Oblique lumbar interbody fusion versus minimally invasive transforaminal lumbar interbody fusion for the treatment of degenerative disease of the lumbar spine: a systematic review and meta-analysis
Bibliographic record
Abstract
This meta-analysis compared the efficacy of oblique lumbar interbody fusion (OLIF) and minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) in the treatment of lumbar degenerative diseases. A computer search for the published literature on OLIF and MIS-TLIF for the treatment of lumbar degenerative diseases in the PubMed, Web of Science, Embase, CINAHL, MEDLINE, Cochrane Library, and other databases was performed, from which 522 related articles were retrieved and 13 were finally included. Two reviewers independently extracted data from the included studies and analyzed them using RevMan 5.4. The quality of the studies was assessed using the Cochrane systematic analysis and the Newcastle-Ottawa scale. Meta-analysis showed that the blood loss [95% confidence intervals (CI) (- 121.01, - 54.56), [Formula: see text]], hospital stay [95% CI (- 1.98, - 0.85), [Formula: see text]], postoperative fusion rate [95%CI (1.04, 3.60), [Formula: see text]], postoperative disc height [95% CI (0.50, 3.63), [Formula: see text]], and postoperative foraminal height [95% CI (0.96, 4.13), [Formula: see text]] were all better in the OLIF group; however, the complication rates were significantly lower in the MIS-TLIF group [95% CI (1.01, 2.06), [Formula: see text]]. However, there were no significant differences between the two in terms of surgery time, patient satisfaction, or postoperative functional scores. The OLIF group had the advantages of lower blood loss, a shorter hospital stay, a higher postoperative fusion rate, and better recovery of the disc and foraminal heights, whereas MIS-TLIF had a relatively lower complication rate.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.044 |
| Bibliometrics | 0.005 | 0.005 |
| 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) | 0.003 | 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".