Severe Hypoglycemia in a Patient With Type 1 Diabetes Mellitus Recently Started on Sacubitril/Valsartan: A Case Report
Bibliographic record
Abstract
This report describes an episode of severe hypoglycemia in a 55-year-old woman with type 1 diabetes mellitus approximately 2 weeks after initiating sacubitril/valsartan for heart failure. She was receiving a continuous subcutaneous insulin infusion and denied any severe hypoglycemic events in the prior 13 years. She experienced a second hypoglycemic episode 1 week later. She subsequently reduced her insulin dose and continued on sacubitril/valsartan. Eight months later, she did not have any recurrent hypoglycemic episodes. Clinicians should be aware of this potential adverse effect and educate patients on concomitant insulin therapy to monitor for symptoms of hypoglycemia when initiating sacubitril/valsartan.
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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) | 0.001 | 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".