Effect of Discontinuation of Manganese Supplementation From Home Parenteral Nutrition Solutions on Whole‐Blood Levels and Magnetic Resonance Imaging of the Brain: A 5‐Year Cohort Study
Bibliographic record
Abstract
BACKGROUND: Manganese (Mn) is included in current premixed multiple trace element (TE) additives for home parenteral nutrition (HPN). However, there is a risk of oversupplementation of Mn due to contamination from PN additives. Oversupplementation can produce Mn toxicity with neurologic symptoms and abnormalities on brain magnetic resonance imaging (MRI). In 2009, we reported that whole-blood Mn levels were above the upper limit of normal in 16 HPN patients, with 81% having MRI findings. Subsequently, we removed Mn supplementation from all our HPN patients. We present a 5-year follow-up here. METHODS: This is a prospective cohort study on 11 of the surviving 16 patients on HPN. All patients had Mn removed from PN and had yearly monitoring of blood Mn levels. Eight patients had a repeat MRI to evaluate for resolution of basal ganglia deposits. Patient demography, clinical history, and bloodwork were recorded. RESULTS: Five of 6 patients who initially had elevated Mn levels had normal levels on follow-up. All patients who had Mn levels measured serially had a decrease in levels; the mean percent decrease of Mn was 38.1% (range, 10.1%-53.8%). Two patients had elevated Mn despite the absence of supplementation. Six of 8 patients who had repeat MRIs had complete resolution abnormalities. CONCLUSIONS: Removal of Mn as an additive in HPN solutions resulted in resolution of MRI abnormalities in most patients. Over 5 years, all patients except for 1 maintained normal blood Mn levels. Therefore, Mn levels should be monitored and supplementation be individualized.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".