Minimally Invasive Transforaminal Interbody Fusion Versus Microdiscectomy Without Fusion for Recurrent Lumbar Disk Herniation: A Prospective Comparative Study
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to compare the clinical outcome of minimally invasive transforaminal lumbar interbody fusion (MIS TLIF) versus standard revision diskectomy for recurrent lumbar disk herniation (RLDH). BACKGROUND: RLDH is the most common cause of redo surgery after a microdiscectomy. Commonly, in patients without evidence of spinal instability, many surgeons would simply redo microdiscectomy, while others proceed to a redo microdiscectomy with arthrodesis. According to the literature, there is no evidence of what the best management of an RLDH would be. METHODS: This study involved 90 patients who underwent lumbar microdiscectomy in the past and were now experiencing a new lumbar disk herniation for the first time. The patients were divided into two groups, each with 45 patients: group A received standard revision microdiscectomy, whereas group B received revision microdiscectomy with MIS TLIF.The Japanese Orthopaedic Association score, operating time, blood loss, duration of hospital stay, costs, and complications were all prospectively recorded in a database and examined. Back and leg discomfort were measured using the visual analog scale. RESULTS: The mean total postoperative Japanese Orthopaedic Association score across the groups exhibited no statistically significant difference, nor did the preoperative clinical and epidemiological data. Although postoperative leg pain was comparable in both groups, postoperative lower back pain in group A was much worse than that in group B. Additional revision surgery was necessary for six individuals in group A. Group A had higher rates of dural rupture and postoperative neurological impairment. Group A experienced much less intraoperative blood loss, longer operation times, and postoperative hospital stays. CONCLUSION: In patients with RLDH, revision microdiscectomy is effective. In comparison with conventional microdiscectomy, MIS TLIF reduces intraoperative risk of dural rupture or neural injury, postoperative incidence of mechanical instability or recurrence, and postoperative lower back pain. STUDY DESIGN: Prospective, randomized, multicenter, comparative study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".