Plasma myo-inositol elevation in heart failure: clinical implications and prognostic significance. Results from the BElgian and CAnadian MEtabolomics in HFpEF (BECAME-HF) research project
Bibliographic record
Abstract
BACKGROUND: The metabolic environment plays a crucial role in the development of heart failure (HF). Our prior research demonstrated that myo-inositol, a metabolite transported by the sodium-myo-inositol co-transporter 1 (SMIT-1), can induce oxidative stress and may be detrimental to heart function. However, plasmatic myo-inositol concentration has not been comprehensively assessed in large cohorts of patients with heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). METHODS: Plasmatic myo-inositol levels were measured using mass spectrometry and correlated with clinical characteristics in no HF subjects and patients with HFrEF and HFpEF from Belgian (male, no HF, 53%; HFrEF, 84% and HFpEF, 40%) and Canadian cohorts (male, no HF, 51%; HFrEF, 92% and HFpEF, 62%). FINDINGS: Myo-inositol levels were significantly elevated in patients with HF, with a more pronounced increase observed in the HFpEF population of both cohorts. After adjusting for age, sex, body mass index, hypertension, diabetes, and atrial fibrillation, we observed that both HFpEF status and impaired kidney function were associated with elevated plasma myo-inositol. Unlike HFrEF, abnormally high myo-inositol (≥69.8 μM) was linked to unfavourable clinical outcomes (hazard ratio, 1.62; 95% confidence interval, [1.05-2.5]) in patients with HFpEF. These elevated levels were correlated with NTproBNP, troponin, and cardiac fibrosis in this subset of patients. INTERPRETATION: Myo-inositol is a metabolite elevated in patients with HF and strongly correlated to kidney failure. In patients with HFpEF, high myo-inositol levels predict poor clinical outcomes and are linked to markers of cardiac adverse remodelling. This suggests that myo-inositol and its transporter SMIT1 may have a role in the pathophysiology of HFpEF. FUNDING: BECAME-HF was supported by Collaborative Bilateral Research Program Québec - Wallonie-Brussels Federation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 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".