The Hydrocephalus Clinical Research Network quality improvement initiative: the role of antibiotic-impregnated catheters and vancomycin wound irrigation
Bibliographic record
Abstract
OBJECTIVE: Two previous Hydrocephalus Clinical Research Network (HCRN) studies have demonstrated that compliance with a standardized CSF shunt infection protocol reduces shunt infections. In this third iteration, a simplified protocol consisting of 5 steps was implemented. This analysis provides an updated evaluation of protocol compliance and evaluates modifiable shunt infection risk factors. METHODS: The new simplified protocol was implemented at HCRN centers on November 1, 2016, for all shunt procedures, excluding external ventricular drains, ventricular reservoirs, and subgaleal shunts. Procedures performed through December 31, 2019, were included (38 months). Compliance with the protocol, use of antibiotic-impregnated catheters (AICs), and other variables of interest were collected at the index operation. Outcome events for a minimum of 6 months postoperatively were recorded. The definition of infection was unchanged from the authors' previous report. RESULTS: A total of 4913 procedures were performed at 13 HCRN centers. The overall infection rate was 5.1%. Surgeons were compliant with all 5 steps of the protocol in 79.4% of procedures. The infection rate for the protocol alone was 8.1% and dropped to 4.9% when AICs were added. Multivariate analysis identified having ≥ 2 complex chronic conditions (odds ratio [OR] 1.76, 95% confidence interval [CI] 1.26-2.44, p = 0.01) and a history of prior shunt surgery within 12 weeks (OR 1.84, 95% CI 1.37-2.47, p < 0.01) as independent risk factors for shunt infection. The use of AICs (OR 0.70, 95% CI 0.50-0.97, p = 0.05) and vancomycin irrigation (OR 0.36, 95% CI 0.21-0.62, p < 0.01) were identified as independent factors protective against shunt infection. CONCLUSIONS: The authors report the third iteration of their quality improvement protocol to reduce the risk of shunt infection. Compliance with the protocol was high. These updated data suggest that the incorporation of AICs is an important, modifiable infection prevention measure. Vancomycin irrigation was also identified as a protective factor but requires further study to better understand its role in preventing shunt infection.
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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 | 0.187 | 0.226 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".