Feasibility of a Modified Atkins Diet in Glioma Patients During Radiation and Its Effect on Radiation Sensitization
Bibliographic record
Abstract
Background: Gliomas are the most dreaded primary brain tumour because of their dismal cure rates. Ketogenic-type diets (kds) are high-fat, low-protein, and low-carbohydrate diets; the modified Atkins diet (mad) is a less-stringent version of a kd that still generates serum ketones in patients. The purpose of the present study was to retrospectively examine the feasibility of attaining ketosis and the safety of the mad in patients undergoing radiation and chemotherapy treatment for glioma. The rate of pseudoprogression (psp) after treatment was also assessed as a marker of radiation sensitization. To our knowledge, this dataset is the largest published relating to patients with glioma undergoing kd during radiation and chemotherapy. Methods: We retrospectively studied 29 patients with grades ii-iv astrocytoma following the mad during standard radiation and chemotherapy. Feasibility of attaining ketosis was assessed though levels of beta hydroxybutyrate in blood. Pre- and post-radiation magnetic resonance images were evaluated for psp by a neuroradiologist blinded to patient data. Results: In the 29 patients who started the mad during radiation, ketosis was achieved in all 29 (100%). No serious adverse events occurred secondary to the mad. Of those 29 patients, 19 had glioblastoma multiforme. Of the latter 19 patients, 11 (58%) showed psp after mad and radiation and temozolomide therapy. Conclusions: A modified Atkins diet is feasible and safe for glioma patients during radiation and chemotherapy treatment. The mad and resulting ketosis could play a role as a radiation sensitizer.
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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".