Lateral Lumbar Interbody Fusion With rhBMP-2 can Achieve High Fusion Rates in Adult Spine Deformity Surgeries
Bibliographic record
Abstract
STUDY DESIGN: An ambispective, observational study of the prospective, institutional adult spine deformity (ASD) database. OBJECTIVES: The study investigates the clinical and radiographic fusion rates with lateral interbody approach and rhBMP-2 in multiple-level lumbar fusion in the ASD population. Previous studies have reported over 10% pseudoarthrosis rate with multiple segment fusions. Lateral lumbar interbody fusion (LLIF) allows multiple-level, less-invasive access to the anterior lumbar spine. We hypothesized that fusion rates with lateral approach with rhBMP-2 use are superior to the published data on lumbar fusion in ASD patients. METHODS: The institutional ASD database was searched to identify eligible patients with two or more levels of LLIF (T12-L5), >4 levels of posterior instrumentations and >2 years of follow-up between the years 2010 and 2018. Antero-posterior and lateral 36-inch standing radiographs for each patient and computed tomography scans in select patients were studied to ascertain fusion status and patients were divided into two groups based on fusion status. RESULTS: The study included 179 patients with a mean age of 65.3 years and 74% female patients. The median number of interbody fusions was performed at 3 (IQR 3-4) levels. The mean follow-up duration was 4.4 years (SD = 1.9). 169 patients (94.5%) had successful arthrodesis, while 10 patients (5.5%) had radiological pseudoarthrosis at one level. Of the 10 patients, 8 (4.4%) were either clinically asymptomatic or had manageable back pain. Two patients (1.1%) required revision surgery for symptomatic pseudoarthrosis. CONCLUSION: This is the largest known series of ASD patients investigating the fusion rates with multiple-level LLIFs. LLIF along with rhBMP-2 can achieve high fusion success across interbody fusion levels in multi-segmental ASD surgeries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".