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11. Impact of progressive aortic regurgitation on outcomes after left ventricular assist device implantation

13. Remote haemodynamic monitoring of pulmonary artery pressures in patients with chronic heart failure (MONITOR-HF): a randomised clinical trial

14. Contemporary guideline‐directed medical therapy in de novo, chronic, and worsening heart failure patients: First data from the TITRATE‐HF study

25. Age-stratified and blood-pressure-stratified effects of blood-pressure-lowering pharmacotherapy for the prevention of cardiovascular disease and death: an individual participant-level data meta-analysis

27. Abstract 12012: Subphenotypes of Heart Failure With Reduced Ejection Fraction Based on Repeated Measurements of 4210 Circulating Proteins Are Driven by Protein Subsets Reflecting Different Biological Mechanisms

29. Guideline implementation, drug sequencing, and quality of care in heart failure:design and rationale of TITRATE-HF

30. Embedding routine health care data in clinical trials:with great power comes great responsibility

31. Sex-specific cardiovascular protein levels and their link with clinical outcome in heart failure

32. The different risk of new-onset, chronic, worsening, and advanced heart failure:A systematic review and meta-regression analysis

33. Embedding routine health care data in clinical trials: with great power comes great responsibility

34. Cost-effectiveness of remote haemodynamic monitoring by an implantable pulmonary artery pressure monitoring sensor (CardioMEMS-HF system) in chronic heart failure in the Netherlands

37. Guideline implementation, drug sequencing, and quality of care in heart failure: design and rationale of TITRATE‐HF

39. Use of loop diuretics in patients with chronic heart failure: an observational overview

40. Remote haemodynamic monitoring and the next step: Involving the patient in the self‐management of heart failure.

46. The different risk of new‐onset, chronic, worsening, and advanced heart failure: A systematic review and meta‐regression analysis.

48. Machine learning–based biomarker profile derived from 4210 serially measured proteins predicts clinical outcome of patients with heart failure

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