Abstract
Aims
We aimed to assess the impact of pre‐admission beta‐blocker (BB) therapy on the clinical characteristics, in‐hospital treatment and outcomes of patients with cardiogenic shock (CS).
Methods
All patients enrolled in the multicentre prospective Altshock‐2 registry since March 2020 with available data on pre‐admission BB therapy were included. Clinical characteristics, in‐hospital management, haemodynamic parameters and clinical outcomes were compared in patients with versus without BB therapy. The primary endpoint was in‐hospital mortality.
Results
A total of 668 patients were included [median age 66 (56–74) years, male sex 76.5%]: 299 patients (44.8%) with and 369 patients (55.2%) without previous BB therapy. Patients receiving pre‐admission BB therapy had more frequently heart failure‐related CS (43.8% vs. 17.9%) and less frequently cardiac arrest at presentation (20.1% vs. 27.8%, P = 0.027). Levosimendan was used less frequently and dobutamine was used more frequently in patients with baseline BB therapy (P = 0.033 and P = 0.043, respectively). Differences in the early haemodynamic response to vasoactive drugs were observed between patients with and without previous BB therapy, with a significant impact of baseline BB on mean arterial pressure (MAP) response during norepinephrine infusion (P = 0.012) and with dobutamine having a reduced response in MAP and heart rate in patients receiving BBs before admission (P = 0.023 and P = 0.001, respectively). In‐hospital mortality was not significantly different between the BB and no‐BB groups (40% vs. 33.7%; adjusted odds ratio 1.32, 95% confidence interval 0.84–2.07, P = 0.224). Similarly, baseline BB therapy was not independently associated with 48 h mortality (12.7% vs. 14.6%; adjusted odds ratio 1.09, 95% confidence interval 0.64–1.87, P = 0.749). The lack of association between baseline BB therapy and mortality was also confirmed at inverse probability of treatment weighting‐adjusted analysis.
Conclusions
In a real‐world, contemporary cohort of patients with CS, previous BB therapy influenced the haemodynamic response to vasoactive drugs, but it was not associated with in‐hospital mortality.
Keywords: Cardiogenic shock, beta‐blockers, inotropes, mortality, vasopressors
Among 668 with cardiogenic shock included in the multicentre prospective Altshock‐2 registry, 299 patients (44.8%) received pre‐admission beta‐blocker therapy. Previous beta‐blocker therapy influenced the early hemodynamic response to vasoactive drugs, but it was not associated with in‐hospital mortality.
Introduction
Cardiogenic shock (CS) is a syndrome with clinical and biochemical evidence of tissue hypoperfusion, which can lead to multi‐organ failure and death in a high percentage of patients (30%–60%). 1 Its management is based on the immediate stabilization of haemodynamic parameters with the use of inotropes/vasopressors and possible escalation to mechanical circulatory supports (MCSs), in addition to the management of the primary aetiology. 2 However, the most commonly used inotropes/vasopressors act by stimulating β‐adrenergic receptors and their action could be less effective in patients with previous β‐blocker therapy, which is very common in patients with pre‐existing cardiovascular disease, particularly in presence of heart failure (HF); actually, acute decompensation of HF is among the most common causes of CS. 3 , 4 Moreover, β‐blockers (BBs) have a negative inotropic and chronotropic effect that could be deleterious in unstable patients. On the other side, in the setting of acute HF needing inotropic support, BBs have been shown to reduce the rate of vasopressor/inotrope‐induced ventricular arrhythmias and the rates of premature ventricular contractions. 5 BBs at admission and discharge also resulted in lower mortality at 31 days in these patients. 6 Recently, the first data on BBs impact in patients hospitalized for CS were published 7 , 8 : in particular, in a subgroup analysis of the Dobutamine Compared with Milrinone (DOREMI) trial, patients with CS who were treated with BBs in the 24 h prior to initiating inotropic therapy, had fewer deaths and resuscitated cardiac arrest in the early resuscitation period, although this difference was no longer present at hospital discharge. Moreover, BB therapy was not associated with an impaired haemodynamic response to milrinone or dobutamine. 9 In the multicentre FRENSHOCK registry, the discontinuation of previous BBs therapy resulted in increased 1 month all‐cause mortality and a trend towards increased 1 year all‐cause mortality. 10
The aim of the present study was to compare the clinical characteristics, in‐hospital therapeutic strategies and outcomes of CS patients enrolled in the multicentre Altshock‐2 registry based on pre‐admission BB therapy.
Methods
Study design
The Altshock‐2 registry (NCT04295252) is a multicentre, prospective, observational registry enrolling consecutive patients admitted for CS at 12 Italian centres since March 2020. CS was defined and staged according to the Society for Cardiovascular Angiography and Interventions (SCAI) criteria. 11 , 12 , 13
In accordance with the EU Regulation 536/2014, all competent patients provided written informed consent, whereas consent was waived for patients who were not competent on admission. The study was conducted in accordance with ethical principles based on the Declaration of Helsinki, 14 International Conference on Harmonization for Good Clinical Practice and the current ethical rules. The Strengthening the Reporting of Observational Studies in Epidemiology Guidelines was followed for reporting study findings. 15 Only patients with known baseline use or non‐use of BBs therapy were considered for the present analysis. Patients' characteristics, in‐hospital data and clinical outcomes of all consecutively enrolled patients were collected and registered in an electronic case report form through the RedCap® platform. Laboratory, echocardiographic and haemodynamic variables, as well as the SCAI shock stages according to the updated classification, were also reported. 13
Endpoints
The primary endpoint of this study was in‐hospital mortality. Secondary outcomes were 48 h mortality, length of hospitalization, left ventricular assist device (LVAD) implantation and heart transplantation during the index admission. The in‐hospital therapeutic management and haemodynamic parameters at admission and at 24 h were also evaluated.
Statistical analysis
Continuous variables are expressed as mean ± standard deviation (SD) or median and interquartile range (IQR), as appropriate, and were compared with the Student T‐test or Mann–Whitney U‐test, respectively. Categorical variables are presented as numbers and percentages and were compared with the χ 2 or Fisher test, as appropriate. Baseline characteristics, in‐hospital data, repeated haemodynamic parameters and clinical outcomes were compared between the patients with previous BBs therapy before hospitalization and those without BBs therapy before hospitalization. The association between BB use and the change in mean arterial pressure (MAP) and heart rate (HR) between admission and 24 h was analysed with repeated measures mixed models, that were performed separately in patients treated with different inotropes/vasopressors (epinephrine, norepinephrine, dobutamine and levosimendan). Univariable and multivariable binary logistic regression analyses were performed to evaluate the impact of previous BB therapy on in‐hospital mortality and 48 h mortality. The following clinically relevant variables in the context of CS were included in the multivariable analyses: age, sex, CS aetiology, cardiac arrest at presentation, MAP at admission, lactates at admission, glomerular filtration rate (GFR) at admission, need of MCS during hospitalization, need of vasoactive treatment during hospitalization, need of respiratory support during hospitalization, need of continuous renal replacement therapy (CRRT) during hospitalization and SCAI classification at admission. Results of the analyses are reported as unadjusted or adjusted odds ratio (OR) with 95% confidence interval (CI). No imputation was performed for missing values. Propensity score methodology with inverse probability of treatment weighting (IPTW) was also performed to account for bias between patients with versus without previous BB therapy. 16 , 17 , 18 Propensity scores predicting each patient's probability of receiving pre‐admission BB were estimated with multivariable logistic regression including the following variables: age, sex, CS aetiology, cardiac arrest at presentation, MAP at admission, lactates at admission, GFR at admission, need of MCS during hospitalization, need of vasoactive treatment during hospitalization, need of respiratory support during hospitalization, need of CRRT during hospitalization and SCAI classification at admission. Stabilized weights were computed from propensity scores by means of IPTW. The weight for pre‐admission BB was the inverse of the respective propensity score, whereas the weight for the lack of pre‐admission BB therapy was the inverse of 1‐propensity score. Logistic regression models evaluating the impact of BB versus no‐BB on in‐hospital and 48 h mortality were weighted using IPTW.
Subgroup analyses were also performed to evaluate the impact of previous BB therapy on in‐hospital mortality in the following subgroups of interest: sex, age ≥75 years versus ≤75 years, CS aetiology [acute coronary syndrome (ACS) vs. non‐ACS], cardiac arrest at presentation, need of temporary MCSs, need of vasoactive drugs, need of invasive or non‐invasive respiratory support, need of CRRT, lactates ≥2 mmoL/L versus ≤2 mmoL/L, GFR < 30 mL/min versus ≥ 30 mL/min, MAP < 60 mmHg versus ≥ 60 mmHg and SCAI classifications A–C versus D–E.
Analyses were performed with SPSS V 29.0 (SPSS, Chicago, Illinois, USA) and STATA software version 16 (STATA Corp., College Station, Texas, USA). Statistical significance was set at the two‐tailed 0.05 level.
Results
Baseline characteristics and clinical presentation
Out of 725 patients enrolled in the Altshock‐2 registry, a total of 668 patients (92.1%) with available data on pre‐admission BB therapy were included in the present study: 299 (44.8%) with and 369 (55.2%) without baseline BB therapy. The most common aetiology of CS was ACS (49.3%), followed by HF‐CS in 29.5% of patients (Table 1). Patients receiving baseline BB therapy had less frequently ACS‐CS (34.8%) compared with those without BB therapy (61%). Conversely, HF‐CS was observed in 43.8% of patients in the BB group versus 17.9% in the no‐BB group (P < 0.001). SCAI stages on admission according to BB and no‐BB groups are described in Figure 1. Overall, most patients presented with SCAI stage C (52.8%). Demographic data and baseline characteristics are summarized in Table 1. Patients with BB therapy at baseline were older than patients without BB therapy [68 (IQR 59–76) vs. 64 (IQR 53–73) years, P < 0.001] and had more comorbidities, including a higher prevalence of diabetes, prior stroke or transient ischaemic attack, atrial fibrillation, prior myocardial revascularization and chronic kidney disease. Prior HF hospitalization was more common, and pre‐admission left ventricular ejection fraction (LVEF) was lower among patients with previous BB therapy; these patients were also treated more frequently with other medications for HF. Patients receiving BBs therapy had less cardiac arrest at presentation (20.1% vs. 27.8%, P = 0.027).
Table 1.
Baseline characteristics according to baseline BB therapy.
| Characteristics | Overall cohort (N = 668) | Previous BB therapy (N = 299) | No previous BB therapy (N = 369) | P value |
|---|---|---|---|---|
| Demographics | ||||
| Age (n = 666) | 66 (56–74) | 68 (59–76) | 64 (53–73) | <0.001 |
| BMI, kg/m2 (n = 643) | 25.7 (23.2–28.4) | 26 (23.6–29.4) | 25.4 (23.1–27.8) | 0.050 |
| Male sex (n = 511) | 511 (76.5) | 233 (77.9) | 273 (74) | 0.433 |
| Ethnicity (n = 565) | 0.352 | |||
| White | 525 (92.9) | 228 (93.1) | 297 (92.8) | |
| Hispanic | 10 (1.8) | 5 (2) | 5 (1.6) | |
| Asian | 8 (1.4) | 1 (0.4) | 7 (2.2) | |
| Black | 10 (1.8) | 6 (2.5) | 4 (1.2) | |
| Other | 12 (2.1) | 5 (2) | 7 (2.2) | |
| Medical history | ||||
| Previous COVID‐19 (n = 652) | 40 (6.1) | 23 (7.9) | 17 (4.7) | 0.087 |
| Smoking (n = 662) | 169 (25.5) | 57 (19.3) | 112 (30.5) | 0.001 |
| Hypertension (n = 667) | 360 (54) | 194 (65.1) | 166 (45) | <0.001 |
| Diabetes (n = 668) | 201 (30.1) | 108 (36.1) | 93 (25.2) | 0.002 |
| Dyslipidaemia (n = 667) | 278 (41.7) | 160 (53.7) | 118 (32) | <0.001 |
| Stroke or TIA (n = 666) | 43 (6.5) | 30 (10.1) | 13 (3.5) | <0.001 |
| Peripheral artery disease (n = 664) | 117 (17.6) | 77 (26.1) | 40 (10.8) | <0.001 |
| Atrial fibrillation (n = 666) | 155 (23.3) | 117 (39.3) | 38 (10.3) | <0.001 |
| CKD (n = 665) | 152 (22.9) | 113 (38) | 39 (10.6) | <0.001 |
| Anaemia (n = 668) | 76 (11.4) | 49 (16.4) | 27 (7.3) | <0.001 |
| Liver disease (n = 668) | 33 (4.9) | 20 (6.7) | 13 (3.5) | 0.060 |
| Thyroid disease (n = 667) | 94 (14.1) | 60 (20.1) | 34 (9.2) | <0.001 |
| Prior PCI (n = 666) | 163 (24.5) | 113 (37.9) | 50 (13.6) | <0.001 |
| Prior CABG (n = 665) | 60 (9) | 46 (15.5) | 14 (3.8) | <0.001 |
| ICD (n = 667) | 93 (13.9) | 83 (27.9) | 10 (2.7) | <0.001 |
| CRT‐D (n = 666) | 43 (6.5) | 38 (12.7) | 5 (1.4) | <0.001 |
| HF hospitalization (n = 656) | 98 (16.5) | 72 (29.3) | 26 (7.5) | <0.001 |
| Prior LVEF, % (n = 359) | 40 (25–55) | 35 (25–48) | 50 (40–60) | <0.001 |
| Cancer (n = 666) | 85 (12.8) | 43 (14.4) | 42 (11.4) | 0.246 |
| Waiting list for HT (n = 663) | 21 (3.2) | 19 (6.4) | 2 (0.5) | <0.001 |
| Drug history | ||||
| Periodic levosimendan (n = 663) | 25 (3.8) | 20 (6.7) | 5 (1.4) | <0.001 |
| ACE‐I (n = 666) | 108 (16.2) | 68 (22.9) | 40 (10.8) | <0.001 |
| ARB (n = 665) | 80 (12) | 51 (17.2) | 29 (7.9) | <0.001 |
| Sacubitril/valsartan (n = 664) | 73 (11) | 68 (22.9) | 5 (1.4) | <0.001 |
| Loop diuretic (n = 665) | 257 (38.6) | 197 (66.1) | 60 (16.3) | <0.001 |
| MRA (n = 663) | 167 (25.2) | 139 (47) | 28 (7.6) | <0.001 |
| SGLT2‐i (n = 215) | 29 (13.5) | 28 (32.9) | 1 (0.8) | <0.001 |
| CCB (n = 662) | 75 (11.3) | 37 (12.6) | 38 (10.3) | 0.362 |
| Anti‐arrhythmic (n = 664) | 93 (14) | 74 (24.9) | 19 (5.2) | <0.001 |
| Oral anticoagulant (n = 666) | 165 (24.8) | 123 (41.3) | 42 (11.4) | <0.001 |
| Ivabradine (n = 664) | 22 (3.3) | 14 (4.7) | 8 (2.2) | 0.067 |
| SAPT (n = 665) | 233 (35) | 154 (51.9) | 79 (21.5) | <0.001 |
| DAPT (n = 663) | 62 (9.4) | 45 (15.2) | 17 (4.6) | <0.001 |
| Statin (n = 202) | 68 (33.7) | 45 (56.2) | 23 (18.9) | <0.001 |
| Oral antidiabetics (n = 663) | 113 (17) | 66 (22.3) | 47 (12.8) | 0.001 |
| Insulin (n = 660) | 79 (12) | 53 (18) | 26 (7.1) | <0.001 |
| CS aetiology (n = 668) | <0.001 | |||
| ACS‐CS | 329 (49.3) | 104 (34.8) | 225 (61) | |
| HF‐CS | 197 (29.5) | 131 (43.8) | 66 (17.9) | |
| Acute myocarditis | 17 (2.5) | 2 (0.7) | 15 (4) | |
| PE | 15 (2.2) | 4 (1.3) | 11 (3) | |
| Other | 110 (16.5) | 58 (19.4) | 52 (14.1) | |
| Cardiac arrest at presentation (n = 627) | 153 (24.4) | 56 (20.1) | 97 (27.8) | 0.027 |
Note: Data are presented as n (% on available) and as median (IQR). Bold values represent significant P values.
Abbreviations: ACE‐I, angiotensin‐converting enzyme inhibitor; ACS‐CS, acute coronary syndrome‐cardiogenic shock; ARB, angiotensin receptor blocker; BBs, β‐blocker; BMI, body mass index; CABG, coronary artery bypass graft; CCB, calcium‐channel blocker; CKD, chronic kidney disease; COVID‐19, Coronavirus disease 2019; CRT‐D, cardiac resynchronization therapy‐defibrillator; CS, cardiogenic shock; DAPT, dual antiplatelet therapy; HF, heart failure; HF‐CS, heart failure‐cardiogenic shock; HT, heart transplant; ICD, implantable cardioverter defibrillator; IQR, interquartile range; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid receptor antagonist; PCI, percutaneous coronary intervention; PE, pulmonary embolism; SAPT, single antiplatelet therapy; SGLT2‐I, sodium‐glucose cotransporter 2 inhibitor; TIA, transient ischaemic attack.
Figure 1.
Society for Cardiovascular Angiography and Interventions (SCAI) class at admission in the whole cohort and according to baseline β‐blocker (BB) therapy.
Type of invasive monitoring, haemodynamic data, blood gas analysis, laboratory profile, echocardiographic and pulmonary artery catheter (PAC) findings are reported in Table 2. Overall, the majority of patients were monitored with invasive arterial line (96.2%) and central venous catheter (91.7%), whereas PAC was used only in 22.7% of patients. On admission, patients previously treated with BB had a slightly lower MAP [70 (IQR 60–80) vs. 71 (IQR 62–85) mmHg, P = 0.019] and higher systolic pulmonary artery pressure (PAP), mean PAP, pulmonary vascular resistance and PaO2/FiO2 ratio. In contrast, central venous pressure, cardiac output (CO), wedge pressure, lactates and central venous oxygen saturation at presentation were similar in the two groups. Of note, there was no significant difference in HR between the BB and no‐BB groups [89 (IQR 73–110) vs. 93 (IQR 79–110) bpm, P = 0.082]. On admission, patients treated with BB had lower GFR, higher C‐reactive protein and higher N‐terminal pro brain natriuretic peptide concentrations. Regarding echocardiographic data, patients with prior BB therapy had higher left ventricular end‐diastolic volume, lower tricuspid annular plane systolic excursion and a higher prevalence of severe mitral regurgitation and severe tricuspid regurgitation, whereas median LVEF was not significantly different between the BB and no‐BB groups [23 (IQR 15–30) vs. 25 (IQR 17–35) %, P = 0.327].
Table 2.
Type on invasive monitoring, haemodynamic findings, blood gas analysis, laboratory profile, echocardiographic findings and pulmonary findings according to baseline BB therapy.
| Variable | Overall cohort (N = 668) | Previous BB therapy (N = 299) | No previous BB therapy (N = 369) | P value |
|---|---|---|---|---|
| Type of invasive monitoring | ||||
| Invasive arterial pressure (n = 666) | 641 (96.2) | 281 (94.3) | 360 (97.8) | 0.017 |
| CVC (n = 664) | 609 (91.7) | 271 (90.9) | 338 (92.3) | 0.512 |
| Pulmonary artery catheter (n = 665) | 151 (22.7) | 59 (19.8) | 92 (25.1) | 0.107 |
| Haemodynamic data on admission | ||||
| SBP, mmHg (n = 646) | 95 (80–110) | 94 (80–110) | 100 (82–115) | 0.125 |
| MAP, mmHg (n = 644) | 70 (60–83) | 70 (60–80) | 71 (62–85) | 0.019 |
| HR, bpm (n = 644) | 90 (75–110) | 89 (73–110) | 93 (79–110) | 0.082 |
| CVP, mmHg (n = 424) | 12 (8–15) | 12 (8–16) | 11 (8–15) | 0.107 |
| Systolic PAP, mmHg (n = 84) | 39 (±14) | 45 (±17) | 36 (±12) | 0.004 |
| Mean PAP, mmHg (n = 84) | 28 (±11) | 32 (±12) | 26 (±9) | 0.027 |
| PCWP, mmHg (n = 71) | 20 (+7) | 22 (+6) | 19 (+7) | 0.080 |
| Cardiac output, L/min (n = 53) | 3.8 (±1) | 3.8 (±1.1) | 3.9 (±1) | 0.950 |
| Cardiac index, L/min/m2 (n = 57) | 1.98 (±0.47) | 1.96 (±0.51) | 1.99 (±0.46) | 0.834 |
| PVR, Woods unit (n = 46) | 2.3 (1.5–3.2) | 3.1 (2.1–3.9) | 2.0 (1.5–2.6) | 0.008 |
| SVR, dynes*s/cm5 (n = 39) | 1339.1 (1336–1625.5) | 1263.2 (916.7–1562.4) | 1384.6 (1226.7–1637.6) | 0.270 |
| Blood gas analysis on admission | ||||
| PaO2, mmHg (n = 629) | 98 (77–140) | 96 (78–139) | 100 (76–142) | 0.653 |
| PaO2/FiO2 ratio (n = 595) | 250 (159–361) | 266 (175–375) | 234 (146–350) | 0.010 |
| PaCO2, mmHg (n = 630) | 35 (30–42) | 34 (29–41) | 35 (30–42) | 0.225 |
| HCO3 −, mmol/L (n = 503) | 20 (17–23.1) | 20.2 (17–23.9) | 20 (17.1–23) | 0.666 |
| Lactate, mmol/L (n = 641) | 2.6 (1.6–5.3) | 2.5 (1.6–5.1) | 2.7 (1.6–5.7) | 0.308 |
| SvcO2, % (n = 323) | 62 (51–71) | 60 (50–70) | 63 (52–71) | 0.132 |
| Laboratory profile on admission | ||||
| Haemoglobin, g/dL (n = 638) | 12.7 (10.8–14.5) | 12 (10.5–13.9) | 13.2 (11.4–14.7) | <0.001 |
| Platelet count, 103/mm3 (n = 638) | 217 (163–277) | 195 (154–256) | 235 (176–292) | <0.001 |
| WBC count, 103/mm3 (n = 637) | 12.9 (9.1–17.5) | 11.7 (8.5–15.8) | 14.1 (9.5–18.4) | <0.001 |
| Glycaemia, mg/dL (n = 588) | 171 (132–243) | 168 (130–227) | 180 (134–265) | 0.032 |
| AST, U/L (n = 519) | 101 (34–338) | 64 (24–213) | 137 (49–420) | <0.001 |
| ALT, U/L (n = 457) | 71 (27–190) | 52 (24–195) | 82 (34–185) | 0.037 |
| Bilirubin, mg/dL (n = 554) | 0.8 (0.5–1.5) | 1 (0.6–1.7) | 0.8 (0.5–1.3) | 0.003 |
| GFR, ml/min (n = 620) | 56 (35–80) | 48 (28–68) | 64 (43–89) | <0.001 |
| CRP, mg/L (n = 512) | 3.4 (0.8–11.9) | 3.9 (1.1–12.6) | 2.8 (0.5–10.2) | 0.032 |
| Troponin T, ng/L (n = 213) | 962 (100–4798) | 252 (53–2372) | 1760 (176–6653) | <0.001 |
| Troponin I, ng/L (n = 379) | 2790 (247–36 541) | 850 (90–6702) | 6637 (527–95 390) | <0.001 |
| NT‐proBNP, ng/L (n = 189) | 8423 (4218–21 456) | 9403 (4956–26 996) | 6000 (2685–14 968) | 0.001 |
| Echocardiographic findings on admission | ||||
| LVEF, % (n = 541) | 25 (16–33) | 23 (15–30) | 25 (17–35) | 0.327 |
| LVEDV, mL (n = 276) | 150 (115–200) | 169 (120–248) | 135 (112–180) | <0.001 |
| Severe MR (n = 516) | 95 (18.4) | 65 (27.4) | 30 (10.8) | <0.001 |
| Severe TR (n = 490) | 64 (13.1) | 48 (21.4) | 16 (6) | <0.001 |
| TAPSE, mm (n = 407) | 15 (12–18) | 15 (12–17) | 16 (12–19) | 0.012 |
| Pulmonary findings on admission | ||||
| Bilateral B‐lines (n = 239) | 208 (87) | 97 (85.8) | 111 (88.1) | 0.538 |
| Pleural effusion (n = 241) | 98 (40.7) | 44 (37.9) | 54 (43.2) | 0.405 |
Note: Data are presented as n (% on available), as mean (SD) and as median (IQR). Bold values represent significant P values.
Abbreviations: ALT, alanine aminotransferase; AST, aspartate aminotransferase; BBs, β‐blocker; CRP, C‐reactive protein; CVC, central venous catheter; CVP, central venous pressure; GFR, glomerular filtration rate; HCO3−, bicarbonate ion; HR, heart rate; IQR, interquartile range; LVEDV, left ventricular end diastolic volume; LVEF, left ventricular ejection fraction; MAP, mean arterial pressure; MR, mitral regurgitation; NT‐proBNP, N‐terminal pro brain natriuretic peptide; PaCO2, partial pressure of carbon dioxide; PaO2, partial pressure of arterial oxygen; PAP, pulmonary artery pressure; PCWP, pulmonary capillary wedge pressure; PVR, pulmonary vascular resistance; SBP, systolic blood pressure; SvcO2, central venous oxygen saturation; SVR, systemic vascular resistance; TAPSE, tricuspid annular plane systolic excursion; TR, tricuspid regurgitation; WBC, white blood cell.
In‐hospital therapeutic management
In‐hospital management is described in Table 3. The maximum inotropic score was similar in the two groups [14 (IQR 5.5–28) vs. 15 (IQR 6–31.1), P = 0.292]. The most used adrenergic drug in β‐blocked patients was epinephrine (57.7%), while norepinephrine was the most used drug in the BB naïve group (64.4%). Regarding dobutamine administration, it was more used in patients with baseline BB therapy (46.6% vs. 38.9%, P = 0.043) and was also used at slightly higher maximum doses in this group of patients compared with patients without baseline BB. Maximum doses of epinephrine and norepinephrine were similar between BB and no‐BB groups. Levosimendan was used more frequently in patients without previous BB therapy (41.5% vs. 32.5%, P = 0.033). Sodium nitroprusside was used more frequently in BB patients (39%) as compared with BB naïve patients (30.6%, P = 0.034), and higher doses for longer duration were prescribed in the former group.
Table 3.
Therapeutic management stratified according to baseline BB therapy.
| Overall cohort (N = 668) | Previous BB therapy (N = 299) | No previous BB therapy (N = 369) | P value | |
|---|---|---|---|---|
| Vasoactive drugs | ||||
| Overall vasoactive medication (n = 662) | 617 (93.2) | 277 (93.6) | 340 (92.9) | 0.728 |
| Max inotropic score | 14.5 (5.7–30) | 14 (5.5–28) | 15 (6–31.1) | 0.292 |
| Epinephrine a | 351 (56.9) | 157 (57.7) | 194 (57.1) | 0.928 |
| Max dose, y/kg/min | 0.10 (0.05–0.13) | 0.10 (0.05–0.12) | 0.10 (0.05–0.14) | 0.986 |
| Median time of epinephrine infusion, h | 72 (24–160) | 72 (25–144) | 72 (24–174) | 0.614 |
| Levosimendan a | 231 (37.4) | 90 (32.5) | 141 (41.5) | 0.033 |
| Max dose, y/kg/min | 0.10 (0.05–0.10) | 0.10 (0.05–0.10) | 0.10 (0.05–0.10) | 0.145 |
| Median time of levosimendan infusion, h | 38 (24–48) | 44 (24–48) | 36 (24–48) | 0.277 |
| Norepinephrine a | 373 (60.5) | 154 (55.6) | 219 (64.4) | 0.035 |
| Max dose, y/kg/min | 0.15 (0.10–0.30) | 0.15 (0.10–0.30) | 0.15 (0.10–0.30) | 0.403 |
| Median time of norepinephrine, h | 48 (18–106) | 48 (24–120) | 48 (14–96) | 0.277 |
| Dobutamine a | 261 (42.3) | 129 (46.6) | 132 (38.9) | 0.043 |
| Max dose, y/kg/min | 5 (3–5.6) | 5 (4–6) | 4.7 (3–5) | 0.014 |
| Median time of dobutamine infusion, h | 48 (23–120) | 48 (24–120) | 48 (14–120) | 0.564 |
| Dopamine a | 77 (12.5) | 42 (15.2) | 35 (10.3) | 0.065 |
| Max dose, y/kg/min | 4 (2.5–5) | 3.2 (2.5–4.5) | 4 (3–5) | 0.173 |
| Median time of dopamine infusion, h | 48 (12–138) | 72 (24–192) | 24 (3–87) | 0.010 |
| Enoximone a | 15 (2.4) | 9 (3.2) | 6 (1.8) | 0.222 |
| Max dose, y/kg/min | 2.79 (±1.46) | 3.23 (±1.40) | 2.27 (±1.48) | 0.254 |
| Median time of enoximone infusion, h | 47 (±30) | 33 (23) | 61 (31) | 0.103 |
| Milrinone a | 29 (4.7) | 15 (5.4) | 14 (4.1) | 0.441 |
| Max dose, y/kg/min | 0.49 (±0.20) | 0.46 (±0.19) | 0.52 (±0.22) | 0.467 |
| Median time of milrinone infusion, h | 132 (48–366) | 120 (96–384) | 190 (18–360) | 0.622 |
| Sodium nitroprusside a | 212 (34.4) | 108 (39) | 104 (30.6) | 0.034 |
| Max dose, y/kg/min | 0.5 (0.3–0.9) | 0.6 (0.4–1.0) | 0.40 (0.25–0.80) | 0.009 |
| Median time of sodium nitroprusside, h | 96 (36–240) | 120 (70–245) | 72 (24–240) | 0.013 |
| Temporary mechanical circulatory support | ||||
| Overall tMCS (n = 663) | 430 (64.9) | 170 (57.6) | 260 (70.7) | <0.001 |
| IABP b | 346 (80.5) | 138 (81.2) | 208 (80) | 0.671 |
| IABP duration, h | 96 (48–168) | 96 (48–168) | 96 (48–172) | 0.617 |
| Impella b | 94 (21.9) | 32 (18.8) | 62 (23.8) | 0.272 |
| Impella duration, h | 117 (49–176) | 129 (72–194) | 96 (48–176) | 0.374 |
| ECMO b | 128 (29.8) | 48 (28.2) | 80 (30.8) | 0.636 |
| ECMO duration, h | 87 (48–170) | 72 (46–157) | 96 (48–191) | 0.577 |
| Other supports | ||||
| Need of respiratory support (n = 659) | 503 (76.3) | 210 (71.9) | 293 (79.3) | 0.018 |
| NIV c | 193 (38.4) | 91 (43.3) | 102 (34.8) | 0.036 |
| NIV duration, h | 48 (14–96) | 47 (11–96) | 48 (20–96) | 0.615 |
| Mechanical ventilation c | 359 (71.4) | 140 (66.7) | 219 (74.7) | 0.064 |
| Mechanical ventilation duration, h | 96 (42–240) | 72 (36–240) | 108 (48–240) | 0.089 |
| CRRT (n = 658) | 141 (21.4) | 65 (22.3) | 76 (20.8) | 0.642 |
| CRRT duration, h | 86 (38–205) | 96 (36–195) | 76 (41–231) | 0.848 |
Note: Data are presented as n (% on available), as mean (SD) and as median (IQR). Bold values represent significant P values.
Abbreviations: BBs, β‐blocker; CRRT, continuous renal replacement therapy; ECMO, extracorporeal membrane oxygenation; h, hour; IABP, intra‐aortic balloon pump; NIV, non‐invasive ventilation (both continuous positive airway pressure and bilevel ventilation); tMCS, temporary mechanical circulatory support.
Percentage among patients treated with overall vasoactive medications.
Percentage among patients treated with overall tMCS.
Percentage among patients treated with respiratory support.
Overall, short‐term MCS devices were used in 64.9% of patients, but their use was significantly lower in the BB group (57.6%) as compared with the no‐BB group (70.7%, P < 0.001; Table 3).
Effect of baseline BBs use on early response to vasoactive drugs
Figures 2 and 3 show changes in MAP and HR between admission and 24 h in patients with and without pre‐admission BB therapy; these changes were assessed separately in patients treated with different vasoactive drugs. Among patients treated with epinephrine, no significant differences were observed between the BB and no‐BB groups in terms of change in MAP and HR (Figure 2A,B). No difference in HR change was observed between the BB and no‐BB groups during norepinephrine infusion (Figure 2D). Conversely, there was a significant difference in MAP change between the two groups (Figure 2C; P = 0.012), with a higher MAP increase at 24 h among BB naïve patients as compared with patients on pre‐admission BB therapy. Among patients treated with dobutamine, there were significant differences between the BB and no‐BB groups for both haemodynamic parameters (Figure 3A,B). In detail, patients on pre‐admission BB therapy had a MAP decrease, whereas MAP slightly increased in BB naïve patients (P = 0.023). Moreover, a smaller HR decrease was observed in the BB group as compared with the no‐BB group (P = 0.001). During levosimendan infusion (Figure 3C,D), BB patients had a more pronounced MAP decrease (P = 0.022) and a slightly less pronounced HR decrease (P = 0.047), as compared with BB naïve patients.
Figure 2.
Change in haemodynamic parameters between baseline and the first 24 h according to infusion of epinephrine or norepinephrine (A, MAP during epinephrine infusion; B, HR during epinephrine infusion; C, MAP during norepinephrine infusion; D, HR during norepinephrine infusion). MAP and HR values at baseline and at 24 h are reported in the BB (red) and no‐BB (blue), along with 95% CI. BB, β‐blocker; bpm, beats per minute; CI, confidence interval; HR, heart rate; MAP, mean arterial pressure.
Figure 3.
Change in haemodynamic parameters between baseline and the first 24 h according to infusion of dobutamine or levosimendan (A, MAP during dobutamine infusion; B, HR during dobutamine infusion; C, MAP during levosimendan infusion; D, HR during levosimendan infusion). MAP and HR values at baseline and at 24 h are reported in the BB (red) and no‐BB (blue), along with 95% CI. BB, β‐blocker; bpm, beats per minute; CI, confidence interval; HR, heart rate; MAP, mean arterial pressure.
Clinical outcomes
Clinical outcomes are reported in Table 4. Patients with previous BB therapy had longer hospital stay [23 (IQR 12–39) vs. 18 (IQR 10–30) days, P = 0.024]. Overall in‐hospital mortality was 36.5%, not significantly different between the BB and no‐BB groups (40.0% vs. 33.7%, P = 0.101). Similarly, early mortality evaluated at 48 h did not differ between the two groups (12.7% vs. 14.6%, P = 0.473). Overall, 27 patients (6.3%) underwent LVAD implantation, and 30 patients (4.6%) underwent heart transplantation during index admission. The proportion of patients undergoing LVAD implantation was numerically higher, and the proportion of patients undergoing heart transplantation was significantly higher in the BB group (Table 4).
Table 4.
Clinical outcomes according to baseline BB therapy.
| Overall cohort (N = 668) | Previous BB therapy (N = 299) | No previous BB therapy (N = 369) | P value | |
|---|---|---|---|---|
| Length of hospitalization, days | 20 (11–36) | 23 (12–39) | 18 (10–30) | 0.024 |
| 48 h mortality | 92 (13.8) | 38 (12.7) | 54 (14.6) | 0.473 |
| In‐hospital mortality | 233 (36.5) | 114 (40.0) | 119 (33.7) | 0.101 |
| LVAD implantation | 27 (6.3) | 15 (8.9) | 12 (4.6) | 0.078 |
| Heart transplantation | 30 (4.6) | 21 (7.1) | 9 (2.5) | 0.004 |
Note: Data are presented as n (%) and as median (IQR). Bold values represent significant P values.
Abbreviations: BBs, β‐blocker; IQR, interquartile range LVAD, left ventricular assist device.
At univariable and multivariable analyses, there was no impact of previous BB therapy on 48 h and in‐hospital mortality (Table 5). This was also confirmed after IPTW adjustment for both 48 h mortality (IPTW‐adjusted OR 1.00, 95% CI 0.59–1.69, P = 0.992) and for in‐hospital mortality (IPTW‐adjusted OR 1.12, 95% CI 0.74–1.70, P = 0.580). At subgroup analyses, (Table 6), there was no evidence of significant interaction between previous BB therapy and all the subgroups of interest (all P values for interaction >0.100).
Table 5.
Logistic regression analysis to evaluate the impact of previous BB therapy on 48 h and in‐hospital mortality.
| Univariable analysis | Multivariable analysis | IPTW‐adjusted analysis | ||||
|---|---|---|---|---|---|---|
| Unadjusted OR (95% CI) | P value | Adjusted OR (95% CI) a | P value | IPTW‐adjusted OR (95% CI) a | P value | |
| 48 h mortality | 1.18 (0.75–1.84) | 0.473 | 1.09 (0.64–1.87) | 0.749 | 1.00 (0.59–1.69) | 0.992 |
| In‐hospital mortality | 1.31 (0.95–1.81) | 0.101 | 1.32 (0.84–2.07) | 0.224 | 1.12 (0.74–1.70) | 0.580 |
Note: Data are presented as OR and 95% CI.
Abbreviations: BB, β‐blocker; CI, confidence interval; CRRT, continuous renal replacement therapy; CS, cardiogenic shock; GFR, glomerular filtration rate; IPTW, inverse probability of treatment weighting; MAP, mean arterial pressure; OR, odds ratio; SCAI, Society for Cardiovascular Angiography and Interventions.
Covariates included in multivariable analysis are age, sex, CS aetiology, cardiac arrest at presentation, MAP at admission, lactates at admission, GFR at admission, need of MCS during hospitalization, need of vasoactive treatment during hospitalization, need of respiratory support during hospitalization, need of CRRT during hospitalization and SCAI classification at admission.
Table 6.
Impact of previous BB therapy on in‐hospital mortality in subgroups of interest.
| Subgroups | No. of events (%) in previous BB therapy | No. of events (%) without BB therapy | Previous BB therapy vs. no BB therapy within each subgroup, OR (95% CI), P value | P value for interaction a |
|---|---|---|---|---|
| Sex subgroups | 0.717 | |||
| Male | 85/222 (38.3) | 82/264 (31.1) | 1.38 (0.95–2.01), P = 0.095 | |
| Female | 29/63 (46) | 37/89 (41.6) | 1.20 (0.63–2.30), P = 0.585 | |
| Age subgroups | 0.583 | |||
| ≥75 years | 39/78 (50) | 39/82 (47.6) | 1.10 (0.59–2.05), P = 0.758 | |
| <75 years | 75/206 (36.4) | 80/270 (29.6) | 1.36 (0.93–2.00), P = 0.118 | |
| CS aetiology subgroups | 0.321 | |||
| ACS‐CS | 41/102 (40.2) | 80/218 (36.7) | 1.16 (0.72–1.88), P = 0.548 | |
| Non ACS‐CS | 73/183 (39.9) | 39/135 (28.9) | 1.63 (1.02–2.63), P = 0.043 | |
| CS presentation subgroups | 0.334 | |||
| Cardiac arrest | 23/55 (41.8) | 39/96 (40.6) | 1.05 (0.54–2.06), P = 0.886 | |
| Non‐cardiac arrest | 87/209 (41.6) | 75/237 (31.6) | 1.54 (1.05–2.27), P = 0.029 | |
| SCAI subgroups | 0.726 | |||
| A–B–C | 58/183 (31.7) | 44/208 (21.2) | 1.73 (1.10–2.73), P = 0.018 | |
| D–E | 50/78 (64.1) | 66/122 (54.1) | 1.52 (0.85–2.72), P = 0.163 | |
| tMCS subgroups | 0.353 | |||
| Yes | 61/163 (37.4) | 85/250 (34) | 1.16 (0.77–1.75), P = 0.477 | |
| No | 53/120 (44.2) | 34/103 (33) | 1.61 (0.93–2.77), P = 0.089 | |
| Vasoactive drugs subgroups | 0.302 | |||
| Yes | 111/265 (41.9) | 113/325 (34.8) | 1.35 (0.97–1.89), P = 0.077 | |
| No | 2/18 (11.1) | 5/26 (19.2) | 0.53 (0.09–3.06), P = 0.474 | |
| Respiratory support subgroups | 0.286 | |||
| Yes | 90/201 (44.8) | 99/285 (34.7) | 1.52 (1.05–2.20), P = 0.026 | |
| No | 23/78 (29.5) | 20/67 (29.9) | 0.98 (0.48–2.01), P = 0.962 | |
| CRRT subgroups | 0.149 | |||
| Yes | 37/64 (57.8) | 46/74 (62.2) | 0.83 (0.42–1.65), P = 0.603 | |
| No | 75/216 (34.7) | 73/277 (26.4) | 1.49 (1.01–2.19), P = 0.045 | |
| Lactates subgroups | 0.442 | |||
| ≥2 mmoL/L | 77/171 (45) | 87/227 (38.3) | 1.32 (0.88–1.97), P = 0.179 | |
| <2 mmoL/L | 34/105 (32.4) | 24/112 (21.4) | 1.76 (0.96–3.23), P = 0.070 | |
| GFR subgroups | 0.398 | |||
| ≥30 mL/min | 67/196 (34.2) | 85/287 (29.6) | 1.23 (0.84–1.82), P = 0.289 | |
| <30 mL/min | 42/76 (55.3) | 22/37 (59.5) | 0.84 (0.38–1.87), P = 0.673 | |
| MAP subgroups | 0.259 | |||
| ≥60 mmHg | 81/206 (39.3) | 83/273 (30.4) | 1.48 (1.01–2.17), P = 0.042 | |
| <60 mmHg | 30/69 (43.5) | 30/69 (43.5) | 1.00 (0.51–1.50), P = 1.00 | |
Note: Data are presented as HR and 95% CI. Bold values represent significant P values.
Abbreviations: ACS, acute coronary syndrome; BB, β‐blocker; CI, confidence interval; CRRT, continuous renal replacement therapy; CS, cardiogenic shock; GFR, glomerular filtration rate; HR, hazard ratio; MAP, mean arterial pressure; tMCS, temporary mechanical circulatory support.
P value for interaction = P value for interaction between patients with previous BB therapy versus no BB therapy and the subgroup of interest.
Discussion
The aim of this analysis of the Altshock‐2 registry was to compare the characteristics, therapeutic strategies and outcomes in CS patients with versus without pre‐admission BB therapy. The main findings of our study are as follows: (1) 48 h and in‐hospital mortality were similar in BB‐treated and BB naïve patients; (2) prior BB therapy influenced the early haemodynamic response to vasoactive therapy evaluated at 24 hour, as baseline BB had a significant impact on MAP change during norepinephrine and on MAP and HR changes during dobutamine or levosimendan. 2 BB therapy is one of the pillars of HF therapy in the presence of reduced LVEF 19 ; indeed, we observed that CS patients with baseline BB had more frequently HF‐CS and history of HF with lower LVEF, more HF hospitalizations and were more frequently treated with drugs for HF, implantable cardioverter defibrillator or cardiac resynchronization therapy. Although BB use in CS patients requiring inotropic support may seem counterintuitive, analyses of patients with acute HF, as well as a prospective randomized trial, have consistently shown a better outcome when BB therapy is continued or initiated in patients with acute HF. 20 , 21 , 22 These data seem confirmed also in patients with acute HF requiring inotropic support with a lower rate of vasopressor/inotropic‐induced ventricular arrhythmias and especially mortality at 31 days in patients on BBs. 5 , 6 In recent years, evidence about BB use has also accumulated for patients with CS. In a subgroup analysis of DOREMI, 9 Di Santo et al. reported fewer early deaths (within 48 h) in patients treated with BB [crude relative risk (RR) 0.41, 95% CI 0.18–0.95, P = 0.03] while this finding was not confirmed through the entire hospitalization with a non‐significant difference regarding in‐hospital mortality in patients with versus without BB (crude RR 0.86, 95% CI 0.61–1.23, P = 0.41). However, in this analysis it was not known whether BB therapy was maintained or discontinued after hospital admission.
In an analysis of the FRENSHOCK registry, Cardelli et al. compared patients who maintained or discontinued BB, but also assessed the impact of an early (within 24 h) initiation of BB therapy in patients with CS. 10 Patients receiving BB at 24 h had a non‐significant trend towards lower all‐cause mortality at 1 month (adjusted HR 0.61, 95% CI 0.34–1.1, P = 0.10). Moreover, compared with patients who discontinued BBs at 24 h, those who did not discontinue BB had lower 1 month mortality (adjusted HR 0.43, 95% CI 0.2–0.92, P = 0.03). Lastly, an early introduction of BB therapy after CS was not associated with 1 month mortality (adjusted HR 0.96, 95% CI 0.38–2.4, P = 0.93).
In contrast with the DOREMI analysis, we did not find an initial protective action of BB therapy as early mortality (at 48 h) was similar in the BB and no‐BB groups (12.7% vs. 14.6%, P = 0.473). Similarly to previous analyses by Di Santo et al. and Cardelli et al., in our study in‐hospital death was not different between the two groups (40.0% vs. 33.7%, P = 0.101). Of note, prior BB therapy was also associated with a lower risk of long‐term mortality in a previous study on miscellaneous CS. 8 Taken together, available studies seem to confirm the lack of a significant impact of previous BB therapy on in‐hospital mortality in patients with CS, that is reassuring since a non‐negligible proportion of CS patients are treated with BB prior to hospital admission, especially those with pre‐existing HF. In our study, we also did not find a significant interaction between previous BB therapy and several subgroups of interest based on sex, age or other key variables related to clinical presentation. Regretfully, we do not have data regarding interruption or prosecution of BB therapy in our registry.
Because previous BB therapy may alter the haemodynamic response during infusion of vasoactive drugs, 4 , 23 we also evaluated the haemodynamic response to different vasoactive therapies in patients with or without baseline BB. In our analysis, levosimendan was more used in BB naïve patients, while dobutamine was more used in patients with prior BB therapy. Evaluating the impact of BB on the early (24 h) haemodynamic response to vasoactive drugs infusion, we observed significant differences between the BB and no‐BB groups in terms of changes in MAP and HR during dobutamine infusion, with BB patients showing a MAP decrease while this parameter slightly increased in BB naïve patients, and with a less pronounced HR decrease in the BB group. Slight differences in MAP and HR changes between patients with versus without baseline BB were also observed during levosimendan infusion, as well as a higher MAP increase was observed among BB naïve patients during norepinephrine infusion. The impact of baseline BB on the early MAP response to norepinephrine and dobutamine may be secondary to their competitive effect on adrenergic receptors, thus influencing the catecholamine‐related increase in CO and MAP. Interestingly, in a previous small trial enrolling 227 patients with CS, those receiving BB had a lower HR when vasopressors/inotropes were at maximum doses and also lower systolic and diastolic blood pressure. 7 Analysing individual inotropes in the DOREMI trial, there was no difference between the BB and no BB groups with respect to HR and MAP variations in the first 48 h during dobutamine infusion. In the Levosimendan Infusion versus Dobutamine (LIDO) study, the use of BB had significant effects on CO increase because BB attenuated the effect of dobutamine on CO, but did not reduce that of levosimendan. 24
Of note, the pharmacological properties of different BB generations may impact on the haemodynamic response to vasoactive agents. In fact, administering dobutamine in patients previously exposed to metoprolol tartrate or carvedilol markedly attenuated its effects on invasive haemodynamic parameters (including PAP and wedge pressure decline), especially with carvedilol. 4 However, the type of BB used was not assessed in our study nor in the other analyses focused on CS patients.
In our study, the lower use of MCS and the higher rate of heart transplantation observed in the BB group may reflect differences in patient profiles at baseline. Patients with previous BB therapy had a higher prevalence of chronic HF and more advanced structural heart disease. This may be reflected in a larger percentage of those already on the waiting list for heart transplantation at the time of admission. Therefore, these patients may have been considered less suitable for temporary MCS due to their advanced disease or this may have favoured an early transition to durable therapies such as heart transplantation. Additionally, the lower frequency of cardiac arrest at presentation among BB users may have influenced the clinical decision‐making regarding the need for immediate short‐term MCS.
Limitations
Our study has several limitations. First, the present registry represents a real‐world picture of contemporary management of CS. However, patients were treated according to protocols that may vary between enrolling centres, thus potentially creating some bias in data interpretation. Furthermore, some variables had a non‐negligible number of missing values, which could have influenced the study results. Second, we reported the impact of BB as a class effect because we did not have data on BB type and dose, although the actual BB type may have an impact when evaluating the response to vasoactive therapy. Third, although it is very likely that background BB therapy was interrupted on admission due to CS in order to avoid its negative inotrope effect, this detail was not specifically collected as well as the timing of BB interruption. Fourth, although we adjusted the impact of BB on mortality for relevant covariates including CS aetiology, the different proportion of patients with history of HF and HF‐CS in the BB versus no‐BB groups still represents an important confounder and might have influenced the study findings. Finally, in the analysis on the changes in MAP and HR during vasoactive therapy in response to the presence or absence of BB therapy, some confounding factors such as the use of MCS could have influenced the findings. Furthermore, we could not evaluate the impact on other invasive haemodynamic parameters (such as CO) because PAC was used in a minority of patients.
Conclusions
In a contemporary, prospective, real‐world, multicentre cohort of patients with CS, baseline BB therapy influenced the haemodynamic response to vasoactive drugs, such as dobutamine and norepinephrine, but was not associated with early mortality at 48 h or in‐hospital mortality. These findings potentially supporting the safety of prior BB use in this high‐risk population are, however, hypothesis‐generating only. Future dedicated studies should explore whether the maintenance or early reintroduction of BB after stabilization could improve outcomes and assess the role of specific BB subtypes in modulating the haemodynamic responses and clinical trajectories in CS.
Conflict of interest statement
Dr. Pagnesi has received personal fees from Abbott Vascular, AstraZeneca, Boehringer Ingelheim, Novartis, Roche Diagnostics and Vifor Pharma. Dr. Sacco and Dr. Morici received institutional grant support from Getinge Global US; Dr. Sacco received speaker honoraria from AstraZeneca and Menarini. Dr. Marini received consulting/speaker honoraria from AstraZeneca, Orion and Abiomed. Dr. Pappalardo is a consultant for Abiomed. Dr. Metra has received consulting honoraria as a member of trial committees or advisory boards for Abbott Vascular, Actelion, Amgen, Bayer, Edwards Therapeutics, Servier, Vifor Pharma and Windtree Therapeutics. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Acknowledgements
Open access publishing facilitated by Azienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia, as part of the Wiley – SBBL agreement.
Pagnesi, M. , Riccardi, M. , Sacco, A. , Tavecchia, G. , Viola, G. , Frea, S. , Briani, M. , Bertoldi, L. F. , Bertaina, M. , Potena, L. , Valente, S. , Marini, M. , De Ferrari, G. M. , D'Ettore, N. , Cardinale, A. , Camporotondo, R. , Rota, M. , Tavazzi, G. , Morici, N. , Pappalardo, F. , Metra, M. , and Altshock‐2 investigators (2025) Pre‐admission beta‐blocker therapy and outcomes in cardiogenic shock: Insights from the Altshock‐2 Registry. ESC Heart Failure, 12: 2565–2577. 10.1002/ehf2.15322.
References
- 1. Chioncel O, Parissis J, Mebazaa A, Thiele H, Desch S, Bauersachs J, et al. Epidemiology, pathophysiology and contemporary management of cardiogenic shock—a position statement from the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail 2020;22:1315‐1341. doi: 10.1002/ejhf.1922 [DOI] [PubMed] [Google Scholar]
- 2. Riccardi M, Pagnesi M, Chioncel O, Mebazaa A, Cotter G, Gustafsson F, et al. Medical therapy of cardiogenic shock: contemporary use of inotropes and vasopressors. Eur J Heart Fail 2024;26:411‐431. doi: 10.1002/ejhf.3162 [DOI] [PubMed] [Google Scholar]
- 3. Mebazaa A, Nieminen MS, Packer M, Cohen‐Solal A, Kleber FX, Pocock SJ, et al. Levosimendan vs dobutamine for patients with acute decompensated heart failure: the SURVIVE Randomized Trial. JAMA 2007;297:1883‐1891. doi: 10.1001/jama.297.17.1883 [DOI] [PubMed] [Google Scholar]
- 4. Metra M, Nodari S, D'Aloia A, Muneretto C, Robertson AD, Bristow MR, et al. Beta‐blocker therapy influences the hemodynamic response to inotropic agents in patients with heart failure: a randomized comparison of dobutamine and enoximone before and after chronic treatment with metoprolol or carvedilol. J Am Coll Cardiol 2002;40:1248‐1258. doi: 10.1016/s0735-1097(02)02134-4 [DOI] [PubMed] [Google Scholar]
- 5. Mert KU, Mert GÖ, Morrad B, Tahmazov S, Mutlu F, Çavuşoglu Y. Effects of ivabradine and beta‐blocker therapy on dobutamine‐induced ventricular arrhythmias. Kardiol Pol 2017;75:786‐793. doi: 10.5603/KP.a2017.0094 [DOI] [PubMed] [Google Scholar]
- 6. Böhm M, Link A, Cai D, Nieminen MS, Filippatos GS, Salem R, et al. Beneficial association of β‐blocker therapy on recovery from severe acute heart failure treatment: data from the survival of patients with acute heart failure in need of intravenous inotropic support trial*. Crit Care Med 2011;39:940‐944. doi: 10.1097/CCM.0b013e31820a91ed [DOI] [PubMed] [Google Scholar]
- 7. Ryu R, Hauschild C, Bahjri K, Tran H. The usage of concomitant Beta‐blockers with vasopressors and inotropes in cardiogenic shock. Med Sci (Basel) 2022;10. doi: 10.3390/medsci10040064 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Delmas C, Orloff E, Bouisset F, Moine T, Citoni B, Biendel C, et al. Predictive factors for long‐term mortality in miscellaneous cardiogenic shock: protective role of beta‐blockers at admission. Arch Cardiovasc Dis 2019;112:738‐747. doi: 10.1016/j.acvd.2019.04.004 [DOI] [PubMed] [Google Scholar]
- 9. Di SP, Mathew R, Jung RG, Simard T, Skanes S, Mao B, et al. Impact of baseline beta‐blocker use on inotrope response and clinical outcomes in cardiogenic shock: a subgroup analysis of the DOREMI trial. Crit Care 2021;25:289. doi: 10.1186/s13054-021-03706-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Cardelli LS, Cherbi M, Huet F, Schurtz G, Bonnefoy‐Cudraz E, Gerbaud E, et al. Beta blockers improve prognosis when used early in patients with cardiogenic shock: an analysis of the FRENSHOCK Multicenter Prospective Registry. Pharmaceuticals (Basel) 2023;16:1740. doi: 10.3390/ph16121740 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Bertaina M, Morici N, Frea S, Garatti L, Briani M, Sorini C, et al. Differences between cardiogenic shock related to acute decompensated heart failure and acute myocardial infarction. ESC Heart Fail 2023;10:3472‐3482. doi: 10.1002/ehf2.14510 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Morici N, Frea S, Bertaina M, Sacco A, Corrada E, Dini CS, et al. SCAI stage reclassification at 24 h predicts outcome of cardiogenic shock: insights from the Altshock‐2 registry. Catheter Cardiovasc Interv 2023;101:22‐32. doi: 10.1002/ccd.30484 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Naidu SS, Baran DA, Jentzer JC, Hollenberg SM, van Diepen S, Basir MB, et al. SCAI SHOCK stage classification expert consensus update: a review and incorporation of validation studies. J Am Coll Cardiol 2022;79:933‐946. doi: 10.1016/j.jacc.2022.01.018 [DOI] [PubMed] [Google Scholar]
- 14. World Medical Association . World medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 2013;310:2191‐2194. doi: 10.1001/jama.2013.281053 [DOI] [PubMed] [Google Scholar]
- 15. Vandenbroucke JP, von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. PLoS Med 2007;4:e297. doi: 10.1371/journal.pmed.0040297 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Pagnesi M, Adamo M, Stolz L, Pancaldi E, Kresoja K, von Stein J, et al. Malnutrition and outcomes in patients with tricuspid regurgitation undergoing transcatheter tricuspid valve repair. Eur J Heart Fail 2025; doi: 10.1002/ejhf.3623 [DOI] [PubMed] [Google Scholar]
- 17. Benedetto U, Head SJ, Angelini GD, Blackstone EH. Statistical primer: propensity score matching and its alternatives†. Eur J Cardiothorac Surg 2018;53:1112‐1117. doi: 10.1093/ejcts/ezy167 [DOI] [PubMed] [Google Scholar]
- 18. Austin PC, Stuart EA. Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Stat Med 2015;34:3661‐3679. doi: 10.1002/sim.6607 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Authors/Task Force Members , McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, et al. 2021 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: developed by the task force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). With the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail 2022;24:4‐131. doi: 10.1002/ejhf.2333 [DOI] [PubMed] [Google Scholar]
- 20. Jondeau G, Neuder Y, Eicher J‐C, Jourdain P, Fauveau E, Galinier M, et al. B‐CONVINCED: Beta‐blocker CONtinuation vs. INterruption in patients with Congestive heart failure hospitalizED for a decompensation episode. Eur Heart J 2009;30:2186‐2192. doi: 10.1093/eurheartj/ehp323 [DOI] [PubMed] [Google Scholar]
- 21. Prins KW, Neill JM, Tyler JO, Eckman PM, Duval S. Effects of beta‐blocker withdrawal in acute decompensated heart failure: a systematic review and meta‐analysis. JACC Heart Fail 2015;3:647‐653. doi: 10.1016/j.jchf.2015.03.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Metra M, Torp‐Pedersen C, Cleland JGF, Di Lenarda A, Komajda M, Remme WJ, et al. Should beta‐blocker therapy be reduced or withdrawn after an episode of decompensated heart failure? Results from COMET. Eur J Heart Fail 2007;9:901‐909. doi: 10.1016/j.ejheart.2007.05.011 [DOI] [PubMed] [Google Scholar]
- 23. Mebazaa A, Nieminen MS, Filippatos GS, Cleland JG, Salon JE, Thakkar R, et al. Levosimendan vs. dobutamine: outcomes for acute heart failure patients on beta‐blockers in SURVIVE. Eur J Heart Fail 2009;11:304‐311. doi: 10.1093/eurjhf/hfn045 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Follath F, Cleland JGF, Just H, Papp JGY, Scholz H, Peuhkurinen K, et al. Steering Committee and Investigators of the Levosimendan Infusion versus Dobutamine (LIDO) study. Efficacy and safety of intravenous levosimendan compared with dobutamine in severe low‐output heart failure (the LIDO study): a randomised double‐blind trial. Lancet 2002;360:196‐202. doi: 10.1016/s0140-6736(02)09455-2 [DOI] [PubMed] [Google Scholar]