The Association Between Iron Deficiency and Febrile Seizures in Childhood
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to determine the association between iron deficiency and febrile seizures in a large cohort of children aged 6 to 36 months. METHODS: A retrospective case control study with 361 patients who presented with febrile seizures to the emergency department and 390 otherwise healthy controls who presented with a febrile illness to the emergency department were reviewed to determine iron status using the MCV, RDW, and hemoglobin. RESULTS: A total of 9% of cases had iron deficiency (ID) and 6% had iron deficiency anemia (IDA), compared to 5% and 4% of controls respectively. The conditional logistic regression odds ratio for ID in patients with febrile seizures was 1.84 (95% CI, 1.02-3.31). CONCLUSION: Children with febrile seizures were almost twice as likely to be iron deficient as those with febrile illness alone. The results suggest that screening for ID should be considered in children presenting with febrile seizure.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".