Medication-Induced Hyperglycemia and Diabetes Mellitus: A Review of Current Literature and Practical Management Strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the increasing global incidence of diabetes mellitus, physicians may encounter more patients with acute and chronic complications of medication-induced hyperglycemia and diabetes. Moreover, medication-induced diabetes may be an important contributing factor to the high rates of diabetes, and recognizing its impact and risk is a critical step in curtailing its effect on the global population. It has long been recognized that multiple classes of medications are associated with hyperglycemia through various mechanisms, and the ability to foresee this and implement adequate management strategies are important. Moreover, different antihyperglycemic medications are better suited to combat the hyperglycemia encountered with different classes of medications, so it is critical that physicians can recognize which agents should be used, and which medications to avoid in certain types of medication-induced hyperglycemia. In this review, we will discuss the evidence behind the main classes of medications that cause hyperglycemia, their mechanism of action, specific agents that are associated with worsened glycemic control, and, most importantly, management strategies that are tailored to each specific class.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it