The anterior and medial open approaches yield superior outcomes compared to the lateral and posterior open approaches in supracondylar humerus fractures in children: a systematic review and network meta-analysis
Bibliographic record
Abstract
This study aimed to perform a systematic review and network meta-analysis (NMA) to examine which open approach is superior in terms of outcomes and complications in the treatment of pediatric supracondylar humerus fractures. MEDLINE/PubMed, Embase, Web of Science, Clinicaltrials.gov , and Cochrane Library were searched from database inception to December 2022 and screened for relevant studies. Data were collected regarding patient demographics, Flynn's functional and cosmetic outcomes, and complications. Unsatisfactory Flynn's and complications were considered negative events. Comparisons of outcomes from aggregate data from each surgical approach using relative risk (RR) with a 95% confidence interval (95% CI) were performed. The NMA of overall negative events was conducted using a Bayesian hierarchical random-effects model analysis. A total of 26 studies involving 1461 patients were included; 459 (31.4%) patients underwent a closed reduction and percutaneous pinning (CRPP), 84 (5.7%) an anterior approach, 240 (16.4%) a medial, 220 (15%) a lateral, and 458 (31.3%) a posterior. The lateral and posterior approaches demonstrate a higher risk of negative event in the NMA compared to CRPP [RR = 2 (1.03, 3.85); RR = 2.63 (1.96, 3.57), respectively], anterior approach [RR = 3.33 (1.11, 10); RR = 4.35 (1.49, 12.5), respectively], and medial approach [RR = 1.82 (1.16, 2.86); RR = 2.38 (1.23, 4.76), respectively]. The medial approach resulted in a similar negative event rate compared to the anterior [RR = 1.82 (0.58, 5.88)]. The anterior and medial open approaches yield superior functional and cosmetic outcomes with fewer complications compared to the lateral and posterior.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.034 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".