Unusual Acute Pediatric Pyelonephritis Presenting With Cluster Convulsions by Possible Central Nervous System Lesion: A Case Report
Bibliographic record
Abstract
Acute pyelonephritis is the leading cause of bacterial infection among children. It can be difficult to diagnose early in the disease course owing to non-specific symptoms and physical findings. Recently, some cases of pediatric acute pyelonephritis with mild encephalitis/encephalopathy with a reversible splenial lesion (MERS) have been reported. We describe a case of a six-year-old boy who presented with a high fever and four episodes of cluster convulsions. Despite the absence of leukocyturia and hypo-inflammatory response in the blood, he was diagnosed with acute pyelonephritis by contrast-enhanced computed tomography seven days after onset. The convulsions were not simple febrile convulsions and suggested central nervous system (CNS) lesions, as the patient was older than the usual cut-off age of five years for febrile seizures. This case highlights an unusual presentation and clinical course of a case of pediatric acute pyelonephritis characterized by cluster convulsions and a poor inflammatory response. Furthermore, we strongly consider that the cause of the cluster convulsions may be related to MERS spectrum disorder and emphasize that pyelonephritis can be accompanied by CNS disturbances.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".