Relationship of causative organism and time to infection among children with cerebrospinal fluid shunt infection
Bibliographic record
Abstract
OBJECTIVE: Infection is a common complication of cerebrospinal fluid (CSF) shunts, occurring in 6%-20% of children. Although studies are limited, Staphylococcus aureus is thought to cause more rapid and aggressive infection than coagulase-negative Staphylococcus (CONS) or gram-negative organisms. The authors' objective was to evaluate the relationship between the causative organisms of CSF shunt infection and the timing of infection. METHODS: The authors performed a retrospective cohort study of children who underwent CSF shunt placement at a tertiary care children's hospital over a 9-year period and subsequently developed a CSF shunt infection. The primary predictor variable was the causative organism recovered from CSF culture, characterized as S. aureus, CONS, or gram-negative organisms. The primary outcome was time to infection, defined as the number of days from most recent shunt intervention to the diagnosis of the infection. The association between causative organism and time to infection was visualized using Kaplan-Meier curves, and statistical comparisons were made using nonparametric Kruskal-Wallis tests. RESULTS: Among 103 children in whom a CSF shunt infection developed, the causative organism was CONS in 57 (55%), S. aureus in 19 (18%), and gram-negative organisms in 9 (9%). The median time to infection did not differ (p = 0.81) for infections caused by CONS (20 days, IQR 11-40), S. aureus (26 days, IQR 12-95), and gram-negative organisms (23 days, IQR 17-34). CONCLUSIONS: No significant difference in time to infection based on the causative organism was observed among children with a CSF shunt infection.
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 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".