CT scan in children with acute bacterial meningitis: experience from emergency department of a tertiary-care hospital in Karachi, Pakistan.
Bibliographic record
Abstract
OBJECTIVE: To determine the role of computed tomography scan in children presenting to emergency department with symptoms and signs of suspected acute bacterial meningitis. METHODS: The retrospective analysis was done on children who were admitted through the Emergency Department at Aga Khan University Hospital, Karachi, from September 2009 to September 2011 with the diagnosis of acute bacterial meningitis. Information related to age, gender, presenting complaints, clinical signs and symptoms, computed tomography scan findings and final outcome of patients was gathered from the medical records. SPSS 19 was used for statistical analysis. RESULTS: A total of 192 patients were admitted with the relevant diagnosis. The male-female ratio was 2.3:1. Computed tomography scan was done in 114 (59.4%) patients. The scan was reported normal in 90 (78.94%) patients. However, cerebral oedema was found in 16 (14.03%) patients, cerebral infarct in 6(5.26%) and hydrocephalus in 2 (1.75%) patients. Overall, there were 6 (3.1%) deaths. CONCLUSION: Comuted tomography scan may have a beneficial role in children with acute bacterial meningitis. However, further studies are required to use the scan as a routine investigation for such a diagnosis.
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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 | 0.001 |
| 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".