Association of hemoglobin with incidence of in-hospital cardiac arrest in patients with acute coronary syndrome complicated by cardiogenic shock

Abstract

Objective

This study was performed to investigate the association of the admission hemoglobin level with the incidence of in-hospital cardiac arrest (IHCA) in patients with acute coronary syndrome (ACS) complicated by cardiogenic shock (CS).

Methods

In this retrospective study, we reviewed the medical records of consecutive patients with ACS complicated by CS admitted to the coronary care unit from January 2014 to October 2017. Logistic regression models were carried out to evaluate the association between hemoglobin and the incidence of IHCA. Interaction and subgroup analyses were also performed.

Results

In total, 211 patients were included in the study, and 61 (28.9%) patients developed IHCA. In the multivariable analysis, hemoglobin was a strong independent predictor of IHCA (odds ratio, 0.971; 95% confidence interval, 0.954–0.989). In the fully adjusted model, patients in the higher hemoglobin tertile were less likely to develop IHCA than patients in the lowest hemoglobin tertile (odds ratio, 0.194; 95% confidence interval, 0.071–0.530). The relationship remained stable in most subgroups except patients aged ≥70 years.

Conclusion

In patients with ACS complicated by CS, the incidence of IHCA is related to the hemoglobin concentration, and a high hemoglobin concentration is a protective factor against the development of IHCA.

Keywords

Hemoglobin in-hospital cardiac arrest incidence predictor acute coronary syndrome cardiogenic shock

Abbreviations

IHCA, in-hospital cardiac arrest; ACS, acute coronary syndrome; CS, cardiogenic shock; CCU, coronary care unit; BNP, brain natriuretic peptide; OR, odds ratio; CI, confidence interval.

Introduction

In-hospital cardiac arrest (IHCA) is defined as cessation of cardiac activity as confirmed by the absence of signs of circulation in a hospitalized patient who had a pulse at the time of admission.¹ Because survival to discharge after IHCA remains poor (10%–22%),^2–6 prevention of this event is crucial. Although systematic research has been performed in an attempt to prevent cardiac arrest by recognizing clinical deterioration in patients, the incidence of IHCA has remained largely unchanged.^7–10 Additional studies are needed to reduce the incidence rate.

Several studies have shown that patients with hemodynamic instability are more liable to develop cardiac arrest.^11–13 Cardiogenic shock (CS) is a condition of hemodynamic instability with particularly high mortality.^14–16 CS is defined as a state of end-organ hypoperfusion due to reduced cardiac output, and it is caused by acute coronary syndrome (ACS).^14,15,17 Thus, it is necessary to identify patients with CS who have a high risk of developing cardiac arrest, especially IHCA.

Respiratory problems and deterioration of the mental status are considered predictors of IHCA.^11–13 However, data on the association between anemia and IHCA are sparse. Previous studies have shown that anemia is closely associated with a high risk of cardiovascular adverse events.^18–21 Thus, we hypothesized that patients with a low hemoglobin level are more likely to develop IHCA. In this study, we investigated the relationship between the hemoglobin level and the incidence of IHCA in patients admitted with ACS complicated by CS.

Materials and methods

Population

This retrospective study was performed at the First Affiliated Hospital of Wenzhou Medical University. Patients were included if they had been diagnosed with ACS and admitted to the coronary care unit (CCU) from January 2014 to October 2017. To investigate the prognostic role of the hemoglobin level in patients with CS, patients who did not meet the diagnostic criteria for CS were excluded. To identify patients with CS, we used the following three criteria of the Intraaortic Balloon Pump in Cardiogenic Shock II trial¹⁴: systolic blood pressure of <90 mmHg for ≥30 minutes or the need for catecholamines to maintain the systolic blood pressure at >90 mmHg, clinical pulmonary congestion, and impaired end-organ perfusion (altered mental status, cold/clammy skin and extremities, urine output of <30 mL/h, or lactate level of >2.0 mmol/L). Because this was a retrospective study based on medical records, ethics approval and written informed consent were not obtained.

Data collection

Each patient’s clinical data (demographic data, medical history, and vital signs) were collected upon admission to the CCU. Patients were considered to have hypertension or diabetes mellitus based on a previous diagnosis in their medical records or a history of use of related drugs. Blood samples were also collected upon admission. Laboratory data were obtained from the electronic medical record system. Echocardiography and electrocardiography were performed within the first 72 hours, and the left ventricular ejection fraction was recorded. All of the main treatments and surgeries performed before IHCA were recorded.

Definition of IHCA

According to the guidelines (the Utstein Style for in-hospital resuscitation research) that were established to assure a uniform standard for management of IHCA, we diagnosed IHCA in patients who had a pulse at the time of admission but subsequently had no detectable pulse, were unresponsive, and exhibited apnea or agonal respirations.¹

Statistical methods

The tertiles of the whole population were categorized separately as follows: T1, hemoglobin of ≤112 g/L; T2, hemoglobin of 113 to 133 g/L; and T3, hemoglobin of ≥134 g/L. We established multiple logistic regression models to evaluate the associations between the hemoglobin level and the incidence of IHCA. Both unadjusted and multivariate adjusted models were applied. Model 1 was a univariate analysis for hemoglobin. Model 2 was used to estimate the odds for hemoglobin after adjusting for sex and age. Model 3 was adjusted for sex, age, coronary revascularization, hypertension, diabetes mellitus, ventricular arrhythmias at admission, brain natriuretic peptide (BNP), creatinine, and lactate. We selected these confounders on the basis of their associations with outcomes or a change in the effect estimate of >10%. The odds ratios (ORs) with 95% confidence intervals (CIs) and P values for IHCA were reported after adjusting for confounding variables across each tertile of the hemoglobin concentration.

Interaction and subgroup analyses were performed in different groups: age (<70 and ≥70 years), sex (male and female), smoking status (never-smokers and smokers), ventricular arrhythmias at admission, hypertension, diabetes mellitus, and other factors. All confounding variables were adjusted in each stratification (sex, age, coronary revascularization, hypertension, diabetes mellitus, ventricular arrhythmias, BNP, creatinine, and lactate) except the stratification factor itself.

Continuous variables are presented as mean ± standard deviation or median (interquartile range) for variables with a skewed distribution. Categorical variables are presented as number and percentage. The characteristics of the study population according to hemoglobin trisectors were compared using one-way analysis of variance or the Kruskal–Wallis test for continuous variables and the X² test for categorical variables. All tests were two-sided, and a P value of <0.05 was considered significant. Analyses were performed using the statistical software packages R (http://www.R-project.org) and EmpowerStats (X&Y Solutions, Inc., Boston, MA, USA; http://www.empowerstats.com).

Results

Baseline characteristics of study population

In total, 1900 patients admitted to the CCU for ACS in the First Affiliated Hospital of Wenzhou Medical University were initially enrolled in the study. After exclusion of patients who did not satisfy the CS criteria, 211 patients with CS were considered eligible for the main analyses of the association between the hemoglobin level and the incidence of IHCA. The distribution of the baseline hemoglobin level is shown in Figure 1. The patients were classified into three groups by hemoglobin level: T1 (≤112 g/L), T2 (113–133 g/L), and T3 (≥134 g/L). Table 1 shows the characteristics of the overall study population and the characteristics of patients according to their tertile measurements of hemoglobin. A total of 61 (28.9%) patients developed IHCA among all 211 patients. In the T1 group (≤112 g/L), 28 (40.6%) of 69 patients developed IHCA, while in the T3 group (≥134 g/L), only 13 (17.6%) of 74 patients developed IHCA. Overall, the patients’ mean age was 69.6 ± 12.3 years, and 138 (65.4%) were men. More than half of the patients had hypertension (61.1%). The patients’ medical history also included a smoking history in 69 (32.7%) patients, a drinking history in 31 (14.7%), diabetes mellitus in 73 (34.6%), and ventricular arrhythmia at admission in 46 (21.8%). Compared with patents in the T1 group, those in T3 were younger, had a male preponderance, and had a lower incidence of hypertension. Vital signs at admission, laboratory test results, echocardiography indices, and surgery-related data during the hospital stay are shown in Table 1.

Figure 1.

Distribution of baseline hemoglobin levels.

Table 1.

Characteristics of study patients.

Characteristics	Overall	Tertiles of hemoglobin (g/L) among all 211 patients
Characteristics	Overall	T1 (≤112)	T2 (113–133)	T3 (≥134)	P value
Patients, n	211	69	68	74
IHCA	61 (28.9)	28 (40.6)	20 (29.4)	13 (17.6)	0.010
Demographics
Age, years	69.6 ± 12.3	73.5 ± 11.5	71.3 ± 10.5	64.4 ± 13.0	<0.001
Male	138 (65.4)	33 (47.8)	39 (57.4)	66 (89.2)	<0.001
Medical history
Hypertension	129 (61.1)	49 (71.0)	41 (60.3)	39 (52.7)	0.079
Diabetes mellitus	73 (34.6)	21 (30.4)	26 (38.2)	26 (35.1)	0.626
Smoking	69 (32.7)	11 (15.9)	17 (25.0)	41 (55.4)	<0.001
Drinking	31 (14.7)	7 (10.1)	7 (10.3)	17 (23.0)	0.044
Ventricular arrhythmia	46 (21.8)	11 (15.9)	13 (19.1)	22 (29.7)	0.111
Surgery
Coronary revascularization	153 (72.5)	45 (65.2)	50 (73.5)	58 (78.4)	0.206
Stent	135 (64.0)	38 (55.1)	44 (64.7)	53 (71.6)	0.118
PTCA	91 (43.1)	31 (44.9)	29 (42.6)	31 (41.9)	0.931
Thrombus aspiration	44 (20.9)	10 (14.5)	15 (22.1)	19 (25.7)	0.247
IABP	40 (19.0)	12 (17.4)	13 (19.1)	15 (20.3)	0.907
Laboratory tests
BNP, ng/L	490.0 (122.5–1970.0)	1287.0 (266.0–3176.0)	535.0 (129.2–1927.5)	223.5 (70.5–920.5)	<0.001
Creatinine, μmol/L	113.0 (78.0–168.0)	135.0 (84.0–228.0)	109.5 (71.0–136.2)	114.0 (79.0–159.5)	<0.001
CRP, mg/L	42.3 (13.7–76.8)	46.6 (21.6–77.8)	26.9 (10.9–65.2)	43.1 (13.6–84.8)	0.187
Lactate, mmol/L	3.9 (2.5–6.8)	2.9 (1.8–6.8)	4.0 (2.5–5.7)	4.5 (3.2–7.3)	0.275
Uric acid, μmol/L	441.0 (363.2–592.5)	475.0 (340.0–590.5)	428.5 (381.5–562.8)	438.5 (366.2–620.0)	0.825
D-dimers, mg/L	2.0 (1.2–4.9)	1.9 (1.4–5.5)	1.7 (1.1–3.5)	2.1 (1.3–6.3)	0.231
Procalcitonin, ng/L	0.2 ± 0.1	0.2 ± 0.1	0.2 ± 0.1	0.2 ± 0.1	0.105
Potassium, mmol/L	4.1 ± 0.7	4.1 ± 0.8	4.1 ± 0.6	4.0 ± 0.7	0.785
INR	1.3 ± 0.4	1.4 ± 0.5	1.3 ± 0.2	1.3 ± 0.4	0.660
Echocardiography
LVEF, %	41.1 ± 9.2	40.8 ± 9.6	42.3 ± 9.2	40.4 ± 8.9	0.474
LVEDD, mm	50.9 ± 6.5	52.5 ± 6.8	49.6 ± 6.6	50.6 ± 5.8	0.038
Vital signs at admission
Temperature, ºC	37.0 ± 0.7	37.1 ± 0.8	36.8 ± 0.7	37.0 ± 0.6	0.063
Heart rate, beats/min	98.6 ± 23.1	94.0 ± 19.8	97.6 ± 26.4	103.7 ± 22.1	0.039
SBP, mmHg	110.1 ± 24.5	110.6 ± 24.0	107.8 ± 23.6	111.8 ± 25.8	0.618
DBP, mmHg	68.0 ± 16.2	65.5 ± 15.0	67.2 ± 15.2	71.0 ± 17.8	0.119
Respiratory rate, breaths/min	21.7 ± 6.2	22.1 ± 6.2	20.7 ± 5.8	22.2 ± 6.6	0.296

Data are presented as n (%), mean ± standard deviation, or median (interquartile range). Abbreviations: IHCA, in-hospital cardiac arrest; PTCA, percutaneous transluminal coronary angioplasty; IABP, intra-aortic balloon pump; BNP, brain natriuretic peptide; CRP, C-reactive protein; INR, international normalized ratio; LVEF, left ventricular ejection fraction; LVEDD, left ventricular end-diastolic dimension; SBP, systolic blood pressure; DBP, diastolic blood pressure.

Association between hemoglobin and prevalence of IHCA

As illustrated in Table 2, the univariate analysis suggested that the hemoglobin concentration was a strong independent predictor of IHCA (OR, 0.979; 95% CI, 0.966–0.992; P = 0.002) when hemoglobin was analyzed as a continuous variable. After adjusting for sex and age, the multivariate analysis revealed that the hemoglobin concentration was still closely associated with the incidence of IHCA (OR, 0.976; 95% CI, 0.962–0.990; P = 0.001). Furthermore, the OR of model 3 (adjusted for sex, age, coronary revascularization, hypertension, diabetes mellitus, ventricular arrhythmias, BNP, creatinine, and lactate) was 0.971 (95% CI, 0.954–0.989; P = 0.001).

Table 2.

Association between hemoglobin concentration and incidence of in-hospital cardiac arrest

All patients (N = 211)	Events/incidence	Model 1		Model 2		Model 3
All patients (N = 211)	Events/incidence	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value
Continuous	61/28.9%	0.979 (0.966–0.992)	0.002	0.976 (0.962–0.990)	0.001	0.971 (0.954–0.989)	0.001
T1 (n = 69)	28/40.6%	Ref		Ref		Ref
T2 (n = 68)	20/29.4%	0.610 (0.300–1.240)	0.172	0.576 (0.279–1.192)	0.137	0.572 (0.252–1.300)	0.182
T3 (n = 74)	13/17.6%	0.312 (0.145–0.672)	0.003	0.257 (0.111–0.597)	0.002	0.194 (0.071–0.530)	0.001

Model 1: unadjusted.

Model 2: adjusted for sex and age.

Model 3: adjusted for sex, age, coronary revascularization, hypertension, diabetes mellitus, ventricular arrhythmias, brain natriuretic peptide, creatinine, and lactate.

Tertiles of hemoglobin: T1 (≤112 g/L), T2 (113–133 g/L), T3 (≥134 g/L).

Abbreviations: OR, odds ratio; CI, confidence interval; Ref, reference.

Different incidence of IHCA between patients with higher and lower hemoglobin concentrations

As presented in Table 2 and Figure 2, the multivariate analysis suggested that the risk of IHCA in the T3 group was lower (OR, 0.312; 95% CI, 0.145–0.672; P = 0.003) with T1 as a reference in the unadjusted model. When sex and age were adjusted, however, the prevalence of IHCA became higher (OR, 0.257; 95% CI, 0.111–0.597; P = 0.002) with T1 as a reference. Furthermore, in model 3 (adjusted for sex, age, coronary revascularization, hypertension, diabetes mellitus, ventricular arrhythmias, BNP, creatinine, and lactate), patients in the T3 group were less likely to develop IHCA (OR, 0.194; 95% CI, 0.071–0.530; P = 0.001) with T1 as a reference. Although the OR for T2 compared with T1 was not statistically significant, the overall trend was that patients with a higher hemoglobin level were less likely to develop IHCA (all P for trend <0.01).

Figure 2.

ORs of hemoglobin for IHCA. (a) Unadjusted. (b) Adjusted for sex, age, coronary revascularization, hypertension, diabetes mellitus, ventricular arrhythmias, brain natriuretic peptide, creatinine, and lactate. OR, odds ratio; CI, confidence interval; IHCA, in-hospital cardiac arrest.

Subgroup analyses

The results of the interaction and stratified analyses are shown in Figure 3. The relationship between hemoglobin and IHCA remained stable in most subgroups except patients aged ≥70 years. There was a significant association between hemoglobin and IHCA in patients aged <70 years (P = 0.001), but not in patients aged ≥70 years (Figure 3). The interaction between an age of<70 and ≥70 years was significant (P for interaction = 0.021). The interactions in the other groups were not statistically significant, indicating that the relationship between hemoglobin and IHCA remained stable in the other groups.

Figure 3.

Association between hemoglobin and IHCA according to baseline characteristics. Each stratification was adjusted for all factors (sex, age, coronary revascularization, hypertension, diabetes mellitus, ventricular arrhythmias, brain natriuretic peptide, creatinine, and lactate) except the stratification factor itself. OR, odds ratio; CI, confidence interval; IHCA, in-hospital cardiac arrest.

Discussion

In this retrospective observational study, we investigated whether the serum hemoglobin level was independently associated with an increased risk of IHCA in patients with ACS complicated by CS. We found that the incidence of IHCA was related to the hemoglobin concentration. In addition, the results suggested that a higher hemoglobin concentration was associated with a lower prevalence of IHCA. Indeed, a 1-g/L increase in the hemoglobin level was associated with a 2.9% lower risk of IHCA, further confirming the relationship between hemoglobin and IHCA. Moreover, patients with a higher hemoglobin level had a 0.194-fold lower risk of developing IHCA compared with patients with a lower hemoglobin level. Interestingly, a prior study showed that older patients had a higher risk of IHCA during hospitalization.²² In the subgroup analysis of our study, however, no such association was observed in patients aged >70 years. The following explanation seems plausible. As previously reported, a low hemoglobin level is more common in patients of advanced age^23,²⁴ and may be a sign of frailty in younger patients.²⁵ Younger patients with frailty are more likely to have many comorbidities, which may play a role in the occurrence of IHCA. From this viewpoint, a low hemoglobin level is more closely associated with IHCA in younger than older patients. There are several other possibilities for how our study population differs from those of previous studies, and the number of patients in the present study may not have been large enough. Further research is needed to more fully investigate the association.

The findings of our study are consistent with those of previous research in that the patients with a lower hemoglobin concentration were more likely to develop an adverse prognosis.^26–28 Previous reports have described hemoglobin as a predictor of mortality, major bleeding, and cardiovascular events in patients with ACS,^26–28 but the association between hemoglobin and IHCA has not been reported. Several studies have investigated the risk factors for IHCA. One study showed that a cardiac etiology was the dominant cause of IHCA.²⁹ Both pneumonia and a hypoxic etiology were also related to IHCA.^30,³¹ Joundi et al.³² found that aging and diabetes were important predictive factors for IHCA. To the best of our knowledge, the present study is the first to describe the relationship between the hemoglobin concentration and the incidence of IHCA.

Different from previous studies,^29–32 the population in our study comprised patients with ACS complicated by CS. CS is a state of end-organ hypoperfusion due to reduced cardiac output,^14–16 which is considered a sign of hemodynamic instability. Patients with hemodynamic instability are more liable to develop cardiac arrest.^11–13 From this viewpoint, our research is clinically meaningful, and the population in this study represents typical patients with hemodynamic instability who are in danger of developing IHCA. Thus, the incidence rate of IHCA in this study may be much higher than that in other ordinary patients. Identification of patients with CS who have a high risk of developing cardiac arrest should be given more attention in the clinical setting.

Given the observational nature of our cohort, we were limited to describing the association between the hemoglobin concentration and the incidence of IHCA. Therefore, further studies are necessary to elucidate the underlying pathophysiological mechanisms, which may include the following. First, anemia is reportedly related to left ventricular dysfunction.^33,³⁴ Chronic left ventricular dysfunction often causes ventricular remodeling, including left ventricular hypertrophy and dilatation.³⁵ Left ventricular hypertrophy and left ventricular expansion increase the risk of cardiac arrest and sudden cardiac death in patients with cardiovascular disease.^36–38 Second, patients with anemia may be prone to developing ventricular arrhythmia,³⁷ which is the most common pathophysiological mechanism of cardiac arrest. Third, previous studies have demonstrated that anemia induces tissue hypoxia in the most vulnerable regions affected by ischemia.^39–41 Patients with CS have an increased wedge pressure and thus hampered oxygen and carbon dioxide exchange at the pulmonary level, resulting in even lower oxygenation of the already decreased hemoglobin level on admission.⁴² In a sense, anemia has the same effect on IHCA as do respiratory problems by decreasing oxygen delivery. Fourth, anemia reportedly worsens the outcome of patients with heart failure by enhancing their myocardial workload.⁴³ In patients with cardiac shock with already poor cardiac function, the increased myocardial workload makes cardiac arrest more likely to occur.

Considering that the outcomes of IHCA are very poor,^32,44–46 prevention of IHCA is extremely important. The present study showed that a low hemoglobin concentration may be related to the incidence of IHCA and could thus serve as a clinical monitoring index and facilitate early decision-making. We believe that more methods with which to effectively predict the occurrence of IHCA, such as a risk score that includes hemoglobin or other indicators, will be developed in future clinical practice. Furthermore, it may be valuable to explore whether we can reduce the risk of IHCA by increasing the patient’s hemoglobin concentration. Notably, previous studies have shown that the relationship between the baseline hemoglobin level and an adverse prognosis is curvilinear (reverse J-shaped curve) in patients with ACS.^47,48 Although the same phenomenon was not observed in our study, it may still exist in other populations. This is an interesting question that should be further studied in the future and may help to identify the risk threshold of hemoglobin in the development of IHCA.

The present study has some limitations. First, the study was based on a single-center cohort, which limits the generalizability of the results. Physicians should conduct a longitudinal large-scale, multicenter study of a general population to confirm the relationship between the hemoglobin concentration and the incidence of IHCA. Second, the self-reported history of chronic disease in this study may have led to recall bias, affecting the accuracy of disease prevalence estimations. Third, the study may still have some selection bias, including frailty of the patients, despite the fact that we adjusted for possible confounding variables in the multiple logistic regression models.

Conclusion

In patients with ACS complicated by CS, the incidence of IHCA is related to the hemoglobin concentration. Furthermore, a high hemoglobin concentration is a protective factor against the development of IHCA.

Footnotes

Declaration of conflicting interest

The authors declare that there is no conflict of interest.

Funding

The study was funded by Major Project of the Science and Technology of Wenzhou (ZS2017010).

References

Jacobs

Nadkarni

Bahr

, et al. Cardiac arrest and cardiopulmonary resuscitation outcome reports: update and simplification of the Utstein templates for resuscitation registries. A statement for healthcare professionals from a task force of the international liaison committee on resuscitation (American Heart Association, European Resuscitation Council, Australian Resuscitation Council, New Zealand Resuscitation Council, Heart and Stroke Foundation of Canada, InterAmerican Heart Foundation, Resuscitation Council of Southern Africa). Resuscitation 2004; 63: 233–249.

Hershey

Fisher

Why outcome of cardiopulmonary resuscitation in general wards is poor.

Lancet 1982; 1: 31–34.

Sandroni

Nolan

Cavallaro

, et al. In-hospital cardiac arrest: incidence, prognosis and possible measures to improve survival. Intensive Care Med 2007; 33: 237–245.

Nolan

Soar

Smith

, et al. Incidence and outcome of in-hospital cardiac arrest in the United Kingdom National Cardiac Arrest Audit. Resuscitation 2014; 85: 987–992.

Shao

Liang

, et al. Incidence and outcome of adult in-hospital cardiac arrest in Beijing, China. Resuscitation 2016; 102: 51–56.

Liu

, et al. Characteristics and outcomes of in-hospital cardiac arrest in adults hospitalized with acute coronary syndrome in China. Am J Emerg Med 2018; pii: S0735-6757(18)30813-1. doi: 10.1016/j.ajem.2018.10.003.

Hess

Campbell

White

RD.

Epidemiology, trends, and outcome of out-of-hospital cardiac arrest of non-cardiac origin.

Resuscitation 2007; 72: 200–206.

Nolan

and European Resuscitation C. European Resuscitation Council guidelines for resuscitation 2005. Section 1. Introduction. Resuscitation 2005; 67: S3–S6.

Skogvoll

Isern

Sangolt

, et al. In-hospital cardiopulmonary resuscitation. 5 years' incidence and survival according to the Utstein template. Acta Anaesthesiol Scand 1999; 43: 177–184.

10.

Dumas

Rea

TD.

Long-term prognosis following resuscitation from out-of-hospital cardiac arrest: role of aetiology and presenting arrest rhythm.

Resuscitation 2012; 83: 1001–1005.

11.

Kause

Smith

Prytherch

, et al. A comparison of antecedents to cardiac arrests, deaths and emergency intensive care admissions in Australia and New Zealand, and the United Kingdom–the ACADEMIA study. Resuscitation 2004; 62: 275–282.

12.

Franklin

Mathew

Developing strategies to prevent inhospital cardiac arrest: analyzing responses of physicians and nurses in the hours before the event.

Crit Care Med 1994; 22: 244–247.

13.

Schein

Hazday

Pena

, et al. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest 1990; 98: 1388–1392.

14.

van Diepen

Katz

Albert

, et al. Contemporary management of cardiogenic shock: a scientific statement from the American Heart Association. Circulation 2017; 136: e232–e268.

15.

Reynolds

Hochman

JS.

Cardiogenic shock: current concepts and improving outcomes.

Circulation 2008; 117: 686–697.

16.

Redfors

Angeras

Ramunddal

, et al. 17-year trends in incidence and prognosis of cardiogenic shock in patients with acute myocardial infarction in western Sweden. Int J Cardiol 2015; 185: 256–262.

17.

Laslett

Alagona

Jr Clark

3rd , et al. The worldwide environment of cardiovascular disease: prevalence, diagnosis, therapy, and policy issues: a report from the American College of Cardiology. J Am Coll Cardiol 2012; 60: S1–S49.

18.

Winther

Finer

Sharma

, et al. Association of anemia with the risk of cardiovascular adverse events in overweight/obese patients. Int J Obes (Lond) 2014; 38: 432–437.

19.

Vis

Sjauw

van der Schaaf

, et al. Prognostic value of admission hemoglobin levels in ST-segment elevation myocardial infarction patients presenting with cardiogenic shock. Am J Cardiol 2007; 99: 1201–1202.

20.

Jomaa

Ben Ali

Hamdi

, et al. Prevalence and prognostic significance of anemia in patients presenting for ST-elevation myocardial infarction in a Tunisian center. J Saudi Heart Assoc 2017; 29: 153–159.

21.

Liu

Yang

Zhu

, et al. Anaemia and prognosis in acute coronary syndromes: a systematic review and meta-analysis. J Int Med Res 2012; 40: 43–55.

22.

Larkin

Copes

Nathanson

, et al. Pre-resuscitation factors associated with mortality in 49,130 cases of in-hospital cardiac arrest: a report from the National Registry for Cardiopulmonary Resuscitation. Resuscitation 2010; 81: 302–311.

23.

Guralnik

Eisenstaedt

Ferrucci

, et al. Prevalence of anemia in persons 65 years and older in the United States: evidence for a high rate of unexplained anemia. Blood 2004; 104: 2263–2268.

24.

Riva

Tettamanti

Mosconi

, et al. Association of mild anemia with hospitalization and mortality in the elderly: the Health and Anemia population-based study. Haematologica 2009; 94: 22–28.

25.

Palmer

Vetrano

Marengoni

, et al. The relationship between anaemia and frailty: a systematic review and meta-analysis of observational studies. J Nutr Health Aging 2018; 22: 965–974.

26.

Kalra

Greenlaw

Ferrari

, et al. Hemoglobin and change in hemoglobin status predict mortality, cardiovascular events, and bleeding in stable coronary artery disease. Am J Med 2017; 130: 720–730.

27.

Shah

Nicholas

Timmis

, et al. Threshold haemoglobin levels and the prognosis of stable coronary disease: two new cohorts and a systematic review and meta-analysis. PLoS Med 2011; 8: e1000439.

28.

Brener

Mehran

Dangas

, et al. Relation of baseline hemoglobin levels and adverse events in patients with acute coronary syndromes (from the Acute Catheterization and Urgent Intervention Triage strategY and Harmonizing Outcomes with RevasculariZatiON and Stents in Acute Myocardial Infarction Trials). Am J Cardiol 2017; 119: 1710–1716.

29.

Bergum

Haugen

Nordseth

, et al. Recognizing the causes of in-hospital cardiac arrest - A survival benefit. Resuscitation 2015; 97: 91–96.

30.

Bergum

Nordseth

Mjølstad

, et al. Causes of in-hospital cardiac arrest - incidences and rate of recognition. Resuscitation 2015; 87: 63–68.

31.

Tirkkonen

Hellevuo

Olkkola

, et al. Aetiology of in-hospital cardiac arrest on general wards. Resuscitation 2016; 107: 19–24.

32.

Joundi

Rabinstein

Nikneshan

, et al. Cardiac arrest in acute ischemic stroke: incidence, predisposing factors, and clinical outcomes. J Stroke Cerebrovasc Dis 2016; 25: 1644–1652.

33.

Zhou

Shen

Liu

, et al. Assessment of left ventricular systolic function in patients with iron deficiency anemia by three-dimensional speckle-tracking echocardiography. Anatol J Cardiol 2017; 18: 194–199.

34.

Guglin

Darbinyan

Relationship of hemoglobin and hematocrit to systolic function in advanced heart failure.

Cardiology 2012; 122: 187–194.

35.

Udelson

Konstam

MA.

Relation between left ventricular remodeling and clinical outcomes in heart failure patients with left ventricular systolic dysfunction.

J Card Fail 2002; 8: S465.

36.

Quinones

Greenberg

Kopelen

, et al. Echocardiographic predictors of clinical outcome in patients with left ventricular dysfunction enrolled in the SOLVD registry and trials: significance of left ventricular hypertrophy. Studies of Left Ventricular Dysfunction. J Am Coll Cardiol 2000; 35: 1237–1244.

37.

Narayanan

Reinier

Teodorescu

, et al. Left ventricular diameter and risk stratification for sudden cardiac death. J Am Heart Assoc 2014; 3: e001193.

38.

Aro

Reinier

Phan

, et al. Left-ventricular geometry and risk of sudden cardiac arrest in patients with preserved or moderately reduced left-ventricular ejection fraction. Europace 2017; 19: 1146–1152.

39.

Karkouti

Djaiani

Borger

, et al. Low hematocrit during cardiopulmonary bypass is associated with increased risk of perioperative stroke in cardiac surgery. Ann Thorac Surg 2005; 80: 1381–1387.

40.

Habib

Zacharias

Schwann

, et al. Adverse effects of low hematocrit during cardiopulmonary bypass in the adult: should current practice be changed? J Thorac Cardiov Sur 2003; 125: 1438–1450.

41.

Kramer

Zygun

DA.

Anemia and red blood cell transfusion in neurocritical care. Crit Care 2009; 13: R89.

42.

Metivier

Marchais

Guerin

, et al. Pathophysiology of anaemia: focus on the heart and blood vessels. Nephrol Dial Transpl 2000; 15: 14–18.

43.

Anand

IS.

Anemia and chronic heart failure implications and treatment options.

J Am Coll Cardiol 2008; 52: 501–511.

44.

Mozaffarian

Benjamin

, et al. Heart disease and stroke statistics–2015 update: a report from the American Heart Association. Circulation 2015; 131: e29–e322.

45.

Feingold

Mina

Burke

, et al. Long-term survival following in-hospital cardiac arrest: a matched cohort study. Resuscitation 2016; 99: 72–78.

46.

Limpawattana

Aungsakul

Suraditnan

, et al. Long-term outcomes and predictors of survival after cardiopulmonary resuscitation for in-hospital cardiac arrest in a tertiary care hospital in Thailand. Ther Clin Risk Manag 2018; 14: 583–589.

47.

Numasawa

Ueda

Sawano

, et al. Relation of baseline hemoglobin level to in-hospital outcomes in patients who undergo percutaneous coronary intervention (from a Japanese Multicenter Registry). Am J Cardiol 2018; 121: 695–702.

48.

Bassand

Afzal

Eikelboom

, et al. Relationship between baseline haemoglobin and major bleeding complications in acute coronary syndromes. Eur Heart J 2010; 31: 50–58.