test while the Newcastle-Ottawa tool was used to assess the methodological quality of the studies. A total of 724 hip fractures from 15 included studies received either ORIF or CRIF. Overall, the rate of AVN was approximately 21.7% without statistical significance between both reduction methods [relative risk (RR) = 0.909, using fixed effect model at 95% confidence interval (CI, 0.678-1.217)]. No significant heterogeneity among AVN studies ( I2 = 3.79%, P = 0.409). Similarly, neither coxa-vara nor nonunion rates were statistically significant in both treatment groups (RR = 0.693 and RR = 0.506, respectively). Coxa-vara studies showed mild heterogeneity ( I2 = 27.8%, P = 0.218), while significant publication bias was encountered in nonunion studies ( P = 0.048). No significant difference in the incidence of AVN, coxa-vara and nonunion between ORIF or CRIF of FNF in children. High-quality studies as Randomised Controlled Trials can resolve the inconsistency and heterogeneity of other risk factors including age, initial displacement, fracture type, reduction quality and time to fixation.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.038 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".