A Pragmatic Protocol for I-131 rhTSH-Stimulated Ablation Therapy in Patients With Renal Failure
Bibliographic record
Abstract
PURPOSE: Ablation of thyroid remnants in patients with differentiated thyroid carcinoma and renal failure can be challenging because of the altered and variable clearance rates of iodine from the blood secondary to variations in dialysis protocols, which complicate the selection of the appropriate I-131 dose. The advent of recombinant human TSH allows a simpler approach to dosimetry and ablation without rendering the patient hypothyroid. Avoidance of hypothyroidism may be an important consideration for patients who are experiencing various morbidities from conditions associated with renal failure. METHOD: Three patients on dialysis, who had undergone total thyroidectomy and were euthyroid on L-thyroxine replacement, were given diagnostic doses of I-131 followed by blood and whole-body retention measurements through serial dialyses to determine individual blood clearance rates. After administration of rhTSH, each patient received an ablative dose of I-131 calculated to keep total body dose below 1 Gy. RESULTS: The treatments were administered without complications, and in follow-up imaging of 2 available patients, the ablations were demonstrated to be complete. CONCLUSION: Dosimetry performed on euthyroid dialysis patients permits I-131 dose selection and avoids the additional morbidity of hypothyroidism.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".