MASTERS-D: Final Results of a Prospective Multicenter Observational Data-Monitored Study of Minimally Invasive Fusion to Treat Degenerative Lumbar Disorders
Bibliographic record
Abstract
Introduction Evaluation of 1- or 2-level minimally invasive posterior lumbar interbody fusion (MILIF) for degenerative lumbar (DL) disorders in a multicenter 1-year prospective observational study (NCT01143324). Material and Methods A total of 252 patients (56% female patients, mean age: 54 years, mean BMI: 28, mean duration of symptoms: 29 months [m]) enrolled by 19 centers in 14 countries underwent 1- (83%) or 2-level (17%) MILIF (TLIF: 95%; PLIF: 5%) for treatment of leg pain (52%), back pain (39%), or claudication (9%) due to DL pathologies, including spondylolisthesis (53%), stenosis (71%), and/or disc pathology (94%). Participating surgeons were required to have a minimum prestudy experience of 30 MILIF cases. A total of 15.1% of patients had previous decompression surgery at the target level. Patient demographics, intraoperative data, complications, time to first ambulation, time to study-defined recovery, surgical duration, blood loss, fluoroscopy time, and adverse events (AEs) were recorded. Outcome scores (VAS back and leg, ODI, EQ-5D) were assessed preoperatively and at defined time points through 12 m postoperatively. Results Available for the follow-up: 249 (99%) patients at 4 weeks (w) and 233 (92.5%) at 12 m. One-level surgery occurred at L4–5 or L5–S1 in 91% and 2-level surgery at L4–S1 in 74%. Mean surgical duration, blood loss, and intraoperative fluoro-time were 128 versus 182 minutes, 164 versus 233 mL, and 115 versus 154 seconds in 1- and 2-level cases, respectively. The mean time to first ambulation was 1.3 days and time to study-defined recovery was 3.2 days. Mean preoperative VAS back (6.2) and VAS leg (5.9) scores dropped significantly ( p < .0001) to 3.1 (2.9) and 1.9 (2.5) at discharge (4 w), respectively. VAS improvement was sustained between 4 w and final follow-up at 12 m. Fusion rates: 90.8% fusion in 1- and 90.7% for 2-level procedures (141 and 27 patients evaluated, respectively). Preoperative ODI (45.5%) and EQ-VAS (52.9) changed to 34.5% (22.4%) and 65.4 (71.0) at 4 w (12 m) ( p < 0.0001). There was a constant improvement in EQ-5D subscales and reduction of pain medication from 4 w to 12 m. A total of 50 AEs in 39 patients (15.5%) were attributed to surgery, approach, or device (including 9 AEs in 8 patients), out of which 3 AEs in 3 patients (1.2%) were due to the minimally invasive approach (including 1 SAE); no deep surgical site infections and 7 reoperations occurred. Conclusion This is the largest data-monitored prospective multicenter observational study of MILIF to date, following routine local standard of practice and providing objective results for this procedure. MILIF demonstrated favorable clinical results with early and sustained improvement in patient-reported outcomes and low major perioperative morbidity.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".