Self-identified gadolinium toxicity: comparison of gadolinium in bone and urine to healthy gadolinium-based contrast agent exposed volunteers
Bibliographic record
Abstract
Abstract Objective : To report additional gadolinium bone and urine data that can contribute to gaps in knowledge with respect to gadolinium uptake and retention in the body. Approach : In vivo measurements of gadolinium retention in the tibia bone were performed on individuals self-identified as exhibiting symptoms of gadolinium toxicity as a result of receiving GBCA, as well as on control individuals. Gadolinium urine measurements for controls, symptomatic exposed, and non-symptomatic exposed were conducted through Mayo Medical Laboratories. Main results : Gadolinium bone concentration in the exposed group is significantly higher than the control group ( p < 0.01), with a significant difference between symptomatic and non-symptomatic ( p < 0.01), using a one-tailed t test on variance-weighted means. Gadolinium urine levels in both control subjects and non-symptomatic exposed subjects are significantly lower than symptomatic exposed subjects ( p ≤ 0.05). A linear regression analysis for gadolinium urine levels and GBCA dose resulted in a positive linear relationship ( R 2 = 0.91, p < 0.01). Gadolinium levels in urine and gadolinium concentration in bone were found to have a non-significant relationship ( R 2 = 0.11, p = 0.3). Significance : Significant differences in gadolinium levels in bone and urine are observed between individuals experiencing symptoms of gadolinium toxicity and for those who are not exhibiting symptoms. No correlation was observed between gadolinium in bone and gadolinium excreted in urine, suggesting that the retention of gadolinium in the body is complicated, involving multiple long-term storage sites.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".