Best Practice Guidelines for Surgical Site Infection in High-risk Pediatric Spine Surgery: Definition, Prevention, Diagnosis, and Treatment
Bibliographic record
Abstract
BACKGROUND: Prior "best practice guidelines" (BPG) have identified strategies to reduce the risk of acute deep surgical site infection (SSI), but there still exists large variability in practice. Further, there is still no consensus on which patients are "high risk" for SSI and how SSI should be diagnosed or treated in pediatric spine surgery. We sought to develop an updated, consensus-based BPG informed by available literature and expert opinion on defining high-SSI risk in pediatric spine surgery and on prevention, diagnosis, and treatment of SSI in this high-risk population. MATERIALS AND METHODS: After a systematic review of the literature, an expert panel of 21 pediatric spine surgeons was selected from the Harms Study Group based on extensive experience in the field of pediatric spine surgery. Using the Delphi process and iterative survey rounds, the expert panel was surveyed for current practices, presented with the systematic review, given the opportunity to voice opinions through a live discussion session and asked to vote regarding preferences privately. Two survey rounds were conducted electronically, after which a live conference was held to present and discuss results. A final electronic survey was then conducted for final voting. Agreement ≥70% was considered consensus. Items near consensus were revised if feasible to achieve consensus in subsequent surveys. RESULTS: Consensus was reached for 17 items for defining high-SSI risk, 17 items for preventing, 6 for diagnosing, and 9 for treating SSI in this high-risk population. After final voting, all 21 experts agreed to the publication and implementation of these items in their practice. CONCLUSIONS: We present a set of updated consensus-based BPGs for defining high-risk and preventing, diagnosing, and treating SSI in high-risk pediatric spine surgery. We believe that this BPG can limit variability in practice and decrease the incidence of SSI in pediatric spine surgery. LEVEL OF EVIDENCE: Not applicable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.078 | 0.220 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.016 | 0.009 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".