Risk Factors for Postoperative Subsidence of Single-Level Anterior Cervical Discectomy and Fusion
Bibliographic record
Abstract
STUDY DESIGN: Retrospective cohort study. OBJECTIVE: To investigate and analyze the preoperative risk factors affecting subsidence after anterior cervical discectomy and fusion (ACDF) to reduce subsidence. SUMMARY OF BACKGROUND DATA: Subsidence after ACDF may be caused by various risk factors, although the related information is scarce. METHODS: Seventy-eight patients who underwent single-level ACDF between 2005 and 2011 were included. Patients were categorized into the subsidence (n = 26) and nonsubsidence groups (n = 52). Preoperative factors such as age, sex, operative level, bone mineral density, cervical alignment, segmental sagittal angle, and anterior/posterior disc height were assessed. The use of plates and the anterior/posterior disc height gap were examined as perioperative factors. The clinical outcome was assessed using a visual analogue scale for neck and arm pain. RESULTS: Subsidence occurred in 26 (33.3%) of 78 patients. A significant difference was found in clinical outcomes between the subsidence and nonsubsidence groups (P < 0.05). The fusion rate was 61.5% in the subsidence group. The mean time to subsidence was 4.8 months. Logistic regression analysis revealed that cervical alignment (P = 0.017), age (P = 0.022), and use of plates (P = 0.041) affected subsidence. In patients who received a stand-alone cage, the risk of subsidence was significantly greater in the kyphotic angle group than in the lordotic angle group (odds ratio = 13.56; P < 0.001). CONCLUSION: After ACDF, the main factors affecting subsidence are cervical alignment, age, and use of plates. Our data suggest that surgeons should consider the kyphotic curvature and/or age when deciding on the use of plates.
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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) | 0.000 | 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".