Cardiovascular outcomes and safety with linagliptin, a dipeptidyl peptidase‐4 inhibitor, compared with the sulphonylurea glimepiride in older people with type 2 diabetes: A subgroup analysis of the randomized <scp>CAROLINA</scp> trial
Bibliographic record
Abstract
AIM: To compare the cardiovascular (CV) safety of linagliptin with glimepiride in older and younger participants in the CAROLINA trial in both prespecified and post hoc analyses. MATERIALS AND METHODS: People aged 40 to 85 years with relatively early type 2 diabetes, inadequate glycaemic control and elevated CV risk were randomly assigned to linagliptin 5 mg or glimepiride 1 to 4 mg. The primary endpoint was time to first occurrence of three-point major adverse CV events (MACE: CV death, non-fatal myocardial infarction, or non-fatal stroke). We evaluated clinical and safety outcomes across age groups. RESULTS: Of 6033 participants, 50.7% were aged <65 years, 35.3% were aged 65 to 74 years, and 14.0% were aged ≥75 years. During the 6.3-year median follow-up, CV/mortality outcomes did not differ between linagliptin and glimepiride overall (hazard ratio [HR] for three-point MACE 0.98, 95.47% confidence interval [CI] 0.84, 1.14) or across age groups (interaction P >0.05). Between treatment groups, reductions in glycated haemoglobin were comparable across age groups but moderate-to-severe hypoglycaemia was markedly reduced with linagliptin (HR 0.18, 95% CI 0.15, 0.21) with no differences among age groups (P = 0.23). Mean weight was -1.54 kg (95% CI -1.80, -1.28) lower for linagliptin versus glimepiride. Adverse events increased with age, but were generally balanced between treatment groups. Significantly fewer falls or fractures occurred with linagliptin. CONCLUSIONS: Linagliptin and glimepiride were comparable for CV/mortality outcomes across age groups. Linagliptin had significantly lower risk of hypoglycaemia and falls or fractures than glimepiride, including in "older-old" individuals for whom these are particularly important treatment considerations.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".