Two-Year Clinical and Radiological Outcomes in Patients With Diabetes Undergoing Single-Level Anterior Cervical Discectomy and Fusion
Bibliographic record
Abstract
Study Design: Secondary analysis of data from the multicenter, randomized, parallel-controlled Food and Drug Administration (FDA) investigational device exemption study. Objective: Studies on outcomes following anterior cervical discectomy and fusion (ACDF) in individuals with diabetes are scarce. We compared 24-month radiological and clinical outcomes in individuals with and without diabetes undergoing single-level ACDF with either i-FACTOR or local autologous bone. Methods: Between 2006 and 2013, 319 individuals with single-level degenerative disc disease (DDD) and no previous fusion at the index level underwent ACDF. The presence of diabetes determined the 2 cohorts. Data collected included radiological fusion evaluation, neurological outcomes, Neck Disability Index (NDI), Visual Analog Scale (VAS) scores, and the 36-Item Short Form Survey Version 2 (SF-36v2) Physical and Mental component summary scores. Results: There were 35 individuals with diabetes (11.1%; average body mass index [BMI] = 32.99 kg/m 2 ; SD = 5.72) and 284 without (average BMI = 28.32 kg/m 2 ; SD = 5.67). The number of nondiabetic smokers was significantly higher than diabetic smokers: 73 (25.70%) and 3 (8.57%), respectively. Preoperative scores of NDI, VAS arm pain, and SF-36v2 were similar between the diabetic and nondiabetic participants at baseline; however, VAS neck pain differed significantly between the cohorts at baseline ( P = .0089). Maximum improvement for NDI, VAS neck and arm pain, and SF-36v2 PCS and MCS scores was seen at 6 months in both cohorts and remained stable until 24 months. Conclusions: ACDF is effective for cervical radiculopathy in patients with diabetes. Diabetes is not a contraindication for patients requiring single-level surgery for cervical DDD.
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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 | 0.000 |
| 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".