Three-dimensional printing combined with open reduction and internal fixation versus open reduction and internal fixation in the treatment of acetabular fractures: A systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: This meta-analysis compared the clinical outcome of three-dimensional (3D) printing combined with open reduction and internal fixation (ORIF) to traditional ORIF in the treatment of acetabular fractures. METHODS: We searched the Cochrane Library, PubMed, Embase, VIP database, CNKI, and Wanfang database with keywords "acetabular fracture", "3D printing", "three-dimensional printing", "open reduction and internal fixation", "Acetabulum", "Acetabula" from January 2000 to March 2020. Two reviewers independently selected articles, extracted data, assessed the quality evidence and risk bias of included trials using the Cochrane Collaboration' s tools and/or Newcastle-Ottawa scale. When the two analysts had different opinions, they would ask the third analyst for opinion. Randomized controlled trials or retrospective comparative studies of 3D printing combined with ORIF (3D printing group) versus traditional ORIF (conventional group) in the treatment of acetabular fractures were selected. The data of operation time, intraoperative blood loss, intraoperative fluoroscopy times, incidence of complications, excellent and good rate of Matta score for reduction, and excellent and good rate of hip function score were extracted. Stata14.0 statistical software was used for data analysis. RESULTS: Altogether 9 articles were selected, including 5 randomized controlled trials and 4 retrospective studies. A total of 467 patients were analyzed, 250 in the conventional group, and 217 in the 3D printing group. The operation time in the 3D printing group was less than that in the conventional group and the difference was statistically significant (standardized mean difference (SMD) = -1.19, 95% CI: -1.55 to -0.82, p < 0.05). The intraoperative bleeding volume of the 3D printing group was significantly lower than that of the conventional group (SMD = -1.08, 95% CI: -1.65 to -0.51, p < 0.05). The fluoroscopy times were less in the 3D printing group than in the conventional group and the difference was statistically significant (SMD = -1.64, 95% CI: -2.35 to -0.93, p < 0.05). The total incidence of complications in the 3D printing group was significantly lower than that in the conventional group (OR = 0.43, 95% CI: 0.24-0.79, p < 0.05). There was no significant difference in the excellent and good rate of Matta score for reduction between the two groups (OR = 0.60, 95% CI: 0.34-1.06, p > 0.05). There was no significant difference in the excellent and good rate of hip function score at the end of postoperative follow-up between the two groups (OR = 0.84, 95% CI: 0.46-1.56, p > 0.05), but the follow-up time varies from 6 months to 40 months. CONCLUSION: Compared with traditional ORIF, 3D printing combined with ORIF has certain advantages in terms that 3D printing not only helps surgeons to understand acetabular fractures more intuitively, but also effectively reduces operation time, intraoperative blood loss, intraoperative fluoroscopy times, and postoperative complications. However, there were no significant differences in the excellent and good rate of Matta score for reduction and the excellent and good rate of hip function score at the end of follow-up.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.046 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 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".