July 2019 at a Glance: Imaging of Congestion, Sodium–Glucose Co-Transporter 2 Inhibitors, Myocardial Function and Mitraclip Trials
Bibliographic record
Abstract
Peripartum cardiomyopathy is generally defined as heart failure (HF) with reduced ejection fraction (HFrEF) in the last month of pregnancy or in the months following delivery in women without another known cause of HF. Its outcome ranges from full recovery to persistent left ventricular (LV) dysfunction or even death.1,2 An updated position statement of the Heart Failure Association (HFA) summarizes the pathophysiology, diagnosis and current management of this important condition.3 Sodium–glucose co-transporter 2 (SGLT2) inhibitors reduce HF-related events in patients with type 2 diabetes at high cardiovascular risk.4,5 Ongoing randomized controlled trials are evaluating their efficacy in non-diabetic patients with HF. Insights regarding their potential role and mechanisms of action come from experimental studies. Yurista et al.6 assessed the effects of SGLT2 inhibition with empagliflozin in non-diabetic rats with post-myocardial infarction LV dysfunction induced by coronary artery ligation. In addition to a two-fold increase in diuresis without adverse effects on renal function, empagliflozin treatment increased LV ejection fraction, attenuated cardiomyocyte hypertrophy, interstitial fibrosis, myocardial oxidative stress and mitochondrial DNA damage with normalization of myocardial uptake and oxidation of glucose and fatty acids, and increased ATP production. Circulating ketone levels and myocardial expression of the ketone body transporter and of two critical ketogenic enzymes were also increased consistent with an increase in their myocardial utilization. Thus, in addition to diuresis, SGLT2 inhibition can favourably affect myocardial metabolism.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.120 | 0.020 |
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".