Trends in Antihyperglycemic Medication Prescriptions and Hypoglycemia in Older Adults: 2002-2013
Bibliographic record
Abstract
BACKGROUND: Over the last decade, several new antihyperglycemic medications have been introduced including those associated with a lower hypoglycemia risk. We aimed to investigate how these medications are being prescribed to older adults in our region. METHODS: We conducted population-based cross-sectional analyses of older adults (mean age 75 years) with treated diabetes in Ontario, Canada from 2002 until 2013, to examine the percentage prescribed insulin, sulphonylureas, alpha-glucosidase inhibitors, metformin, thiazolidinediones, meglitinides, and dipeptidyl peptidase-4 inhibitors. Over the study period, we also examined their hospital encounters for hypoglycemia (emergency room or inpatient encounter). RESULTS: The mean age of treated patients increased slightly over the study quarters and the proportion that were women declined. With the exception of chronic kidney disease, cancer, dementia, and neuropathy, the percentage with a comorbidity appeared to decline. The percentage of treated patients prescribed metformin, gliclazide and dipeptidyl peptidase-4 inhibitors increased as did combination therapy. Glyburide and thiazolidinedione prescriptions declined, and insulin use remained stable. In those with newly treated diabetes, the majority were prescribed metformin, with smaller percentages prescribed insulin and other oral agents. Although the absolute number of treated patients with a hypoglycemia encounter increased until mid-2006 and then decreased, the overall percentage with an encounter declined over the study period (0.8% with an event in the first quarter, 0.4% with an event in the last quarter). CONCLUSIONS: Antihyperglycemic medications with safer profiles are being increasingly prescribed to older adults. In this setting there has been a decrease in the percentage of treated patients with a hospital encounter for hypoglycemia.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".