Anterior Cervical Infection: Presentation and Incidence of an Uncommon Postoperative Complication
Bibliographic record
Abstract
STUDY DESIGN: Retrospective multi-institutional case series. OBJECTIVE: The anterior cervical discectomy and fusion (ACDF) affords the surgeon the flexibility to treat a variety of cervical pathologies, with the majority being for degenerative and traumatic indications. Limited data in the literature describe the presentation and true incidence of postoperative surgical site infections. METHODS: A retrospective multicenter case series study was conducted involving 21 high-volume surgical centers from the AOSpine North America Clinical Research Network, selected for their excellence in spine care and clinical research infrastructure and experience. Medical records for 17 625 patients who received cervical spine surgery (levels from C2 to C7) between January 1, 2005, and December 31, 2011, inclusive, were reviewed to identify the occurrence of 21 predefined treatment complications. Patients who underwent an ACDF were identified in the database and reviewed for the occurrence of postoperative anterior cervical infections. RESULTS: A total of 8887 patients were identified from a retrospective database analysis of 21 centers providing data for postoperative anterior cervical infections (17/21, 81% response rate). A total of 6 postoperative infections after ACDF were identified for a mean rate of 0.07% (range 0% to 0.39%). The mean age of patients identified was 57.5 (SD = 11.6, 66.7% female). The mean body mass index was 22.02. Of the total infections, half were smokers (n = 3). Two patients presented with myelopathy, and 3 patients presented with radiculopathic-type complaints. The mean length of stay was 4.7 days. All patients were treated aggressively with surgery for management of this complication, with improvement in all patients. There were no mortalities. CONCLUSION: The incidence of postoperative infection in ACDF is exceedingly low. The management has historically been urgent irrigation and debridement of the surgical site. However, due to the rarity of this occurrence, guidance for management is limited to retrospective series.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".