Insulin Treatment and Clinical Outcomes in Patients with Diabetes and Heart Failure with Preserved Ejection Fraction
Bibliographic record
Abstract
AIMS: Insulin causes sodium retention and hypoglycaemia and its use is associated with worse outcomes in heart failure (HF) with reduced ejection fraction. We have investigated whether this is also the case in HF with preserved ejection fraction (HFpEF). METHODS AND RESULTS: We examined the association between diabetes/diabetes treatments and the risk of the primary composite of cardiovascular death or HF hospitalization, as well as other outcomes in adjusted analyses in CHARM-Preserved (left ventricular ejection fraction ≥ 45%), I-Preserve and TOPCAT (Americas) pooled. Of 8466 patients, 2653 (31%) had diabetes, including 979 (37%) receiving insulin. Patients receiving insulin were younger, had a higher body mass index, prevalence of ischaemic aetiology, N-terminal pro-B-type natriuretic peptide and use of diuretics, worse New York Heart Association class and signs and symptoms, and worse quality of life and renal function, compared to patients with diabetes not on insulin. Among the 1398 patients with echocardiographic data, insulin use was associated with higher left ventricular end-diastolic pressure and more diastolic dysfunction than in other participants. The primary outcome occurred at a rate of 6.3 per 100 patient-years in patients without diabetes, and 10.2 and 17.1 per 100 patient-years in diabetes patients without and with insulin use, respectively [fully adjusted hazard ratio (aHR) insulin-treated diabetes vs. other diabetes: 1.41, 95% confidence interval (CI) 1.23-1.63, P < 0.001]. The adjusted HR is 1.67 (95% CI 1.20-2.32, p = 0.002) for sudden death (insulin-treated diabetes vs. other diabetes). CONCLUSIONS: Insulin use is associated with poor outcomes in HFpEF. Although we cannot conclude a causal association, the safety of insulin and alternative glucose-lowering treatments in HF needs to be evaluated in clinical trials.
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 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) | 0.000 | 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".