Repeat Cerebrospinal Fluid Shunt Infection in Children
Bibliographic record
Abstract
BACKGROUND: In this study, we investigated the treatment of cerebrospinal fluid (CSF) shunt infection and the risk factors for repeat shunt infection (RSI) in a cohort of children treated at the Hospital for Sick Children, Toronto, Canada. METHODS: Between 1996 and 2000, a total of 51 children were identified with shunt infection (mean age 5.8 years). The medical records of these children were reviewed to identify cases of RSI within 6 months of the initial shunt infection (ISI). RESULTS: In the 51 ISIs, the infecting organisms were coagulase-negative Staphylococcus (43.1%), Staphylococcus aureus (37.3%) and others (19.6%). The initial mode of treatment of the shunt infection was using an external ventricular drain (EVD) with removal of the shunt apparatus (54.9%), externalization of the shunt (37.3%) or shunt removal only (7.8%). The mean number of days of external CSF drainage (either EVD or externalized shunt) was 11.2 days. Ten patients (19.6%) developed RSI. The actuarial risk of RSI plateaued after 90 days at 24.4%. The following variables were tested as risk factors for RSI using survival analysis, although none reached statistical significance: initial organism (p = 0.09), age (p = 0.42), etiology of hydrocephalus (p = 0.45), number of days of CSF drainage (p = 0.45), type of surgical treatment of the ISI (p = 0.58) and the presence of bacteriologically positive CSF at ISI (p = 0.85). CONCLUSIONS: The risk of RSI is substantial and greater effort needs to be directed towards understanding the risk factors. Such studies will need a greater sample size in order to obtain sufficient statistical power.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".