Associations of Standard Care, Intrathecal Antibiotics, and Antibiotic-Impregnated Catheters With Cerebrospinal Fluid Shunt Infection Organisms and Resistance
Bibliographic record
Abstract
BACKGROUND: Infection prevention techniques used during cerebrospinal fluid (CSF) shunt surgery include: (1) standard perioperative intravenous antibiotics, (2) intrathecal (IT) antibiotics, (3) antibiotic-impregnated catheter (AIC) shunt tubing, or (4) Both IT and AIC. These techniques have not been assessed against one another for their impact on the infecting organisms and patterns of antimicrobial resistance. METHODS: We performed a retrospective longitudinal observational cohort study of children with initial CSF shunt placement between January 2007 and December 2012 at 6 US hospitals. Data were collected electronically from the Pediatric Health Information Systems+ (PHIS+) database, and augmented with standardized chart review. Only subjects with positive CSF cultures were included in this study. RESULTS: Of 1,723 children whose initial shunt placement occurred during the study period, 196 (11%) developed infection, with 157 (80%) having positive CSF cultures. Of these 157 subjects, 69 (44%) received standard care, 28 (18%) received AIC, 55 (35%) received IT antibiotics, and 5 (3%) received Both at the preceding surgery. The most common organisms involved in monomicrobial infections were Staphylococcus aureus (38, 24%), coagulase-negative staphylococci (36, 23%), and Cutibacterium acnes (6, 4%). Compared with standard care, the other infection prevention techniques were not significantly associated with changes to infecting organisms; AIC was associated with decreased odds of methicillin resistance among coagulase-negative staphylococci. CONCLUSIONS: Because no association was found between infection prevention technique and infecting organisms when compared to standard care, other considerations such as tolerability, availability, and cost should inform decisions about infection prevention during CSF shunt placement surgery.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".