C.07 Calgary shunt protocol, an adaptation of the hydrocephalus clinical research network shunt protocol reduces risk of shunt infection in children
Bibliographic record
Abstract
Background: The effectiveness of the Hydrocephalus Research Network (HCRN) shunt protocol has not been validated in a non-HCRN, small-to-medium volume pediatric neurosurgery center. This study evaluates whether the 9-step Calgary Shunt Protocol (CSP) adapted from the HCRN shunt protocol reduced shunt infections. Methods: The CSP was prospectively applied at Alberta Children’s Hospital from May 23rd, 2013 to all children undergoing any shunt procedure. Children undergoing shunt surgery before CSP implementation acted as a control-cohort. The strict HCRN definition of shunt infection was applied. Results: A total of 268 shunt procedures were performed. There was a significant absolute risk reduction of 10.0% ([95%CI 3.9%-15.9%], p=0.004) in shunt infections after implementation of the CSP. In univariate analyses, chlorhexidine compared to povidone skin prep reduced shunt infection by 8.2% ([95%CI 1.84-14.6%], p=0.02) and waiting ≥ 20 min between receiving preoperative antibiotics and skin incision reduced shunt infections by 9.6% ([95%CI 2.4%-16.9%], p=0.02). In multivariate analysis, only protocol implementation independently reduced shunt infections (OR 0.19 [95%CI 0.06-0.67], p=0.004). Conclusions: This study externally validates the published HCRN protocol for reducing shunt infection in an independent, non-HCRN, and small-to-medium volume neurosurgery setting. Chlorhexidine skin prep and waiting ≥ 20 min between preoperative antibiotic and skin incision may have contributed to the protocol’s quality improvement success.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".