The efficacy and safety of anterior versus posterior approach for the treatment of thoracolumbar burst fractures: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: There has always been controversy about the choice of anterior approach or posterior approach for the surgical approach of thoracolumbar burst fractures (TBFs). The aim of this study was to systematically evaluate the efficacy and safety of anterior and posterior approaches in the treatment of TBFs. Methods: Multiple databases including PubMed, Excerpt Medica Database (Embase), Cochrane Library, and Web of Science (WOS) were used to search for relevant studies, namely full-text articles comparing the anterior versus posterior approach for the treatment of TBFs, which based on population, intervention, control, outcome, and study (PICOS) framework. Review Manager 5.4 was used to assess the effects of the results among selected studies. The risk of bias of the trials was assessed using the Newcastle Ottawa scale (NOS) and the Cochrane Collaboration's tool. Forest plots and funnel plots were also generated for the included articles. Results: Finally, 723 patients were included in 13 studies which satisfied the eligibility criteria, funnel plots and Egger's test showed that there was no significant bias in the publications. There were no differences in terms of length of stay [mean difference (MD): -1.31, (-5.31, 2.69); P=0.52], hospitalization expenses [standardized mean difference (SMD): 1.26, (-0.38, 2.89); P=0.13], and return to work between the anterior approach and posterior approach. However, the posterior approach had the advantages of better Cobb angle correction [MD: 2.06, (0.17, 3.94); P=0.03], shorter operation time [MD: 58.29, (35.39, 81.18); P<0.00001], and lower estimated blood loss [MD: 185.92, (131.76, 240.07); P<0.00001]. Discussion: The posterior approach appeared to be superior to the anterior approach in the treatment of TBFs. However, more high-quality randomized controlled trials should be conducted to confirm the conclusions of this study and guide clinical decision-making.
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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 | 0.019 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.023 | 0.039 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".