NT-proBNP and High Intensity Care for Acute Heart Failure

The STRONG-HF Trial

Marianna Adamo; Alexandre Mebazaa; Beth Davison; Christopher Edwards; Daniela Tomasoni; Mattia Arrigo; Marianela Barros; Jan Biegus; Jelena Celutkiene; Kamilė Čerlinskaitė-Bajorė; Ovidiu Chioncel; Alain Cohen-Solal; Albertino Damasceno; Rafael Diaz; Gerasimos Filippatos; Etienne Gayat; Antoine Kimmoun; Carolyn S.P. Lam; Maria Novosadova; Peter S. Pang; Piotr Ponikowski; Hadiza Saidu; Karen Sliwa; Koji Takagi; Jozine M. Ter Maaten; Adriaan Voors; Gad Cotter; Marco Metra

Disclosures

Eur Heart J. 2023;44(31):2947-2962.

Abstract and Introduction

Abstract

Aims: STRONG-HF showed that rapid up-titration of guideline-recommended medical therapy (GRMT), in a high intensity care (HIC) strategy, was associated with better outcomes compared with usual care. The aim of this study was to assess the role of N-terminal pro-B-type natriuretic peptide (NT-proBNP) at baseline and its changes early during up-titration.

Methods and Results: A total of 1077 patients hospitalized for acute heart failure (HF) and with a >10% NT-proBNP decrease from screening (i.e. admission) to randomization (i.e. pre-discharge), were included. Patients in HIC were stratified by further NT-proBNP changes, from randomization to 1 week later, as decreased (≥30%), stable (<30% decrease to ≤10% increase), or increased (>10%). The primary endpoint was 180-day HF readmission or death. The effect of HIC vs. usual care was independent of baseline NT-proBNP. Patients in the HIC group with stable or increased NT-proBNP were older, with more severe acute HF and worse renal and liver function. Per protocol, patients with increased NT-proBNP received more diuretics and were up-titrated more slowly during the first weeks after discharge. However, by 6 months, they reached 70.4% optimal GRMT doses, compared with 80.3% for those with NT-proBNP decrease. As a result, the primary endpoint at 60 and 90 days occurred in 8.3% and 11.1% of patients with increased NT-proBNP vs. 2.2% and 4.0% in those with decreased NT-proBNP (P = 0.039 and P = 0.045, respectively). However, no difference in outcome was found at 180 days (13.5% vs. 13.2%; P = 0.93).

Conclusion: Among patients with acute HF enrolled in STRONG-HF, HIC reduced 180-day HF readmission or death regardless of baseline NT-proBNP. GRMT up-titration early post-discharge, utilizing increased NT-proBNP as guidance to increase diuretic therapy and reduce the GRMT up-titration rate, resulted in the same 180-day outcomes regardless of early post-discharge NT-proBNP change.

Structured Graphical Abstract

(Enlarge Image)

The role of NT-proBNP in patients receiving high intensity care (HIC) after hospital admission for acute heart failure. This analysis from the STRONG-HF trial includes 1077 patients. The treatment effect of a HIC strategy vs. usual care (UC) reduced the primary endpoint regardless of baseline NT-proBNP concentrations. In the 542 patients included in the HIC group, an increase in NT-proBNP levels was associated with a poorer outcome up to 90-day follow-up, but not at 180 days. CI, confidence interval; HF, heart failure; HR, hazard ratio; NT-proBNP, N-terminal pro-B-type natriuretic peptide.

Introduction

N-terminal pro-B-type natriuretic peptide (NT-proBNP) has a major role in the diagnosis and risk stratification of patients with heart failure (HF).^[1–3] However, its role in the titration of guideline-recommended medical therapy (GRMT) remains unsettled. The Safety, Tolerability and Efficacy of Rapid Optimization, Helped by NT-proBNP Testing, of Heart Failure Therapies (STRONG-HF) study^[4–6] showed the efficacy and safety of a high intensity care (HIC) regimen vs. usual care (UC) in patients recently hospitalized for acute HF. N-terminal pro-B-type natriuretic peptide measurements had a major role in this trial. First, they were used as enrolment criteria as patients had to have NT-proBNP concentrations at screening >2500 pg/mL with >10% decrease between screening and randomization with values >1500 pg/mL at randomization. Second, NT-proBNP measurements were repeated at 1-, 2-, 3-, and 6-week follow-up visits in the HIC regimen group and physicians were recommended not to up-titrate beta-blocker and to increase diuretic dose when NT-proBNP concentrations were >10% higher than at pre-discharge. In the pre-specified subgroup analysis of STRONG-HF, there was a trend towards a larger benefit of HIC vs. UC in patients with NT-proBNP levels above median, but without significant interaction.^[4]

Our present analysis tested two main hypotheses. First, the safety and efficacy of HIC vs. UC may have been different across patients with different NT-proBNP values at baseline. Second, we hypothesized that a HIC strategy of diuretic dose escalation and slower titration of GRMT in response to NT-proBNP increase might have mitigated, if not neutralized, the prognostic impact of early NT-proBNP changes on long-term outcome. Thus, the aim of this study was to examine the relation between baseline NT-proBNP levels and the efficacy of HIC vs. UC, as well as the prognostic significance of changes in NT-proBNP concentrations during follow-up in the HIC group.

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Next Section

Abstract and Introduction
Methods
Results
Discussion
Conclusions
References

Table 1. Baseline characteristics according to baseline N-terminal pro-B-type natriuretic peptide tertiles
	Tertile 1 < 2159 ng/L (n = 359)	Tertile 2 2160–4165 ng/L (n = 359)	Tertile 3 ≥ 4165 ng/L (n = 359)	P-value for trend
Age, years	61.7 (13.85)	62.4 (13.47)	64.7 (13.29)	0.0018
Male sex	220 (61.3%)	220 (61.3%)	221 (61.6%)	0.9694
Race
Black	82 (22.8%)	78 (21.7%)	70 (19.6%)	0.6769
Caucasian	272 (75.8%)	276 (76.9%)	284 (79.3%)
Systolic blood pressure, mmHg	124.0 (12.40)	122.7 (13.28)	121.9 (13.08)	0.0839
History of atrial fibrillation or atrial flutter or present at screening	145 (40.4%)	160 (44.6%)	177 (49.3%)	0.0163
Medical history
Stroke or transient ischaemic attack	28 (7.8%)	36 (10.1%)	35 (9.8%)	0.3597
Malignancies	10 (2.8%)	8 (2.2%)	11 (3.1%)	0.8176
Diabetes	103 (28.7%)	105 (29.4%)	105 (29.3%)	0.8506
Acute coronary syndrome	90 (25.1%)	104 (29.0%)	117 (32.6%)	0.0262
Coronary artery bypass surgery	14 (3.9%)	23 (6.4%)	22 (6.1%)	0.1864
Percutaneous transluminal coronary intervention	48 (13.4%)	52 (14.5%)	52 (14.5%)	0.6570
Moderate or severe chronic obstructive pulmonary disease or asthma	5 (1.4%)	12 (3.3%)	10 (2.8%)	0.2839
Cardiac resynchronization therapy	1 (0.3%)	0	5 (1.4%)	0.0761
Automatic internal cardiac defibrillator	0	4 (1.1%)	5 (1.4%)	0.0625
Heart failure history
History of heart failure	304 (84.7%)	311 (86.6%)	301 (83.8%)	0.7535
NYHA Class 1 month before hospital admission
I	18 (5.4%)	15 (4.5%)	30 (8.9%)	0.3919
II	116 (34.9%)	115 (34.6%)	76 (22.6%)
III	120 (36.1%)	145 (43.7%)	150 (44.6%)
IV	78 (23.5%)	57 (17.2%)	80 (23.8%)
Ischaemic aetiology	154 (43.0%)	176 (49.0%)	184 (51.4%)	0.0248
Left ventricular ejection fraction, %	38.0 (12.15)	36.9 (12.78)	34.0 (12.31)	<0.0001
Hospitalized for heart failure in the past year	84 (23.4%)	86 (24.0%)	103 (28.7%)	0.1031
Number of heart failure hospitalizations in the past year per patient	0.3 (0.55)	0.4 (1.68)	0.4 (0.76)	0.2773
History of atrial fibrillation or atrial flutter	148 (41.2%)	167 (46.5%)	181 (50.4%)	0.0135
Type of atrial fibrillation or atrial flutter
Paroxysmal	31 (20.8%)	45 (27.6%)	41 (23.0%)	0.4831
Permanent	90 (60.4%)	97 (59.5%)	106 (59.6%)
Persistent	28 (18.8%)	21 (12.9%)	31 (17.4%)
Laboratory data
Haemoglobin, g/L	139.0 (128.0, 154.0)	135.0 (121.0, 147.0)	135.0 (122.0, 148.0)	0.0002
Lymphocytes, %	29.4 (22.9, 36.0)	27.0 (20.3, 33.8)	24.6 (17.7, 31.3)	<0.0001
White blood cells, 10⁹/L	6.8 (5.7, 7.8)	6.9 (5.5, 8.3)	6.8 (5.6, 8.2)	0.5221
Glucose, mmol/L	5.4 (4.8, 7.2)	5.5 (5.0, 6.5)	5.6 (4.9, 6.8)	0.3790
Creatinine, μmol/L	98.6 (84.0, 113.0)	104.0 (88.0, 121.0)	107.8 (89.0, 128.0)	<0.0001
Potassium, mmol/L	4.2 (3.9, 4.6)	4.4 (4.0, 4.6)	4.3 (3.9, 4.6)	0.8716
Sodium, mmol/L	141.0 (138.0, 143.7)	140.0 (137.4, 143.0)	140.0 (137.1, 143.0)	0.0851
Urea, mmol/L	6.9 (5.8, 8.8)	7.1 (6.0, 9.1)	7.9 (6.1, 10.0)	0.0001
ALT, U/I	20.0 (15.3, 31.6)	21.1 (15.3, 32.0)	22.0 (14.4, 33.0)	0.8572
Total bilirubin, μmol/L	13.0 (10.2, 18.8)	13.4 (10.6, 20.3)	14.6 (10.0, 23.9)	0.0152
Total cholesterol, mmol/L	4.2 (3.7, 4.9)	4.2 (3.4, 5.0)	4.0 (3.2, 4.7)	<0.0001
Oral heart failure medications taken pre-randomization
ACE inhibitors/ARBs/ARNI	104 (69.8%)	139 (65.9%)	83 (61.5%)	0.1402
β-Blockers	44 (29.5%)	72 (34.1%)	50 (37.0%)	0.1786
Mineralocorticoid receptor antagonists	143 (96.0%)	206 (97.6%)	118 (87.4%)	0.0028
Loop diuretic	143 (96.0%)	204 (96.7%)	128 (94.8%)	0.6368

Values presented are n (%) for categorical variables and mean (SD) or median (25th, 75th percentiles) for continuous variables.

Table 2. Outcomes according to baseline N-terminal pro-B-type natriuretic peptide tertiles and treatment strategy
Endpoint	High intensity care	Usual care	Unadjusted treatment effect		Adjusted treatment effect
Endpoint	High intensity care	Usual care	HR (95% CI)	P-value^a	HR (95% CI)	P-value^a
Primary endpoint	n/N (KM%)	n/N (KM%)
All-cause death or heart failure readmission by Day 180^b	74/506 (23.5%)	109/502 (15.2%)	0.62 (0.45, 0.86)	0.0043	0.61 (0.44, 0.85)	0.0032
Tertile 1: NT-BNP <2160	21/169 (13.5%)	27/168 (18.2%)	0.74 (0.40, 1.37)		0.72 (0.39, 1.34)
Tertile 2: NT-BNP 2160–4142	24/170 (14.4%)	27/171 (16.7%)	0.86 (0.47, 1.60)		0.85 (0.46, 1.57)
Tertile 3: NT-BNP >4142	29/167 (18.0%)	55/162 (36.5%)	0.44 (0.26, 0.72)		0.45 (0.27, 0.74)
Treatment-by-tertile interaction				0.1965		0.2444
Secondary endpoints
All-cause death by Day 180^c	39/506 (8.6%)	48/502 (10.1%)	0.83 (0.52, 1.32)	0.4342	0.78 (0.49, 1.25)	0.3098
Tertile 1: NT-BNP <2160	10/169 (6.6%)	8/168 (4.9%)	1.30 (0.47, 3.62)		1.40 (0.50, 3.92)
Tertile 2: NT-BNP 2160–4142	9/170 (6.1%)	12/171 (6.9%)	0.87 (0.33, 2.25)		0.86 (0.33, 2.24)
Tertile 3: NT-BNP >4142	20/167 (13.2%)	28/162 (19.1%)	0.68 (0.36, 1.28)		0.59 (0.31, 1.13)
Treatment-by-tertile interaction				0.5673		0.3658
	LS: mean (SE)		Mean difference (95% CI)	P-value	Mean difference (95% CI)	P-value
Change from baseline to Day 90 in EQ-5D VAS^d	10.7 (0.88)	7.2 (0.90)	3.49 (1.74, 5.24)	<0.0001	3.74 (2.06, 5.43)	<0.0001
Tertile 1: NT-BNP <2160	12.5 (1.24)	9.4 (1.20)	3.04 (0.11, 5.97)		2.62 (−0.23, 5.47)
Tertile 2: NT-BNP 2160–4142	10.7 (1.20)	7.0 (1.28)	3.70 (0.74, 6.65)		4.04 (1.16, 6.91)
Tertile 3: NT-BNP >4142	8.5 (1.30)	4.7 (1.32)	3.87 (0.70, 7.04)		4.64 (1.55, 7.73)
Treatment-by-tertile interaction				0.9209		0.6183

Results restricted to subjects at sites where patients were followed to 180 days. Results for patients in Cohort 1 are down-weighted proportional to half its sample size. n/N (Kaplan–Meier estimates) are presented. Hazard ratios from Cox proportional hazards model.
^aTreatment-by-tertile interaction P-value or overall main effect P-value presented.
^bAdjusted for baseline diastolic blood pressure, baseline NT-proBNP, ischaemic aetiology, and oedema.
^cAdjusted for baseline creatinine, baseline haemoglobin, baseline urea, and baseline NT-proBNP.
^dAll analyses adjusted for baseline EQ-VAS, region, and LVEF group (≤40/>40) using ANCOVA. Additional adjustment for baseline haemoglobin, baseline creatinine, baseline cholesterol, baseline NT-proBNP, hospitalized for heart failure in prior year, oedema, and NYHA classification.

Table 3. Oral heart failure medications relative to optimal doses by N-terminal pro-B-type natriuretic peptide change categories at 1 week
	Patients with decrease in NT-proBNP (n = 149)	Patients with stable NT-proBNP (n = 212)	Patients with increase in NT-proBNP (n = 135)	P-value for trend
Oral heart failure medications optimal dose categories at Visit 2: post-rand
ACE inhibitors/ARBs/ARNI
None	2 (1.3%)	3 (1.4%)	2 (1.5%)	0.6052
<1/2 Optimal dose	27 (18.1%)	49 (23.1%)	20 (14.8%)
1/2–<Full optimal dose	119 (79.9%)	153 (72.2%)	112 (83.0%)
≥Full optimal dose	1 (0.7%)	7 (3.3%)	1 (0.7%)
β-Blockers
None	4 (2.7%)	5 (2.4%)	1 (0.7%)	0.2270
<1/2 Optimal dose	15 (10.1%)	34 (16.0%)	11 (8.1%)
1/2–<Full optimal dose	129 (86.6%)	170 (80.2%)	121 (89.6%)
≥Full optimal dose	1 (0.7%)	3 (1.4%)	2 (1.5%)
Mineralocorticoid receptor antagonists
None	0	2 (0.9%)	6 (4.4%)	<0.0001
<1/2 Optimal dose	0	1 (0.5%)	0
1/2–<Full optimal dose	72 (48.3%)	139 (65.6%)	83 (61.5%)
≥Full optimal dose	77 (51.7%)	70 (33.0%)	46 (34.1%)
Loop diuretic dose, furosemide equivalence	59.1 (39.71)	64.1 (48.02)	58.3 (57.35)	0.1677
Oral heart failure medications optimal dose categories at Visit 3: Week 1
ACE inhibitors/ARBs/ARNI
None	1 (0.7%)	2 (0.9%)	3 (2.2%)	0.7511
<1/2 Optimal dose	26 (17.4%)	47 (22.2%)	22 (16.3%)
1/2–<Full optimal dose	120 (80.5%)	152 (71.7%)	108 (80.0%)
≥Full optimal dose	2 (1.3%)	11 (5.2%)	2 (1.5%)
β-Blockers
None	2 (1.3%)	4 (1.9%)	8 (5.9%)	0.0382
<1/2 Optimal dose	16 (10.7%)	38 (17.9%)	17 (12.6%)
1/2–<Full optimal dose	127 (85.2%)	164 (77.4%)	108 (80.0%)
≥Full optimal dose	4 (2.7%)	6 (2.8%)	2 (1.5%)
Mineralocorticoid receptor antagonists
None	1 (0.7%)	3 (1.4%)	11 (8.1%)	<0.0001
<1/2 Optimal dose	0	2 (0.9%)	0
1/2–<Full optimal dose	70 (47.0%)	125 (59.0%)	83 (61.5%)
≥Full optimal dose	78 (52.3%)	82 (38.7%)	41 (30.4%)
Loop diuretic dose, furosemide equivalence	48.3 (33.91)	59.7 (45.71)	69.6 (58.42)	<0.0001
Oral heart failure medications optimal dose categories at Visit 4: Week 2
ACE inhibitors/ARBs/ARNI
None	1 (0.7%)	2 (0.9%)	3 (2.3%)	<0.0001
<1/2 Optimal dose	11 (7.5%)	24 (11.3%)	14 (10.6%)
1/2–<Full optimal dose	24 (16.4%)	57 (26.9%)	55 (41.7%)
≥Full optimal dose	110 (75.3%)	129 (60.8%)	60 (45.5%)
βBlockers
None	2 (1.4%)	3 (1.4%)	11 (8.3%)	<0.0001
<1/2 Optimal dose	15 (10.3%)	23 (10.8%)	10 (7.6%)
1/2–<Full optimal dose	25 (17.1%)	78 (36.8%)	70 (53.0%)
≥Full optimal dose	104 (71.2%)	108 (50.9%)	41 (31.1%)
Mineralocorticoid receptor antagonists
None	1 (0.7%)	4 (1.9%)	12 (9.1%)	<0.0001
<1/2 Optimal dose	0	1 (0.5%)	0
1/2–<Full optimal dose	3 (2.1%)	26 (12.3%)	28 (21.2%)
≥Full optimal dose	142 (97.3%)	181 (85.4%)	92 (69.7%)
Loop diuretic dose, furosemide equivalence	42.9 (34.42)	59.2 (41.40)	70.9 (63.96)	<0.0001
Oral heart failure medications optimal dose categories at Visit 5: Week 3
ACE inhibitors/ARBs/ARNI
None	1 (0.7%)	2 (0.9%)	3 (2.3%)	0.0012
<1/2 Optimal dose	8 (5.5%)	24 (11.4%)	16 (12.3%)
1/2–<Full optimal dose	36 (24.8%)	56 (26.5%)	45 (34.6%)
≥Full optimal dose	100 (69.0%)	129 (61.1%)	66 (50.8%)
β-Blockers
None	2 (1.4%)	4 (1.9%)	11 (8.5%)	<0.0001
<1/2 Optimal dose	15 (10.3%)	24 (11.4%)	17 (13.1%)
1/2–<Full optimal dose	32 (22.1%)	69 (32.7%)	56 (43.1%)
≥Full optimal dose	96 (66.2%)	114 (54.0%)	46 (35.4%)
Mineralocorticoid receptor antagonists
None	1 (0.7%)	6 (2.8%)	12 (9.2%)	<0.0001
<1/2 Optimal dose	0	1 (0.5%)	0
1/2–<Full optimal dose	4 (2.8%)	21 (10.0%)	21 (16.2%)
≥Full optimal dose	140 (96.6%)	183 (86.7%)	97 (74.6%)
Loop diuretic dose, furosemide equivalence	43.7 (38.00)	58.5 (42.08)	78.7 (100.11)	<0.0001
Oral heart failure medications optimal dose categories at Visit 6: Week 6
ACE inhibitors/ARBs/ARNI
None	0	1 (0.5%)	2 (1.6%)	0.0030
<1/2 Optimal dose	8 (5.8%)	24 (11.7%)	17 (13.4%)
1/2–<Full optimal dose	39 (28.1%)	53 (25.9%)	43 (33.9%)
≥Full optimal dose	92 (66.2%)	127 (62.0%)	65 (51.2%)
β-Blockers
None	3 (2.2%)	4 (2.0%)	13 (10.2%)	<0.0001
<1/2 Optimal dose	13 (9.4%)	26 (12.7%)	17 (13.4%)
1/2–<Full optimal dose	40 (28.8%)	61 (29.8%)	48 (37.8%)
≥Full optimal dose	83 (59.7%)	114 (55.6%)	49 (38.6%)
Mineralocorticoid receptor antagonists
None	3 (2.2%)	7 (3.4%)	14 (11.0%)	<0.0001
1/2–<Full optimal dose	6 (4.3%)	19 (9.3%)	17 (13.4%)
≥Full optimal dose	130 (93.5%)	179 (87.3%)	96 (75.6%)
Loop diuretic dose, furosemide equivalence	39.1 (35.17)	59.8 (55.29)	72.0 (60.20)	<0.0001
Oral heart failure medications optimal dose categories at Visit 7: Day 90
ACE inhibitors/ARBs/ARNI
None	0	6 (2.9%)	3 (2.3%)	0.0053
<1/2 Optimal dose	11 (7.7%)	27 (13.2%)	19 (14.8%)
1/2–<Full optimal dose	43 (30.3%)	53 (26.0%)	45 (35.2%)
≥Full optimal dose	88 (62.0%)	118 (57.8%)	61 (47.7%)
β-Blockers
None	5 (3.5%)	7 (3.4%)	11 (8.6%)	0.0010
<1/2 Optimal dose	12 (8.5%)	27 (13.2%)	17 (13.3%)
1/2–<Full optimal dose	45 (31.7%)	61 (29.9%)	53 (41.4%)
≥Full optimal dose	80 (56.3%)	109 (53.4%)	47 (36.7%)
Mineralocorticoid receptor antagonists
None	4 (2.8%)	10 (4.9%)	15 (11.7%)	0.0002
<1/2 Optimal dose	0	0	1 (0.8%)
1/2–<Full optimal dose	9 (6.3%)	20 (9.8%)	16 (12.5%)
≥Full optimal dose	129 (90.8%)	174 (85.3%)	96 (75.0%)
Loop diuretic dose, furosemide equivalence	41.3 (39.96)	51.0 (42.90)	66.4 (53.06)	<0.0001
Oral heart failure medications optimal dose categories at Visit 8: Day 180
ACE inhibitors/ARBs/ARNI
None	0	4 (2.4%)	5 (5.2%)	0.0091
<1/2 Optimal dose	14 (12.4%)	26 (15.9%)	14 (14.4%)
1/2– <Full optimal dose	30 (26.5%)	48 (29.3%)	35 (36.1%)
≥Full optimal dose	69 (61.1%)	86 (52.4%)	43 (44.3%)
β-Blockers
None	3 (2.7%)	5 (3.0%)	8 (8.2%)	0.0062
<1/2 Optimal dose	12 (10.6%)	21 (12.8%)	16 (16.5%)
1/2–<Full optimal dose	42 (37.2%)	57 (34.8%)	40 (41.2%)
≥Full optimal dose	56 (49.6%)	81 (49.4%)	33 (34.0%)
Mineralocorticoid receptor antagonists
None	3 (2.7%)	5 (3.0%)	7 (7.2%)	0.0216
<1/2 Optimal dose	0	0	1 (1.0%)
1/2–<Full optimal dose	6 (5.3%)	9 (5.5%)	10 (10.3%)
≥Full optimal dose	104 (92.0%)	150 (91.5%)	79 (81.4%)
Loop diuretic dose, furosemide equivalence	34.8 (31.06)	44.8 (37.13)	65.8 (55.51)	<0.0001

Values presented are n (%) for categorical variables and mean (SD) for continuous variables.

Authors and Disclosures

Marianna Adamo¹, Matteo Pagnesi¹, Alexandre Mebazaa^2,3, Beth Davison^2,4,5, Christopher Edwards⁴, Daniela Tomasoni¹, Mattia Arrigo⁶, Marianela Barros⁴, Jan Biegus⁷, Jelena Celutkiene⁸, Kamilė Čerlinskaitė-Bajorė⁸, Ovidiu Chioncel ⁹, Alain Cohen-Solal^2,10, Albertino Damasceno¹¹, Rafael Diaz¹², Gerasimos Filippatos¹³, Etienne Gayat^2,3, Antoine Kimmoun¹⁴, Carolyn S.P. Lam^15,16, Maria Novosadova⁴, Peter S. Pang¹⁷, Piotr Ponikowski⁷, Hadiza Saidu¹⁸, Karen Sliwa ¹⁹, Koji Takagi⁴, Jozine M. Ter Maaten¹⁶, Adriaan Voors ¹⁶, Gad Cotter^2,4,5 and Marco Metra ^1*

¹Cardiology, ASST Spedali Civili and Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia 25100, Italy; ²Université Paris Cité, INSERM UMR-S 942(MASCOT), Paris, France; ³Department of Anesthesiology and Critical Care and Burn Unit, Saint-Louis and Lariboisière Hospitals, FHU PROMICE, DMU Parabol, APHP.Nord, Paris, France; ⁴Momentum Research Inc, Durham, NC, USA; ⁵Heart Initiative, Durham, NC, USA; ⁶Department of Internal Medicine, Stadtspital Zurich, Zurich, Switzerland; ⁷Institute of Heart Diseases, Wroclaw Medical University, Wrocław, Poland; ⁸Clinic of Cardiac and Vascular Diseases, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, Vilnius, Lithuania; ⁹Emergency Institute for Cardiovascular Diseases 'Prof. C.C.Iliescu', University of Medicine 'Carol Davila,', Bucharest, Romania; ¹⁰AP-HP Nord, Department of Cardiology, Lariboisière University Hospital, Paris, France; ¹¹Faculty of Medicine, Eduardo Mondlane University, Maputo, Mozambique; ¹²Estudios Clínicos Latinoamérica, Instituto Cardiovascular de Rosario, Rosario, Argentina; ¹³National and Kapodistrian University of Athens, School of Medicine, Attikon University Hospital, Athens, Greece; ¹⁴INSERM, Défaillance Circulatoire Aigue et Chronique, Service de Médecine Intensive et Réanimation Brabois, CHRU de Nancy, Université de Lorraine, Vandoeuvre-lès-Nancy, France; ¹⁵National Heart Centre Singapore and Duke- National University of Singapore, Singapore; ¹⁶Department of Cardiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands; ¹⁷Department of Emergency Medicine, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA; ¹⁸Murtala Muhammed Specialist Hospital/Bayero University Kano, Kano, Nigeria; and ¹⁹Cape Heart Institute, Department of Medicine and Cardiology, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa

*Corresponding author
Tel: +393356460581, Email: metramarco@libero.it

Conflict of interest
A.M. has received grants from Roche Diagnostics, Abbott Laboratories, 4TEEN4, and Windtree Therapeutics; honoraria for lectures from Roche Diagnostics, Bayer, and MSD; is a consultant for Corteria Pharmaceuticals, S-form Pharma, FIRE-1, Implicity, 4TEEN4, and Adrenomed; and is coinventor of a patent on combination therapy for patients having acute or persistent dyspnoea. G.C. is employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. G.C. is director of Heart Initiative, a non-profit organization. B.D. is employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. B.D. is director of Heart Initiative, a non-profit organization. A.C.S. has received honoraria for lectures or consultancy from AstraZeneca, Novartis, Vifor, Bayer, Merck, Sanofi, Abbott, and Boehringer Ingelheim. M.M. has received personal fees from Amgen, Livanova, and Vifor Pharma as a member of executive committees of sponsored clinical trials and from AstraZeneca, Bayer, Boehringer Ingelheim, Edwards Lifesciences, and Roche Diagnostics for participation to advisory boards or for speaking at sponsored meetings. C.E. is employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. O.C. received grants from Servier. R.D. has received supporting fees for coordination of STRONG-HF trial activities. G.F. has received lecture fees or was a committee member for trials and registries sponsored by Bayer, Vifor, Boehringer Ingelheim, Medtronic, Servier, and Amgen. K.S. has received grants from Medtronic, Servier, and Amylam and honoraria from MSD, Novartis, and Sanofi. A.A.V. has received consultancy fees or research support from AstraZeneca, Bayer, BMS, Boehringer Ingelheim, Cytokinetics, Myocardia, Merck, Novartis, Novo Nordisk, and Roche Diagnostics. MN is employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. KT is employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. A.D. works for the Faculty of Medicine, Eduardo Mondlane University (Maputo, Mozambique), which received research grants from the Heart Initiative for their participation in this study. P.S.P. has received grants or research contracts from American Heart Association, Roche, Siemens, Ortho Diagnostics, Abbott, Beckman Coulter, and Siemens; consulting fees from Roche; honoraria from WebMD; and he has financial interest in The Heart Course. J.C. has received personal fees from Novartis, AstraZeneca, Boehringer Ingelheim, Roche Diagnostics, and Pfizer. C.S.P.L. is supported by a Clinician Scientist Award from the National Medical Research Council of Singapore; has received research support from Bayer and Roche Diagnostics; has served as consultant or on the Advisory Board/Steering Committee/Executive Committee for Actelion, Alleviant Medical, Allysta Pharma, Amgen, AnaCardio AB, Applied Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Cytokinetics, Darma Inc., EchoNous Inc, Eli Lilly, Impulse Dynamics, Intellia Therapeutics, Ionis Pharmaceutical, Janssen Research & Development LLC, Medscape/WebMD Global LLC, Merck, Novartis, Novo Nordisk, Prosciento Inc, Radcliffe Group Ltd., Redcardio Inc, ReCor Medical, Roche Diagnostics, Sanofi, Siemens Healthcare Diagnostics and Us2.ai; and serves as co-founder and non-executive director of Us2.ai. M.P. has received personal fees from Abbott Laboratories, AstraZeneca, Boehringer Ingelheim and Vifor Pharma. MA has received speaker fees from Abbott Vascular and Medtronic. M.B. is employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. The other authors have no conflicts to report.