Longitudinal changes in <scp>LIC</scp> and other parameters in patients receiving different chelation regimens: Data from <scp>LICNET</scp>
Bibliographic record
Abstract
OBJECTIVES: The liver remains the primary site of iron storage, with liver iron concentration (LIC) being a strong surrogate of total body iron. MRI-R2 can accurately measure LIC. The LICNET (Liver Iron Cutino Network) was established to diagnostics of liver iron overload by MRI-R2 subjects with hemochromatosis in hematological disorders. The aims of the study were to look at variation in LIC measurements during time across different chelation regimens. METHODS: ) were made using t test and/or Wilcoxon test. RESULTS: LIC significantly decreased from MRI1 to MRI2 although at high variance (median change -0.8 mg Fe/g dw, range: -29.0 to 33.0; P = .011) and 7.7% of patients shifted from LIC values of high risk (>15 mg Fe/g dw) to an intermediate-risk category (7-15 mg Fe/g dw). Median change in LIC and correlation with serum ferritin levels (SF), during different chelation regimens, is reported. CONCLUSIONS: These findings suggest as longitudinal variation in the LIC is possible, across all chelation regimens. It confirms as SF levels not always can be used for estimating changes in LIC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".