A new Hydrocephalus Clinical Research Network protocol to reduce cerebrospinal fluid shunt infection
Bibliographic record
Abstract
OBJECT In a previous report by the same research group (Kestle et al., 2011), compliance with an 11-step protocol was shown to reduce CSF shunt infection at Hydrocephalus Clinical Research Network (HCRN) centers (from 8.7% to 5.7%). Antibiotic-impregnated catheters (AICs) were not part of the protocol but were used off protocol by some surgeons. The authors therefore began using a new protocol that included AICs in an effort to reduce the infection rate further. METHODS The new protocol was implemented at HCRN centers on January 1, 2012, for all shunt procedures (excluding external ventricular drains [EVDs], ventricular reservoirs, and subgaleal shunts). Procedures performed up to September 30, 2013, were included (21 months). Compliance with the protocol and outcome events up to March 30, 2014, were recorded. The definition of infection was unchanged from the authors' previous report. RESULTS A total of 1935 procedures were performed on 1670 patients at 8 HCRN centers. The overall infection rate was 6.0% (95% CI 5.1%-7.2%). Procedure-specific infection rates varied (insertion 5.0%, revision 5.4%, insertion after EVD 8.3%, and insertion after treatment of infection 12.6%). Full compliance with the protocol occurred in 77% of procedures. The infection rate was 5.0% after compliant procedures and 8.7% after noncompliant procedures (p = 0.005). The infection rate when using this new protocol (6.0%, 95% CI 5.1%-7.2%) was similar to the infection rate observed using the authors' old protocol (5.7%, 95% CI 4.6%-7.0%). CONCLUSIONS CSF shunt procedures performed in compliance with a new infection prevention protocol at HCRN centers had a lower infection rate than noncompliant procedures. Implementation of the new protocol (including AICs) was associated with a 6.0% infection rate, similar to the infection rate of 5.7% from the authors' previously reported protocol. Based on the current data, the role of AICs compared with other infection prevention measures is unclear.
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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 | 0.080 | 0.122 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
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".