Amino Acid Solutions for 177Lu-Oxodotreotide Premedication: A Tolerance Study
Bibliographic record
Abstract
Background: The co-infusion of amino acid solutions during peptide receptor radionuclide therapy reduces the tubular reabsorption of 177Lu-oxodotreotide, thus minimizing nephrotoxicity. In our nuclear medicine department, the patients received two different types of amino acid perfusion over time: a commercial solution (CS) containing 10% amino acids, and a 2.5% lysine−arginine (LysArg) hospital preparation, produced by a referral laboratory. The aim of the present study was to analyze the tolerance of the two amino acid solutions. Methods: The patient files were analyzed and double-checked. The study parameters comprised the gender, age, primary tumor site, type of amino acid perfusion, adverse events (AE) and WHO AE grades, antiemetic premedication, creatinine, and serum potassium level. Results: From February 2016 to February 2019, 76 patients were treated, for a total 235 cycles. AEs occurred in 71% of the CS cycles (n = 82/116), versus 18% (n = 21/119) in the LysArg group (p < 0.0001). In the CS group, the AEs were mostly WHO grade 4 (n = 24/82), and mostly grade 1 in the LysArg group (n = 13/21). Poisson regression showed a higher risk of AE overall and of grades 3 and 4 in the females and with CS. The mean creatinine clearance was identical before and after the PRRT cycles, whichever amino acid perfusion was used. Conclusions: The lysine−arginine preparation showed better tolerance than the commercial solution. The change to LysArg reduced the antiemetic premedication from four molecules to one.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".