Minimally Invasive Transforaminal Lumbar Interbody Fusion
Bibliographic record
Abstract
In Brief Study Design. Review of published literature. Objective. To review the available medical literature reporting results after minimally invasive transforaminal lumbar interbody fusion (MIS TLIF) and evaluate functional and radiographic outcomes with those following open TLIF and open posterior lumbar interbody fusion (PLIF) procedures. Summary of Background Data. Minimally invasive spine techniques aim to reduce approach-related surgical morbidity without compromising operative and clinical outcomes. MIS TLIF is increasingly being used for the management of various lumbar degenerative diseases. Despite the limited number of well-designed clinical studies, the available published data suggest potential advantages over its open posterior-approach lumbar interbody fusion counterparts. Such benefits include less intraoperative blood loss, less need for blood transfusions, shorter hospital course, and less postoperative pain. Methods. Literature examining posterior-approach interbody fusion techniques (PLIF, TLIF, and MIS TLIF) was collected using the National Center for Biotechnology Information database and PubMed/MEDLINE, and summarized for discussion. Results. Literature reports of MIS TLIF generally show comparable or improved clinical outcomes when compared with those following open posterior interbody fusion techniques. Additionally, significantly less blood loss, hospital stay, and complications were generally reported, despite slightly longer duration of surgery, especially during early cases in a surgeon's experience. Conclusion. More studies designed to provide class I or II data will be needed in the future to further solidify the favorable results observed so far with the MIS TLIF procedure. Minimally invasive transforaminal lumbar interbody fusion procedure is increasingly being used for the management of various lumbar degenerative diseases. Minimally invasive transforaminal lumbar interbody fusion has significant benefits such as less intraoperative blood loss and postoperative pain. However, more studies are needed to further elucidate its potential clinical benefits.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".