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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".