Effectiveness of Titanium Mesh Cylindrical Cages in Anterior Column Reconstruction After Thoracic and Lumbar Vertebral Body Resection
Bibliographic record
Abstract
STUDY DESIGN: A retrospective cohort study with cross-sectional outcome analysis of patients who underwent anterior column reconstruction with a titanium mesh cage after single-level or multilevel thoracic or lumbar vertebrectomy. OBJECTIVES: To radiographically evaluate the ability of titanium mesh cages to maintain alignment and facilitate osseous fusion after thoracolumbar vertebrectomy. Secondary objectives assessed complications and patient outcome. SUMMARY OF BACKGROUND DATA: Titanium mesh cages with cancellous autograft bone for postvertebrectomy reconstruction of the thoracolumbar spine avoid some of the potential problems associated with the acquisition or use of structural autograft or allograft. There is little in the literature that describes the efficacy or outcomes of using cylindrical mesh titanium cages for postvertebrectomy reconstruction. METHODS: The degree of kyphosis and the subsidence of the cage in relation to the vertebral endplates were measured in 43 of 57 (75%) patients available at a minimum of 2 years following titanium mesh cage reconstruction. Health-related quality of life and disability were assessed with various cross-sectional outcome measures. RESULTS: The average kyphosis of 25.4 degrees before surgery was reduced to 7.5 degrees immediately after surgery, and at final follow-up was measured to be 10.4 degrees. Cage subsidence averaged 0.28 and 0.20 cage fenestrations at the cephalad and caudal endplates, respectively. Osseous union (Grade 1 or 2) was identified in 93% of radiographs at the final follow-up. Thoracic reconstructions were significantly more likely to require surgical revision because of mechanical failure than thoracolumbar or lumbar reconstructions. CONCLUSION: The cylindrical mesh titanium cage is a successful adjunct in restoring and maintaining sagittal plane alignment after thoracolumbar vertebrectomy and, in this context, provides an effective method for anterior column reconstruction.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".