Use of incisional vacuum-assisted closure in the prevention of postoperative infection in high-risk patients who underwent spine surgery: a proof-of-concept study
Bibliographic record
Abstract
OBJECTIVE: This proof-of-concept study was conducted to determine whether negative-pressure wound therapy, through the use of incisional vacuum-assisted closure (VAC), is associated with a reduction in surgical site infections (SSIs) when compared to standard wound dressings in patients undergoing open posterior spinal fusion who have a high risk of infection. METHODS: A total of 64 patients were examined; 21 patients received incisional VAC application (VAC group) versus 43 diagnosis-matched patients who received standard wound dressings (control group). Patients in the VAC group were prospectively enrolled in a consecutive series between March 2013 and March 2014 if they met the following diagnostic criteria for high risk of infection: posterior open surgery across the cervicothoracic junction; thoracic kyphosis due to metastatic disease; high-energy trauma; or multilevel revision reconstructive surgery. Patients in the VAC group also met one or more comorbidity criteria, including body mass index ≥ 35 or < 18.5, diabetes, previous radiation at surgical site, chemotherapy, steroid use, bedridden state, large traumatic soft-tissue disruption, or immunocompromised state. Consecutive patients in the control group were retrospectively selected from the previous year by the same high-risk infection diagnostic criteria as the VAC group. All surgeries were conducted by the same surgeon at a single site. The primary outcome was SSI. All patients had 1 year of follow-up after their surgery. Baseline demographics, intraoperative parameters, and postoperative wound infection rates were compared between groups. RESULTS: Patient demographics including underlying comorbidities were similar, with the exception that VAC-treated patients were malnourished (p = 0.020). VAC-treated patients underwent longer surgeries (p < 0.001) and required more postoperative ICU admissions (p = 0.039). The median length of hospital stay was not different between groups. In total, 9 control patients (21%) developed an SSI, versus 2 VAC-treated patients (10%). CONCLUSIONS: Patients in this cohort were selected to have an increased risk of infection; accordingly, the rate of SSI was high. However, negative-pressure wound therapy through VAC application to the postoperative incision resulted in a 50% reduction in SSI. No adverse effects were noted secondary to VAC application. The preliminary data confirm the authors' proof of concept and strongly support the need for a prospective randomized trial.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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".