Case Report: A Metabolic Disorder Presenting as Pediatric Manganism
Bibliographic record
Abstract
CONTEXT: Manganese is a trace element, essential for physiologic functioning but neurotoxic at high doses. Common exposure sources include dietary intake as well as drinking water in some regions; toxicity is most often associated with inhalation exposures in occupational settings. In this article we describe the investigation of a pediatric case of manganism using both clinical and environmental assessment methods. CASE PRESENTATION: A previously healthy 6-year-old child presented with severe Mn neurotoxicity, iron deficiency, and elevated cobalt levels. Immediate and selected extended family members had elevated plasma Mn but remained asymptomatic. An exposure assessment identified seasonal ingestion exposures to Mn at the family's summer cottage; these were common to the four immediate family members. Well water used for drinking and cooking exceeded recommended guidelines, and foods high in Mn predominated in their diet. No inhalation exposures were identified. Only pica was unique to the patient. DISCUSSION: The combined evidence of the environmental assessment and biomonitoring of blood Mn levels supported a seasonal ingestion exposure source; this alone was insufficient to explain the toxicity because the patient's 7-year-old sibling was asymptomatic with almost identical exposures (except pica). A metabolic disorder involving divalent metals (Mn, Fe, and Co) interacting with environmental exposures is the most likely explanation. RELEVANCE TO CLINICAL OR PROFESSIONAL PRACTICE: This case report adds to the emerging body of evidence linking neurologic effects to ingestion Mn exposure.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".