Is There an Association of Epidural Corticosteroid Injection With Postoperative Surgical Site Infection After Surgery for Lumbar Degenerative Spine Disease?
Bibliographic record
Abstract
STUDY DESIGN: Retrospective study. OBJECTIVE: To assess the relation between exposure to epidural steroid injection (ESI) before surgery and occurrence of surgical site infection (SSI) for degenerative lumbar spine conditions. SUMMARY OF BACKGROUND DATA: The effect of local ESI on the occurrence of SSI is controversial. METHODS: Patients who underwent surgery for degenerative lumbar spine conditions at two centers between 2005 and 2015 were identified. Primary outcome measure was SSI within 90 days requiring surgical intervention. RESULTS: A total of 5311 patients (age 57 ± 16 years) were analyzed of which 945 (18%) had at least one ESI within 90 days of surgery. One hundred thirty-four (2.5%) patients developed an SSI requiring reoperation. No association of exposure or dose-response relationship was identified between ESI and SSI for any of the time periods (90-, 30-, and 30-90-day). Five (1.7%) of the 290 patients who had at least one ESI within 30 days before surgery had a postoperative infection compared to 129 (2.6%) of the 5021 in the non-ESI group (unadjusted odds ratio: 0.67, 95% CI: 0.27-1.64, P = 0.376). Fifteen (2.0%) of the 761 patients who had at least one ESI within 30 to 90 days before surgery had a postoperative infection, compared to 119 (2.6%) of the 4550 in the non-ESI group (unadjusted odds ratio: 0.75, 95% CI: 0.44-1.29, P = 0.296). CONCLUSION: In this retrospective study we investigated whether an ESI and its timing influences the postoperative risk of an SSI. We found no association-exposure or dose-response relationship-between ESI and postoperative infection, even after adjusting for potential confounders, for any of the time periods (90-, 30-, and 30-90-day ESI). In addition, we did find that longer hospital stay, greater EBL, posterior approach, and drain placement were associated with higher infection rates.Level of Evidence: 3.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".