Age-related outcomes in patients with cardiogenic shock stratified by etiology

Abstract

BACKGROUND

As a result of improved and novel treatment strategies, the spectrum of patients with cardiovascular disease is consistently changing. Overall, those patients are typically older and characterized by increased burden with comorbidities. Limited data on the prognostic impact of age in cardiogenic shock (CS) is available. Therefore, this study investigates the prognostic impact of age in patients with CS.

METHODS

From 2019 to 2021, consecutive patients with CS of any cause were included. The prognostic value of age (i.e., 60–80 years and > 80 years) was investigated for 30-day all-cause mortality. Spearman’s correlations, Kaplan-Meier analyses, as well as multivariable Cox proportional regression analyses were performed for statistics. Subsequent risk assessment was performed based on the presence or absence of CS related to acute myocardial infarction (AMI).

RESULTS

223 CS patients were included with a median age of 77 years (interquartile range: 69–82 years). No significant difference in 30-day all-cause mortality was observed for both age-groups (54.6% vs. 63.4%, log-rank P = 0.169; HR = 1.273, 95% CI: 0.886–1.831, P = 0.192). In contrast, when analyzing subgroups stratified by CS-etiology, AMI-related CS patients of the group > 80 years showed an increased risk of 30-day all-cause mortality (78.1% vs. 60.0%, log-rank P = 0.032; HR = 1.635, 95% CI: 1.000–2.673, P = 0.050), which was still evident after multivariable adjustment (HR = 2.072, 95% CI: 1.174–3.656, P = 0.012).

CONCLUSIONS

Age was not associated with 30-day all-cause mortality in patients with CS of mixed etiology. However, increasing age was shown to be a significant predictor of increased mortality-risk in the subgroup of patients presenting with AMI-CS.

The clinical syndrome of cardiogenic shock (CS) is a medical emergency associated with high mortality and complex hemodynamic pathophysiology involving multiple organ systems.^[1] Depending on the observed patient cohort and CS etiology, in-hospital mortality ranges from 30%–50%, while CS is most commonly caused by acute myocardial infarction (AMI).^[2–5] It has been estimated that 3%–13% of all AMI are complicated by CS.^[6–9] To further stress the clinical significance of CS, it should be mentioned that approximately 32% of patients with AMI complicated by CS (AMI-CS) experience multiorgan failure.^[10]

Despite the positive impact of percutaneous coronary intervention (PCI) on clinical outcomes of patients suffering from AMI-CS, additional significant mortality-reducing interventions or treatments for CS have yet to be determined.^[11–13] Coronary artery reperfusion through PCI has substantially improved the management of AMI.^[14,15] Therefore, it can be assumed that rates of AMI deteriorating to AMI-CS are reduced through early PCI. Accordingly, incidence of AMI-CS was shown to decrease. Nonetheless, an increase in heart failure related CS (HF-CS) and generally non-AMI-related CS could be observed.^[3] Furthermore, mortality for HF-CS was shown to rise within the last decade.^[16] With the continues ageing population, the prevalence of HF and general multimorbidity is steadily increasing, raising the importance of other forms of CS besides AMI-CS.^[17–20] The complexity of managing patients admitted with multiple comorbid conditions is directly reflected in CS as incidence of multiorgan system failure in CS was shown to increase, especially in patients with higher baseline comorbidity.^[10] This observation also has implications for the economic burden of CS because treatment cost is much higher when CS is accompanied by failure of additional non-cardiac organ systems. Mainly due to increased utilization of resources and longer hospitalization.^[10]

Many parameters have been investigated for their prognostic impact in CS, but studies selectively and comprehensively assessing patients’ baseline characteristics as an indicator for short-term prognosis are limited. Given the current epidemiological trajectory with an ageing population and the comorbidities accompanied by ageing, the impact of age on prognosis in patients admitted with CS will continuously increase in relevance and therefore requires further evaluation.^[19,20]

However, prior studies often comprised few elderly patients and primarily focused on patients with AMI-CS undergoing PCI^[21–24] and receiving mechanical circulatory support (MCS), i.e., venoarterial extracorporeal membrane oxygenation^[25,26] or intra-aortic balloon pump^[27]. Consequently, the evidence concerning the prognostic value of age across different CS etiologies and in the elderly is scarce, although the significance of these cohorts is likely to increase in the future.

Therefore, our study aims to fill this knowledge gap by investigating the prognostic role of age in CS of different etiologies and patients of advanced age in a consecutively enrolled study cohort.

METHODS

Study Population, Design, and Data Collection

The present study prospectively included all consecutive patients presenting with CS of all entities on admission to the internal intensive care unit (ICU) at the University Medical Center Mannheim, Mannheim, Germany, from June 2019 to May 2021, as recently published.^[28] All relevant clinical data related to the index event were documented using the electronic hospital information system as well as the IntelliSpace Critical Care and anesthesia information system (ICCA, Philips, Philips GmbH Market DACH, Hamburg, Germany) implemented at the ICU, organizing patient data such as admission documents, vital signs, laboratory values, treatment data and consult notes. The presence of CS, as well as important laboratory data, ICU-related scores, hemodynamic measurements, and ventilation parameters were assessed on the day of admission.

The present study derived from an analysis of the “Cardiogenic Shock Registry Mannheim” (CARESMA-registry), representing a prospective single-center registry including consecutive patients presenting with CS being acutely admitted to the ICU for Internal Medicine of the University Medical Center Mannheim, Mannheim, Germany (ClinicalTrials.gov Identifier: NCT05575856). The registry was carried out according to the principles of the declaration of Helsinki and was approved by the Medical Ethics Committee II of the Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.

Inclusion and Exclusion Criteria, Study Endpoints

For the present study, all consecutive patients with CS regardless of cause were included. All patients who were < 60 years of age were excluded. Risk stratification was performed according to patients’ age on admission (i.e., 60–80 years and > 80 years).

The diagnosis of CS was determined according to the current recommendations of the Acute Cardiovascular Care Association of the European Society of Cardiology.^[29] Accordingly, CS was defined by hypotension (systolic blood pressure < 90 mmHg) for more than 30 min despite adequate filling status or need for vasopressor or inotropic therapy to achieve systolic blood pressure > 90 mmHg. Additionally, signs for end-organ hypoperfusion must be present such as oliguria with urine output < 30 mL/h, altered mental status, cold clammy skin, and increased lactate > 2 mmol/L. State of CS was classified using the SCAI (Society for Cardiovascular Angiography and Interventions) classification system.^[30]

For the present study, further risk stratification was performed according to AMI and non-AMI related CS on admission according to current international guidelines.^[15,31,32] ST-segment elevation myocardial infarction was defined as a novel elevation in the ST-segment in at least two contiguous leads with ST-segment elevation ≥ 2.5 mm in men < 40 years, ≥ 2 mm in men ≥ 40 years, or ≥ 1.5 mm in women in leads V2–V3 and/or 1 mm in the other leads. Non-ST-segment elevation myocardial infarction was defined as the presence of an acute coronary syndrome with a troponin I increase of above the 99^th percentile of a healthy reference population in the absence of ST-segment elevation, but persistent or transient ST-segment depression, inversion or alteration of T wave, or normal electrocardiogram, in the presence of a coronary culprit lesion.

The primary endpoint of the study was all-cause mortality at 30 days, which was documented using the electronic hospital information system and by directly contacting state resident registration offices (‘bureau of mortality statistics’). Identification of patients was verified by place of name, surname, day of birth, and registered living address. No patient was lost to follow-up regarding all-cause mortality at 30 days.

Statistical Analysis

Quantitative data is presented as mean ± SEM, medians (interquartile range, IQR), and ranges depending on the distribution of the data. They were compared using the independent Student’s t-test for normally distributed data or the Mann-Whitney U test for nonparametric data. Deviations from a Gaussian distribution were tested by the Kolmogorov-Smirnov test. Qualitative data are presented as absolute and relative frequencies and were compared using the Pearson’s chi-squared test or the Fisher’s exact probability test, as appropriate.

Kaplan–Meier analyses according to patient age (i.e., ≤ 80 years and > 80 years) were performed within the entire study cohort and further stratified by the presence of AMI-CS and non-AMI-CS. Univariable hazard ratios (HR) were given together with 95% confidence interval (CI). Subsequently, multivariable Cox regression models were developed using the “forward selection” option, where only statistically significant variables (P < 0.05) were included and analyzed simultaneously. Results of all statistical tests were considered significant for P-value < 0.05. All statistical analyses were performed with SPSS 25.0 (SPSS Inc., IBM, Armonk, NY, USA).

RESULTS

Study Population

From June 2019 to May 2021, 273 patients with CS were admitted to our institution. 50 patients with < 60 years of age were excluded. The final study cohort comprised 223 CS patients with a median age of 77 years (IQR: 69–82 years). The entire cohort was predominantly male (59%) but proportion of male sex was significantly different when comparing both age groups (65.1% vs. 46.5%, P = 0.008), with a higher percentage of female patients in the older cohort.

Table 1 displays further baseline characteristics of the study population divided by the age cut-off of 80 years. Vital signs and cardiovascular risk factors on admission were similar in both groups, except for smoking which was observed significantly more often in the younger group ≤ 80 years (42.8% vs. 15.5%, P = 0.001). While data on prior coronary artery disease (CAD) was alike, several other chronic conditions, i.e., congestive HF (52.1% vs. 30.9%, P = 0.002), atrial fibrillation (52.1% vs. 30.3%, P = 0.002) and chronic kidney disease (52.1% vs. 32.2%, P = 0.005) were more prevalent in older patients > 80 years. Medication on admission was comparable in both groups except for higher use of beta-blockers (70.4% vs. 50.0%, P = 0.004) and diuretics (64.8% vs. 40.1%, P = 0.001) in the group > 80 years.

Table 1. Baseline characteristics for patients stratified by age ≤ 80 years and > 80 years.

Characteristics	≤ 80 years (n = 152)	> 80 years (n = 71)	P-value
Data are presented as median (interquartile range) or n (%).
Age, yrs	71 (65–77)	84 (82–88)	0.001
Male	99 (65.1%)	33 (46.5%)	0.008
Body mass index, kg/m2	26.3 (24.2–30.1)	26.4 (24.2–30.9)	0.924
Vital signs on admission
Body temperature, °C	36.0 (35–36.5)	36.1 (35.5–36.6)	0.398
Heart rate, beats/min	87 (71–109)	82 (65–109)	0.219
Systolic blood pressure, mmHg	110 (94–133)	106 (88–130)	0.618
Respiratory rate, breaths/min	20 (16–23)	20 (17–25)	0.384
Cardiovascular risk factors
Arterial hypertension	118 (77.6%)	62 (87.3%)	0.087
Diabetes mellitus	62 (40.8%)	34 (47.9%)	0.319
Hyperlipidemia	75 (49.3%)	39 (54.9%)	0.437
Smoking	65 (42.8%)	11 (15.5%)	0.001
Prior medical history
Coronary artery disease	60 (39.5%)	34 (47.9%)	0.653
Congestive heart failure	47 (30.9%)	37 (52.1%)	0.002
Atrial fibrillation	46 (30.3%)	37 (52.1%)	0.002
Chronic kidney disease	49 (32.2%)	37 (52.1%)	0.005
Stroke	23 (15.1%)	10 (14.1%)	0.837
Chronic obstructive pulmonary disease	38 (25.0%)	9 (12.7%)	0.036
Liver cirrhosis	7 (4.6%)	0	0.066
Medication on admission
Angiotensin-converting enzyme inhibitor	58 (38.2%)	25 (35.2%)	0.672
Angiotensin II receptor blocker	29 (19.1%)	19 (26.8%)	0.194
Beta-blocker	76 (50.0%)	50 (70.4%)	0.004
Angiotensin receptor neprilysin inhibitor	6 (3.9%)	1 (1.4%)	0.311
Aldosterone antagonist	25 (16.4%)	10 (14.1%)	0.651
Diuretics	61 (40.1%)	46 (64.8%)	0.001
Acetylsalicylic acid	48 (31.6%)	23 (32.4%)	0.903
P2Y12 inhibitor	14 (9.2%)	5 (7.0%)	0.589
Statin	77 (50.7%)	33 (46.5%)	0.561

Specific CS-related information, data on medical management, results of diagnostic procedures as well as endpoints for the two patient groups is illustrated in Table 2. Coronary angiography was performed similarly often in both groups (69.1% vs. 64.8%, P = 0.523). Status of CAD was observed to differ with 3-vessel disease being found more commonly in the older patient group > 80 years (73.9% vs. 53.3%, P = 0.012). Nonetheless, PCI was carried out more frequently in the younger group ≤ 80 years (75.2% vs. 56.5%, P = 0.021). Most CS cases were caused by AMI (49.3% vs. 45.1%) and acute decompensated HF (25.8% vs. 33.8%) whereas no statistically significant differences in CS-etiology between the younger and older patient cohort were observed (P = 0.815). Patients ≤ 80 years were more often classified as having advanced stage CS (i.e., stage E) (57.2% vs. 36.6%, P = 0.025). Furthermore, the rate of out-of-hospital cardiac arrest was higher in the younger group ≤ 80 years (40.1% vs. 22.5%, P = 0.012). Likewise, mechanical ventilation on admission (59.9% vs. 39.4%, P = 0.004) was more frequent in younger patients. Regarding laboratory values at baseline, only pH and white blood cell count showed significant differences, with lower pH (7.28 vs. 7.32, P = 0.017) and higher white blood cell count (15.48 × 10⁶/mL vs. 12.24 × 10⁶/mL, P = 0.002) in the younger group ≤ 80 years.

Table 2. Shock-related data, follow-up data and endpoints of patients differentiated by age ≤ 80 years and > 80 years.

Variables	≤ 80 years (n = 152)	> 80 years (n = 71)	P-value
Data are presented as median (interquartile range) or n (%).
Coronary angiography	105 (69.1%)	46 (64.8%)	0.523
Status of coronary artery disease			0.012
No evidence of coronary artery disease	6 (5.7%)	5 (10.9%)
1-vessel disease	18 (17.1%)	5 (10.9%)
2-vessel disease	25 (23.8%)	2 (4.3%)
3-vessel disease	56 (53.3%)	34 (73.9%)
Affected coronary arteries
Left main trunc	15 (14.3%)	5 (10.9%)	0.569
Left anterior descending	62 (59.0%)	28 (60.9%)	0.834
Left circumflex	51 (48.6%)	24 (52.2%)	0.684
Right coronary artery	58 (55.2%)	28 (60.9%)	0.520
Percutaneous coronary intervention	79 (75.2%)	26 (56.5%)	0.021
Number of stents	1 (0–3)	1 (0–3)	0.355
Coronary artery bypass grafting	11 (10.5%)	5 (10.9%)	0.942
Chronic total occlusion	25 (23.8%)	18 (39.1%)	0.055
Etiology of cardiogenic shock			0.815
Acute myocardial infarction	75 (49.3%)	32 (45.1%)
Arrhythymic	14 (9.2%)	8 (11.3%)
Acute decompensated heart failure	39 (25.8%)	24 (33.8%)
Valvular	6 (3.9%)	3 (4.2%)
Cardiomyopathy	3 (2.0%)	1 (1.4%)
Pulmonary embolism	10 (6.6%)	2 (2.8%)
Pericardial tamponade	4 (2.6%)	1 (1.4%)
Aortic dissection	1 (0.7%)	0
Society for Cardiovascular Angiography and Intervention classification of cardiogenic shock			0.025
Stage B	4 (2.6%)	1 (1.4%)
Stage C	50 (32.9%)	37 (52.1%)
Stage D	11 (7.2%)	7 (9.9%)
Stage E	87 (57.2%)	26 (36.6%)
Transthoracic echocardiography			0.265
Left ventricular ejection fraction > 55%	14 (9.2%)	7 (9.9%)
Left ventricular ejection fraction 54%–41%	19 (12.5%)	5 (7.0%)
Left ventricular ejection fraction 40%–30%	39 (25.7%)	14 (19.7%)
Left ventricular ejection fraction < 30%	70 (46.1%)	35 (49.3%)
Left ventricular ejection fraction not documented	10 (6.6%)	10 (14.1%)
Vena cava inferior, cm	1.8 (1.5–2.2)	2.0 (1.6–2.3)	0.254
Tricuspid annular plane systolic excursion, mm	15 (11–20)	13 (11–18)	0.258
Cardiopulmonary resuscitation
Out-of-hospital cardiac arrest	61 (40.1%)	16 (22.5%)	0.012
In-hospital cardiac arrest	26 (17.1%)	10 (14.1%)
Shockable rhythm	43 (28.3%)	14 (19.7%)	0.172
Non-shockable rhythm	109 (71.7%)	57 (80.3%)
Return of spontaneous circulation, min	15 (10–20)	12 (4–30)	0.536
Respiratory status
Mechanical ventilation	91 (59.9%)	28 (39.4%)	0.004
Duration of mechanical ventilation, days	2 (1–5)	1 (0–3)	0.277
Partial pressure of oxygen/Fraction of inspired oxygen ratio	202 (131–367)	258 (147–339)	0.410
Partial pressure of oxygen, mmHg	107 (75–161)	106 (76–161)	0.725
Multiple organ support during internal intensive care unit
Norepinephrine dose on admission, µg/kg per min	0.1 (0–0.3)	0.1 (0–0.2)	0.170
Mechanical circulatory assist device	12 (7.9%)	1 (1.4%)	0.054
Baseline laboratory values
pH	7.28 (7.17–7.36)	7.32 (7.26–7.39)	0.017
Lactate, mmol/L	3.3 (1.7–8.2)	2.7 (1.6–5.8)	0.144
Sodium, mmol/L	138 (135–141)	137 (136–141)	0.649
Potassium, mmol/L	4.3 (3.8–4.9)	4.4 (4.0–5.3)	0.414
Creatinine, mg/dL	1.51 (1.21–2.19)	1.54 (1.17–2.63)	0.635
Hemoglobin, g/dL	12.4 (10.3–14.2)	12.0 (9.9–13.5)	0.144
White blood cells, × 106/mL	15.48 (11.21–18.58)	12.24 (8.31–17.10)	0.002
Platelets, × 106/mL	217 (169–267)	210 (164–264)	0.834
International normalized ratio	1.17 (1.08–1.40)	1.18 (1.09–1.34)	0.672
D-dimer, mg/L	14.20 (2.04–32)	5.38 (2.46–11.82)	0.118
Aspartate aminotransferase, U/L	137 (49–413)	94 (34–185)	0.085
Alanine aminotransferase, U/L	89 (32–217)	61 (25–123)	0.114
Bilirubin, mg/dL	0.62 (0.42–0.93)	0.80 (0.46–1.21)	0.127
Troponin I, µg/L	0.730 (0.143–6.116)	0.812 (0.182–5.468)	0.967
N-terminal pro-B-type natriuretic peptide, pg/mL	4122 (776–14,262)	9912 (3552–21,244)	0.057
Procalcitonin, ng/mL	0.28 (0.12–2.33)	0.24 (0.05–0.39)	0.119
C-reactive protein, mg/L	12 (4–42)	21 (4–54)	0.340
Primary endpoint
All-cause mortality at 30 days	83 (54.6%)	45 (63.4%)	0.217
Follow-up data
Internal intensive care unit time, days	4 (2–7)	3 (1–6)	0.116
Death internal intensive care unit	81 (53.3%)	45 (63.4%)	0.157

Correlation of Age with Clinical and Laboratory Data

Table 3 outlines univariable correlations of age and selected parameters. Patients’ age correlated positively with levels of N-terminal pro-B-type natriuretic peptide (r = 0.268, P = 0.015). In contrast, an inverse correlation of age and the administered dose of norepinephrine on admission (r = -0.169, P = 0.014) was demonstrated.

Table 3. Correlations of age with laboratory and clinical parameters in all patients.

Variables	r	P-value
Body mass index, kg/m2	-0.095	0.171
Heart rate, beats/min	-0.043	0.533
Systolic blood pressure, mmHg	0.011	0.869
Partial pressure of oxygen/Fraction of inspired oxygen ratio	0.047	0.525
Partial pressure of oxygen	-0.042	0.558
Norepinephrine dose, µg/kg per min	-0.169	0.014
Lactate, mmo/L	-0.055	0.426
Cardiac troponin I, µg/L	0.029	0.708
N-terminal pro-B-type natriuretic peptide, pg/mL	0.268	0.015
C-reactive protein, mg/L	0.083	0.242

Association of Age with 30-day All-cause Mortality

The primary endpoint of all-cause mortality at 30 days was observed in 54.6% of the cohort ≤ 80 years and in 63.4% of the cohort > 80 years (log-rank P = 0.169). No significant difference regarding the risk of 30-day all-cause mortality was observed when comparing the group of patients ≤ 80 years with patients > 80 years (HR = 1.273, 95% CI: 0.886–1.831, P = 0.192) (Figure 1A). When further analyzing the subgroups of AMI-CS and non-AMI-CS patients, AMI-CS was shown to be associated with worse mortality in older patients > 80 years (78.1% vs. 60.0%, log-rank P = 0.032, HR = 1.635, 95% CI: 1.00–2.673, P = 0.05) while non-AMI-CS was not (51.3% vs. 49.4%, log-rank P = 0.878, HR = 1.042, 95% CI: 0.606–1.791, P = 0.881) (Figure 1B & 1C).

Figure 1.

Kaplan-Meier analyses.

Prognostic impact of age on the risk of 30-day all-cause mortality for the entire study cohort (A), patients with AMI-CS (B), and non-AMI-CS (C). AMI: acute myocardial infarction; CS: cardiogenic shock.

Multivariable Risk Prediction Models

Univariable and multivariable Cox regression analyses were performed within the AMI-CS and non-AMI-CS cohorts. To take the important syndrome of frailty into account, biomarkers and comorbidities associated with frailty were incorporated in the analyses (i.e., hemoglobin, C-reactive protein and malignancy).^[33–35] Even after multivariable adjustment, age (i.e., cut-off of 80 years) was associated with 30-day all-cause mortality within the cohort of AMI-CS (HR = 2.072, 95% CI: 1.174–3.656, P = 0.012). Additionally, when age was included as a continuous variable, it remained an independent predictor of all-cause mortality in patients with AMI-CS (HR = 1.035, 95% CI: 1.002–1.069, P = 0.039) (Table 4).

Table 4. Univariable and multivariable Cox regression analyses in patients with AMI-CS and non-AMI-CS regarding 30-day all-cause mortality.

Variables	AMI-CS								Non-AMI-CS
	Univariable				Multivariable				Univariable				Multivariable
	HR	95% CI	P-value		HR	95% CI	P-value		HR	95% CI	P-value		HR	95% CI	P-value
*Referred to multivariable Cox regression model for age included as continuous variable was adjusted for malignancy, creatinine, lactate, hemoglobin, C-reactive protein, and cardiopulmonary resuscitation. AMI: acute myocardial infarction; CS: cardiogenic shock; HR: hazard ratios.
Creatinine, mg/dL	1.222	1.058–1.412	0.007		1.097	0.904–1.331	0.349		1.086	0.950–1.242	0.224		1.112	0.945–1.308	0.200
Lactate, mmo/L	1.128	1.081–1.177	0.001		1.113	1.052–1.179	0.001		1.138	1.079–1.201	0.001		1.108	1.036–1.185	0.003
Hemoglobin, g/dL	0.938	0.848–1.037	0.208		1.003	0.903–1.114	0.955		1.066	0.959–1.185	0.239		1.071	0.956–1.199	0.237
C-reactive protein, mg/L	1.003	0.998–1.008	0.232		1.002	0.996–1.008	0.495		0.998	0.993–1.003	0.470		0.999	0.994–1.004	0.588
Malignancy	1.096	0.588–2.041	0.773		1.129	0.556–2.292	0.737		1.108	0.597–2.053	0.746		0.874	0.407–1.875	0.729
Cardiopulmonary resuscitation	1.234	0.900–1.691	0.192		1.210	0.830–1.763	0.321		2.137	1.515–3.016	0.001		1.807	1.191–2.741	0.005
> 80 years of age	1.635	1.000–2.673	0.050		2.072	1.174–3.656	0.012		1.042	0.606–1.791	0.881		1.274	0.676–2.400	0.453
Age*, yrs	1.025	0.998–1.053	0.073		1.035	1.002–1.069	0.039		1.002	0.969–1.036	0.918		1.001	0.963–1.040	0.963

In the cohort of non-AMI-CS, age was not associated with an increased risk of all-cause mortality at 30 days (HR = 1.274, 95% CI: 0.676–2.400, P = 0.453). However, lactate levels and the need for cardiopulmonary resuscitation were associated with higher mortality in univariable and multivariable Cox regression within the cohort of non-AMI-CS (Table 4).

DISCUSSION

This prospective observational study comprehensively investigated the prognostic value of age in consecutive patients with AMI and non-AMI-related CS admitted to an internal ICU between 2019 and 2021. There was no statistical difference in 30-day all-cause mortality when comparing CS patients of different age groups (i.e., ≤ 80 years and > 80 years). Selective analyses stratified by CS-etiology (i.e., AMI-CS vs. non-AMI-CS) demonstrated a significantly increased mortality-risk in AMI-CS patients of the age group > 80 years, which was still evident after multivariable adjustment. Conversely, no difference in prognosis was observed when comparing the two age groups in the non-AMI-CS cohort.

Ageing is known to be a significant and independent risk factor for the development of cardiovascular disease (CVD) and many other conditions such as chronic kidney disease, hypertension, or type 2 diabetes mellitus. Therefore, elderly patients usually present with worse cardiovascular risk profile and generally more comorbidities when compared to their younger counterparts.^[19,36] Besides multimorbidity, age is often accompanied by polypharmacy, frailty, and reduced functional reserve, continuously adding complexity to the management of CVD.^[37,38]

Given these circumstances, there are relevant differences in the treatment and prognosis of elderly individuals with CVD. Studies investigating HF in the elderly have established that even diagnosing HF is challenging because symptoms are more frequently atypical and can be disguised or simulated by comorbidities.^[39] In turn, delayed diagnosis and initiation of adequate treatment further contribute to worse outcomes.^[40] However, patients of higher age are also less likely to receive guideline-directed treatments even after HF diagnosis^[41,42] and the current recommendations for the management of HF are mainly based on evidence of clinical trials that have often excluded older patients despite this population being the most affected.^[43,44]

Regarding AMI and CAD, adequate diagnosis in older patients also seems to be influenced by atypical symptoms and presentation, leading to delayed contact to medical professionals and initiation of therapy.^[45–47] Furthermore, assessing eligibility for interventional reperfusion in older individuals remains complex and often culminates in less frequent utilization of PCI.^[46,48] Even though, its prognostic benefits seem to be maintained in patient of advanced age.^[49,50]

Despite the progressive ageing of the population and continuous increases in the rates of CVD, elderly patients remain underrepresented in clinical trials or registries investigating cardiovascular conditions related to strict exclusion criteria in randomized controlled trials.^[51,52] This results in a lack of knowledge concerning the prognosis and management of this increasingly relevant cohort. The absence of reliable data in this cohort could prompt clinicians to more conservative treatment approaches which may diverge substantially from guideline recommendations. Therefore, investigating the prognostic impact of age, especially in very acute conditions such as CS, is paramount.

Previous studies and scoring systems have predominantly established age cut-offs between 65–75 years.^{[4,24,53–55]} However, most prior studies investigated patient cohorts that were younger than our cohort [e.g., RESCUE^[53]: mean age of 66 ± 14 years; SHOCK trial^[56]: mean age of 68.7 ± 11.8 years; CardShock^[4]: mean age of 67 ± 12 years; Cardiovascular Shock^[57]: median age of 72 years (IQR: 63–81 years); compared to our cohort: median age of 77 years (IQR: 69–82 years)]. Especially the Cardiovascular Shock Registry did not observe age to be associated with impaired survival. However, the authors themselves note that this could have been attributable to their relatively low number of elderly patients.^[57] Considering the progressively increasing life expectancy, advancing treatment capabilities, high median age of our cohort and lack of data in patients at very advanced age; we decided to set the age cut-off slightly higher than previous studies (i.e., ≤ 80 years and > 80 years). In addition, prior investigations in patients with acute HF as a possible cause of CS observed the steepest increase in mortality between the age groups 75–84 years and 85–94 years.^[41] Due to the high proportion of CS related to acute decompensated HF in our cohort (25.8% and 33.8% in the groups ≤ 80 years and > 80 years, respectively), we wanted to take these findings into account to improve discrimination of effects on mortality. Patients < 60 years of age were excluded because of the high heterogeneity regarding comorbidities within this cohort. These patients commonly suffer from less comorbidities than patients at a more advanced age. Since we wanted to compare the prognosis of old versus very elderly patients, we decided it was appropriate to exclude those < 60 years.

The current state of evidence suggests that advanced age may be associated with higher mortality rates in patients suffering from CS.^[4,36,53,54] This finding was primarily attributed to age-related factors like the aforementioned multimorbidity, frailty or reduced functional reserve. While higher comorbidity among older patients was also present in our study, mortality did not differ between the two age groups when considering the entire cohort. Even though our entire study cohort was predominantly male, the percentage of female patients increased significantly in the cohort > 80 years (34.9% vs. 53.5%) which is also in line with investigations from Jentzer, et al.^[54] and Kanwar, et al.^[36] A high proportion of females is a notable finding since they are generally underrepresented in CS studies.^[58–60] It suggests that the emergency of CS could progressively affect more females as average life expectancy increases.

Even though significance of non-AMI-CS was observed to increase,^[3,16] selective analyses of CS mortality in different age groups stratified by CS-etiologies besides AMI-CS were beyond most previous studies. Data derived from studies that did in fact perform such analyses is heterogeneous, especially due to differences in the chosen age cut-offs and inclusion of CS-etiologies in the non-AMI-CS cohorts. Kanwar, et al.^[36] divided their cohort into AMI-CS and strictly HF-CS. Statistically significant higher mortality rates in older patients were only found in the HF-CS group. However, a trend towards higher mortality was also observed in the AMI-CS group. Osman, et al.^[61] performed age stratified sex-related differences in CS patients which is not entirely applicable to our study settings and selective analysis for age alone was not performed. Nonetheless, their data also suggests increasing mortality with advancing age as well as generally higher mortality in AMI-CS when compared to non-AMI-CS.

In our study population, selective analyses stratified by CS-etiology (i.e., AMI-CS vs. non-AMI-CS) demonstrated significantly higher 30-day all-cause mortality in AMI-CS patients > 80 years but no age-related difference in the non-AMI-CS cohort. It should be noted that mortality rates of both age groups in the AMI-CS cohort were rather high (60% and 78%), compared to prior studies investigating AMI-CS patients.^[13,62,63] Since advanced age as well as CS stage have been shown to predict higher mortality, this could be attributable to the high median age of our entire cohort (77 years) and the circumstance that of all patients, 50.7% of patients presented with advanced CS (the Society for Cardiovascular Angiography and Intervention stage E).^[54] Of note, median age in CS patients included in randomized controlled trials varies from 66–71 years.^[13,62–64] Furthermore, distribution of CS severity can show substantial differences between studies due to the use of varying definitions of classifying CS.^[54]

Regarding treatment approaches in the entire cohort, more intensive medical management, including mechanical ventilation and invasive coronary revascularization (PCI), was observed in the younger patient group ≤ 80 years. Although, coronary angiography rates were similar in both groups and status of detected CAD severity was even worse among older patients. This suggests that many older patients may have been ineligible for PCI or that physicians were often reluctant to perform invasive revascularization, potentially due to age-related reasons such as higher morbidity, assumed risk or limited life expectancy. This finding may have the greatest impact on mortality, especially in the subgroup of patients with AMI-CS, as PCI is currently the only medical intervention that was shown to reduce mortality in randomized clinical trials.^[13,65] In addition, the use of mechanical circulatory assist devices only narrowly missed the level of statistical significance for higher use in younger patients (7.9% vs. 1.4%, P = 0.054). This could be cautiously interpreted as a statistical trend further corroborating more extensive medical treatment in younger patients and would be in line with observations in prior CS studies.^[3,54,55] However, routine use of MCS devices like the intra-aortic balloon pump have not been shown to improve survival in AMI-CS patients and their utilization is associated with additional inherent risks, such as vascular complications, risk of infection, bleeding or mechanical malfunction.^[63,66] Furthermore, age was shown to be a major predictor of worse outcomes in several studies investigating the use of extracorporeal membrane oxygenation.^[67,68] Finally, the potential benefit of MCS devices must be weighed carefully against their complications, especially because older patients might have decreased physiologic reserve which could render them unable to withstand these complications.^[69] Nonetheless, advanced age should be considered together with other factors, such as baseline comorbidity or clinical presentation, when determining the utilization of interventional revascularization or initiation of MCS devices and it should not be viewed as an absolute contraindication if cardiac recovery seems feasible.^[70] Our findings, particularly the higher mortality observed in older AMI-CS patients > 80 years, underscore the importance of a comprehensive risk assessment in clinical decision-making and further research is needed to identify patients of advanced age where the benefit of escalating medical management outweighs the potential risks.

LIMITATIONS AND STRENGTHS

This study has several limitations. Due to the single-center and observational study design, results may be influenced by measured an unmeasured confounding regardless of performing multivariable Cox regression to adjust for potential confounders. Further, we only observed a modest sample size and patients with out-of-hospital cardiac arrest not transferred to our institution could not be included in the study. In addition, no information on mortality beyond 30 days was available for the present study.

Despite these limitations, our study provided relevant data investigating the prognostic impact of age in CS patients through comprehensive statistical analysis of a diverse patient cohort presenting with CS. Unlike previous studies where predominantly younger patients and AMI-CS were investigated, our study cohort was characterized by high median-age and CS caused by different pathologic conditions. Furthermore, patients were enrolled consecutively, ensuring a more randomized and representative study cohort.

CONCLUSIONS

In conclusion, our study demonstrated that 30-day all-cause mortality was not associated with patient age in a CS cohort of different etiology, while medical management showed significant disparities in patients with advanced age. The selective group of patients with AMI-CS was observed to be at higher risk of mortality when compared to non-AMI-CS with higher age being an impactful factor contributing to higher mortality in this cohort.