The impact of high dose vitamin C on blood glucose testing in FDG PET imaging
Bibliographic record
Abstract
2641 Objectives Alternative therapies are common in oncology, however not all patients may disclose these treatments to their health care team. Unforeseen side effects may occur and interfere with conventional management. Specifically, high dose Vitamin C (ascorbic acid) treatment may lead to an inability to measure blood glucose prior to FDG injection in PET scanning. We report a case of a 52-y-old female referred for an FDG PET/CT to evaluate the extent of recurrent colorectal cancer. Methods A PET/CT appointment immediately followed a single intravenous dose of 25g vitamin C administered by a Naturopath. Prior to FDG injection, the patient9s fasting blood glucose was measured with a glucometer which employs the glucose oxidase method of analysis. In this method, blood glucose reacts with glucose oxidase on the strip, subsequently forming a blue color on the test strip proportional to glucose levels in the blood. Results When the patient9s blood was placed on the glucose test strip, no reaction occurred. Several blood samples from both venous and capillaries were used. 6 separate glucose strips from different containers and different lot numbers also produced no blue color on the test strip. The package insert for glucose test strips lists ascorbic acid in concentrations above expected therapeutic levels (up to 0.2mmol/L) is among the contraindications for this type of glucometer. No alternate means for testing glucose were immediately accessible so FDG was administered and a PET/CT scan was performed without knowing the patient9s fasting blood glucose level. Upon image review, the scan results and FDG distribution did not seem to be compromised. Conclusions Patients may not disclose alternative treatments to their health care team. We found the high concentration of ascorbic acid in the patient9s blood interfered with the chromagen oxidation on the glucose test strip, resulting in no glucose reading prior to FDG injection. Blood glucose testing is a validity check, as high glucose levels would reduce tumor absorption of FDG and impair scan sensitivity.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".