Stability of RAIU in pre-therapy patients
Bibliographic record
Abstract
197 Objectives Radioactive iodine uptake (RAIU) plays a central role in 131I-NaI dose calculation for hyperthyroidism. Current guidelines recommend use of recent (≤1 month) values to calculate therapy. We wish to evaluate stability of RAIU in patients with hyperthyroidism and identify factors that might predict variation of RAIU over time. Methods 56 patients with hyperthyroidism (32 Grave’s disease, 18 toxic multinodular goiter, 6 solitary adenoma) underwent repeat RAIU measurements within 8-52 weeks without intervening radioiodide therapy. Demographic information, etiology, gland size, and history of medical and radioiodide therapy were recorded. Results Interval between RAIU repeat measurements was 8-52 weeks (average 25.2 weeks); RAIU ranged from 6-80% (average 44.9%). Absolute and relative RAIU differences between measurements ranged from 0-38% (average 11.6%) and 0 to 1.43 (average 0.296) respectively (SEM in our lab is 1%). There was no significant correlation between relative RAIU difference and time (R2=-0.02, p=0.88). In 49 patients, relative RAIU differences were ≤0.50, an accepted variation in treatment dosing. 7 patients had relative RAIU difference >0.50; all had small glands (Wt ≤30g) and low RAIU (≤35%). Interval between RAIU measurements in these patients was 13-39 weeks (average 21.7 weeks). Using a F-test to compare standard deviation, we show that fractional Δ RAIU variation was greater in patients with small vs large thyroids (F(41,13)=7.74, p=0.0003) and in those with low vs high initial RAIU (F(20,34)=13.0, p Conclusions Variation of RAIU over 8-52 weeks is relatively constant and does not correlate with intervening interval, averaging 11.6%, with greater relative variability in patients with lower uptake and smaller glands. These results suggest that in patients with large thyroids and elevated RAIU, RAIU can be considered clinically stable and usable to calculate therapy over the course of several months.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".