Hypoglycemia Associated With PEG-asparaginase and 6-MP Therapy During Treatment of Acute Lymphoblastic Leukemia in Pediatric Patients: A Case Series
Bibliographic record
Abstract
BACKGROUND: Asparaginases are a mainstay treatment for pediatric acute lymphoblastic leukemia (ALL). Recent reports identified hypoglycemia associated with asparaginases. Other reports describe hypoglycemia associated with 6-mercaptopurine (6-MP), another fundamental ALL therapy. Little is known about the risk of hypoglycemia associated with ALL therapy, an adverse event that puts children at risk of decreased level of consciousness, seizures, and possibly negative neurocognitive sequelae. METHODS: We performed a retrospective chart review of 6 children with hypoglycemia during ALL treatment in our institution from May 2016 to August 2019. Timing and duration of hypoglycemia relative to polyethylene glycol (PEG)-asparaginase, 6-MP, and corticosteroids were determined. Laboratory values of the critical sample were collected. RESULTS: The median age was 2.75 (interquartile range: 1.88 to 3.63) years. Three patients had trisomy 21. The onset of hypoglycemia was 5 to 19 days after the most recent PEG-asparaginase administration or 6 to 7 months after initiating daily 6-MP. Sixteen hypoglycemic events were documented, and 9/16 had a critical sample drawn. Six events were hypoketotic, associated with PEG-asparaginase. Three were ketotic, associated with 6-MP. Two patients required treatment with diazoxide and cornstarch. CONCLUSIONS: Hypoglycemia associated with PEG-asparaginase occurred later and lasted longer than previous reports with l-asparaginase, with the likely mechanism being hyperinsulinism. 6-MP was associated with ketotic hypoglycemia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".