Efficacy and Safety of Posterior Long-Segment Fixation Versus Posterior Short-Segment Fixation for Kummell Disease: A Meta-Analysis
Bibliographic record
Abstract
Purpose Posterior short-segment fixation (SSF) and long-segment fixation (LSF) are two methods for the treatment of Kummell disease, but the safety and effectiveness of these two surgical methods still lack adequate medical evidence. This study aimed to evaluate the two methods. Methods Database searches for randomized controlled trials, case-control studies, and cohort studies of posterior SSF and posterior LSF in the treatment of Kummell disease were performed. After the document quality was evaluated with the Newcastle-Ottawa Quality Assessment Scale, a meta-analysis was carried out. Results Meta-analysis revealed that the operation time and intraoperative blood loss in the LSF group were higher than those in the SSF group [MD = −18.17, 95% CI (−30.31, −6.03), z = 2.93, P = .003; MD = −82.07, 95% CI (−106.91, −57.24], z = 6.48, P < .00001). The postoperative last follow-up local kyphosis angle in the SSF group was greater than that in the LSF group (MD = 3.18, 95% CI [.56, 5.81], z = 2.38, P = .02), and there were no significant differences in perioperative complications, bone cement leakage rate, incidence of adverse events during follow-up, postoperative follow-up visual analog scale, postoperative Oswestry dysfunction index, and postoperative immediate local kyphosis angle between the two groups ( P > .05). Conclusion SSF and LSF are effective and safe for the treatment of Kummell disease. SSF can reduce the operation time and intraoperative bleeding; LSF can better maintain the long-term stability of kyphosis. The methods should be evaluated by clinicians according to the individual situation of the 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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.050 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".