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Record W4415306615 · doi:10.3171/2025.7.peds25208

Effect of a recommended shunt infection prevention protocol on perioperative practices and infection rates in the Hydrocephalus Clinical Research Network–Quality

2025· article· en· W4415306615 on OpenAlexaff
Mandeep S. Tamber, Hailey Jensen, Ron Reeder, Jason Clawson, Nichol Nunn, John R. W. Kestle

Bibliographic record

VenueJournal of Neurosurgery Pediatrics · 2025
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPerioperativeHydrocephalusInfection controlShunt (medical)Protocol (science)Clinical researchRisk of infectionInfection rate

Abstract

fetched live from OpenAlex

OBJECTIVE: The Hydrocephalus Clinical Research Network-Quality (HCRNq) was established to encourage adoption of evidence-based best practices for the care of children with hydrocephalus. A shunt infection prevention initiative is ongoing within the network, and an analysis of baseline data suggested important practice variation with respect to shunt infection prevention practices. In a first attempt to standardize care, the authors recommended adoption of an endorsed shunt infection prevention protocol within the network, and now present information related to protocol adoption, compliance, and its effect on shunt infection rates. METHODS: A memorandum was circulated to HCRNq sites endorsing and recommending adoption of a 7-step shunt infection prevention protocol. Patient and procedural data relevant to shunt surgery and infection prevention were then prospectively collected from 31 network sites. The relationship between the infection outcome and patient and procedural variables, including protocol adoption, was modeled using uni- and multivariable statistics. RESULTS: An unadjusted infection rate of 3.6% was observed over nearly 3500 shunt procedures, similar to what was observed at baseline, but with a narrower range, suggesting that some outlying sites were brought closer to the network average. An increased infection risk was associated with shunt placement for preterm posthemorrhagic hydrocephalus, the occurrence of prior shunt surgery within 6 months of the index procedure, and the use of antibiotic ointment. A reduced infection risk with the use of antibiotic-impregnated catheters was suggested. Adoption of the recommended protocol was modest, and as a result, significant practice variation continued to be observed. In this analysis, no relationship was observed between infection risk and the use of an infection prevention protocol. CONCLUSIONS: This first attempt to encourage standardization of perioperative practices for shunt infection prevention, by endorsing an evidence-based shunt infection prevention protocol for use at network sites, resulted in incremental protocol adoption. Many shunt procedures continue to occur without the cover of a protocol. Although adherence to a protocol did not appear to influence infection risk in the present analysis, an opportunity to improve remains, with a potential beneficial effect on infection rates to follow. The authors continue to work toward further improvement in this regard.

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 imitation

Not 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.

metaresearch head score (Codex)0.178
metaresearch head score (Gemma)0.442
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.940

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1780.442
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.165
GPT teacher head0.513
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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