MR-proADM is a strong independent predictor of long-term all-cause mortality risk in patients with chronic heart failure: results from the E-INH study

Autor: F Kerwagen, F Sahiti, S Sehner, J Albert, V Cejka, N Moser, C Morbach, G Gueder, S Frantz, G Ertl, C E Angermann, S Stoerk
Rok vydání: 2022
Předmět:
Zdroj: European Heart Journal. 43
ISSN: 1522-9645
0195-668X
Popis: Background Mid-regional proadrenomedullin (MR-proADM) is a blood biomarker indicating critical illness. Its short-term prognostic relevance has been investigated in several conditions including heart failure (HF). Yet, the long-term prognostic utility is unknown. Methods We conducted a post-hoc analysis of the Extended Interdisciplinary Network for Heart Failure (E-INH) study, which investigated the long-term effects of a HF nurse-led remote patient care program (HeartNetCare-HFTM [HNC]). Patients from nine regional centers in Germany hospitalized with HF and a left ventricular ejection fraction (LVEF) Results From 919 out of the 1022 recruited patients (90%), baseline levels of MR-proADM were available: median MR-proADM 0.89 (quartiles 0.63, 1.28) nmol/l; mean age 68±12 years; 28% women; 45% in class III or IV of the New York Heart Association (NYHA) classification. Median LVEF was 31 (25, 37) %. Median levels of NT-proBNP, high sensitive C-reactive protein (hsCRP), tumor necrosis factor (TNF)-a, and interleukin-6 (IL-6) were 3045 (1087, 7759) pg/ml, 9.2 (3.3, 25.2) mg/l, 13.4 (10.4, 17.5) pg/ml, and 4.9 (2.0, 11.4) pg/ml, respectively. Higher levels of MR-proADM at baseline were associated with age, female sex, NYHA class, NT-proBNP, hsCRP, IL-6, and TNF-α, while there was an inverse association with LVEF. In the course of 10 years of follow-up, 691 (68%) patients died. Unadjusted MR-proADM strongly predicted all-cause death when used as a continuous variable (HR 1.31 per nmol/l, 95% CI 1.26–1.37; p Conclusion MR-proADM appears to be a strong and independent predictor for long-term all-cause mortality risk in HF with reduced ejection fraction (HFrEF). Therefore, assessing MR-proADM may contribute to better categorization of risk and tailored care. Its clinical utility needs to be investigated in future studies. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): BMBF
Databáze: OpenAIRE
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