Bibliographic record
Abstract
Differences between patients with heart failure (HF) are one of the main obstacles to treatment. The distinction between HF with reduced ejection fraction (HFrEF) or preserved ejection fraction (HFpEF) is a major example of such heterogeneity with effective treatments proven only in HFrEF. In this issue of the journal, a study from the TIME-CHF trial shows differences in the biomarkers' profile between patients with HFrEF and HFpEF with lower NT-proBNP and hs-troponin T levels and higher ST2, hsCRP and cystatin-C levels in the patients with HFpEF.1 As pointed out in the editorial by Eugene Braunwald, these data suggest that different pathophysiological pathways may be involved in the patients with HF. Their detection through biomarkers' profile may be a step towards personalized care.2 Another example of differences between patients with HFrEF and HFpEF is shown. Scherbakow et al. have studied insulin resistance in non-diabetic patients with HF, compared with normal subjects. Patients with HF have insulin resistance and it is more severe in the patients with low EF, compared with those with HFpEF, when dynamic measurements were used.3 Hyperkaelemia may develop in a meaningful proportion of patients with HF and limit the use of renin angiotensin system inhibitors and aldosterone antagonists.4 New gastrointestinal potassium binders have been recently developed and, as pointed out by Marvin Konstam's in his editorial comment, will soon allow safe and tolerable treatment of hypekalemia and better use of neurohormonal antagonists for the treatment of HF.5 In this issue of the journal, the effects of these two agents, sodium zirconium cyclosilicate, ZS-9, a selective potassium ion binder, and patiromer, an oral potassium binding polymer, on serum potassium levels in the patients with HF enrolled in two larger phase III studies, are reported.6, 7 The efficacy, safety and slight differences between these agents can be assessed. The new option for hyperkalaemia treatment is shown. Other studies regarding HF treatment include the revised statistical analysis plan and the baseline characteristics of the patients enrolled in the ATMOSPHERE trial8 and a study comparing the effects of baroreflex activation therapy in patients with and without CRT.9 Enjoy reading!
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
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".