A 20-Year Study of Intracranial Pyogenic Complications of Sinusitis in Children
Bibliographic record
Abstract
BACKGROUND: Intracranial pyogenic complications of sinusitis in children can lead to serious sequelae. We characterize the clinical, epidemiologic and microbiologic characteristics of children with such complications over a 20-year period. METHODS: Single-center retrospective chart review. Cases were identified based on International Classification of Diseases diagnostic codes (ICD)-9 and ICD-10 depending on the year and by reviewing all intracranial microbiologic samples. RESULTS: A total of 104 cases of complicated sinusitis were included after review of 1591 charts. Median age was 12 (IQR 9-14); 72 were male (69%). The most frequent complications were epidural empyema (n = 50, 48%), subdural empyema (n = 46, 44%) and Pott's puffy tumor (n = 27, 26%). 52% (n = 54) underwent neurosurgery and 46% (n = 48) underwent otolaryngologic surgery. The predominant pathogen isolated from sterile site specimens was Streptococcus anginosus (n = 40, 63%), but polymicrobial growth was common (n = 24; 38%). The median duration of intravenous antibiotic therapy was 51 days (IQR 42-80). Persistent neurologic sequelae (or death, n = 1) were found in 24% (n = 25) and were associated with the presence of cerebritis and extensive disease on neuroimaging ( P = 0.02 and P = 0.04, respectively). CONCLUSIONS: Intracranial complications of sinusitis continue to cause significant morbidity in children. Polymicrobial infections are common, which reinforces the need for broad-spectrum empiric antibiotic therapy and cautious adjustment of the antibiotic regimen based primarily on sterile site cultures. The association of neurologic sequelae with the presence of cerebritis and extensive intracranial involvement on neuroimaging suggest that delayed diagnosis may be a contributor to adverse outcome.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".