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Acute and Critical Care > Volume 35(2); 2020 > Article
Song, Lee, Leem, Kim, Chung, Kim, Jung, Kang, Kim, Chang, and Park: Predictors and outcomes of sepsis-induced cardiomyopathy in critically ill patients

KEY MESSAGES

▪ Sepsis-induced cardiomyopathy (SIC) occurred in 14.3% of intensive care unit patients with sepsis.
▪ Low systolic blood pressure and increased left ventricular end-diastolic diameter were predictors of SIC.
▪ High Acute Physiology and Chronic Health Evaluation II and elevated delta neutrophil index were risk factors of 28-day mortality in SIC.

Abstract

Background

Sepsis-induced cardiomyopathy (SIC) occurs frequently in critically ill patients, but the clinical features and prognostic impact of SIC on sepsis outcome remain controversial. Here, we investigated the predictors and outcomes of SIC.

Methods

Patients admitted to a single medical intensive care unit from June 2016 to September 2017 were retrospectively reviewed. SIC was diagnosed by ejection fraction (EF) <50% and ≥10% decrease in baseline EF that recovered within 2 weeks.

Results

In total, 342 patients with sepsis met the inclusion criteria, and 49 patients (14.3%) were diagnosed with SIC; the latter were compared with 259 patients whose EF was not deteriorated by sepsis (non-SIC). Low systolic blood pressure and increased left ventricular end-diastolic diameter (LVEDD) were identified as predictors of SIC. SIC and non-SIC patients did not differ significantly in terms of 28-day all-cause mortality (24.5% vs. 26.3%, P=0.936). Acute Physiology and Chronic Health Evaluation II (APACHE II; hazard ratio [HR], 1.10; 95% confidential interval [CI], 1.02 to 1.18; P=0.009) and delta neutrophil index (DNI; HR, 1.02; 95% CI, 1.00 to 1.08; P=0.026) were independent risk factors for 28-day mortality with SIC. DNI, APACHE II, and lactate were identified as risk factors for 28-day mortality in sepsis patients as a whole.

Conclusions

SIC was not associated with increased mortality compared to non-SIC. Low systolic blood pressure and increased LVEDD were predictors of SIC. High APACHE II score and elevated DNI, which reflect sepsis severity, predict 28-day all-cause mortality.

INTRODUCTION

Sepsis is a syndrome of physiologic, pathologic, and biochemical abnormalities induced by infection that can result in multiple organ dysfunction via inflammatory cytokines, mitochondria dysfunction, and tissue hypoxia [1]. Due to specific injury of cardiomyocytes, approximately 3.8%–65% of patients with sepsis develop sepsis-induced cardiomyopathy (SIC) [2-7]. SIC has been defined as myocardial dysfunction characterized by decreased ejection fraction (EF) and increased left ventricular end-diastolic diameter (LVEDD) that recovers within 7–10 days [2]. Current understanding of the pathogenesis of SIC is limited, and conflicting results remain regarding the prognostic impact of SIC on sepsis outcomes.
Improved understanding of SIC is important for multiple reasons. First, cardiac function is crucial for maintaining hemodynamic stability in patients with septic shock. Second, by understanding the clinical features and predictors of SIC, we can discriminate SIC from other cardiac diseases and avoid unnecessary invasive procedures, such as coronary angiography, a risky procedure in critically ill patients. Thus, we aimed to define clinical predictors of SIC and assess the clinical course and outcome of SIC in patients with sepsis.

MATERIALS AND METHODS

Study Population

In this study, the medical records of patients who were admitted to the medical intensive care unit (ICU) of Yonsei University College of Medicine from June 2016 to September 2017 were reviewed. A total of 576 adult patients (>18 years old) admitted to the ICU during this period were screened for inclusion (Figure 1). Patients who did not (1) meet the sepsis definition, (2) have baseline transthoracic echocardiography (TTE) data, or (3) undergo TTE within 48 hours after ICU admission were excluded. This study was approved by the Institutional Review Board and Ethics Committee of Severance Hospital (IRB No. 4-2018-0751). The requirement for written informed consent from patients was waived. All methods were performed in accordance with the Declaration of Helsinki.

Definitions of Variables

The sepsis-3 definition was applied in patients with sepsis and septic shock [1]. Sepsis was defined by an increase in Sequential Organ Failure Assessment (SOFA) score of ≥2 points due to infection. Infection was defined as detection of microorganisms in culture or as radiologic or clinical manifestations suggesting infection despite negative culture results [8]. Septic shock was defined as sepsis with persistent hypotension requiring vasopressor drugs to maintain mean arterial pressure ≥65 mm Hg accompanied with serum lactate level >2 mmol/L despite adequate volume resuscitation. Left ventricular function deterioration was defined as EF <50% and ≥10% decrease in baseline EF. Among patients with left ventricular function deterioration, those whose EF recovered to the baseline level within 2 weeks were defined as having SIC [7,9,10].

Data Collection

Demographic data (age, sex, body weight, height, pre-existing comorbidities), vital signs, laboratory findings, echocardiographic findings, and clinical findings (presence of acute kidney injury, acute respiratory distress syndrome, and use of mechanical ventilation) were collected. Laboratory tests were performed within 24 hours of ICU admission, and SOFA and Acute Physiology and Chronic Health Evaluation (APACHE) II scores were evaluated at ICU admission. The delta neutrophil index (DNI) was assessed using an automated blood cell analyzer (ADVIA 120; Siemens, Forchheim, Germany) and calculated using the following formula: (neutrophil subfraction+ eosinophil subfraction measured in the myeloperoxidase channel)–(polymorphonuclear subfraction measured in nuclear lobularity channel) [11,12]. If there was no contraindication, TTE was routinely performed by a cardiologist at the time of ICU admission. There was no fixed schedule for follow up TTE, but in the majority of patients it was performed 1–2 weeks after ICU admission, especially when cardiac function deteriorated during ICU admission.

Statistical Analysis

The primary endpoint was 28-day all-cause mortality of SIC. The secondary endpoint was to identify predictors of SIC development and risk factors for 28-day all-cause mortality in patients with SIC. Factors contributing to the incidence of SIC were also analyzed. Continuous variables were analyzed using Student t-test or Mann-Whitney U-test; categorical variables were analyzed using the chi-squared distribution and Fisher’s exact test. A logistic regression model was used to identify variables contributing to the development of SIC. Cox proportional hazards regression analyses were conducted to assess the relationships between variables and 28-day allcause mortality. Area under the curve of receiver operating characteristic curves was used to identify the effect of major variables in multivariate Cox proportional hazards regression analysis (P<0.05) on 28-day all-cause mortality. Cumulative time-to-event distribution (survival) was estimated using Kaplan-Meier survival curves, and differences in survival between groups were assessed using the log-rank test. In all cases, P-values <0.05 were considered statistically significant. Statistical analyses were performed using R statistical software ver. 3.5.1 (R Foundation, Vienna, Austria).

RESULTS

Baseline Characteristics of Study Population

A total of 342 patients met the study eligibility criteria. Of these, 83 showed left ventricular function deterioration compared to baseline TTE. Among these, 49 patients had an EF that recovered to the baseline value and were categorized as SIC. Fifteen patients with persistently decreased EF in follow-up TTE and 19 patients without follow-up TTE were excluded (Figure 1). A total of 259 patients whose EF did not deteriorate with sepsis were categorized as the non-SIC group.
Baseline characteristics of 49 SIC and 259 non-SIC patients with sepsis are shown in Table 1. There was no significant difference between SIC and non-SIC patients in terms of age, sex, and body mass index. APACHE II and SOFA scores also did not significantly differ between SIC and non-SIC patients. Underlying heart failure was more frequent in SIC patients (8.2% vs. 1.5%, P=0.029), but the incidence of other comorbidities, including coronary artery disease, was not significantly different between the groups. On ICU admission, systolic blood pressure was significantly lower in patients with SIC (83.9±18.3 vs. 91.1±22.9, P=0.039). There was no significant difference in vasopressor and inotrope use between SIC and non-SIC patients. Primary site of infection was not significantly different between SIC and non-SIC patients. Both C-reactive protein and serum bilirubin levels were higher (192.4± 134.2 vs. 137.5±110.6, P=0.002; 1.2±1.4 vs. 2.1±4.1, P=0.008, respectively), whereas serum albumin levels were lower (2.4± 0.5 vs. 2.5±0.5, P=0.032) in SIC patients than in non-SIC patients.
Echocardiographic findings and cardiac biomarkers are shown in Table 2. LVEDD and left ventricular end-systolic diameter (LVESD) were significantly increased in SIC patients (49.6±6.0 vs. 43.4±6.3, P<0.001; 39.5±6.4 vs. 28.7±4.8, P<0.001, respectively). N-terminal pro b-type natriuretic peptide (NTproBNP; pg/ml) and troponin-T (pg/ml) were significantly higher in SIC patients (19,911.2±18,194.9 vs. 7,940.3±13,613.9, P<0.001; 278.9±492.7 vs. 104.8±178.4, P=0.019, respectively), but creatine kinase (CK) and creatine kinase-muscle/brain (CK-MB) levels were not significantly different between SIC and non-SIC patients.

Predictors of SIC

Univariate logistic regression analyses for predictors of SIC revealed that low systolic blood pressure, hypoalbuminemia, elevated NT-proBNP, troponin-T, and increased LVEDD were major covariates (P<0.05). Multivariate logistic regression analysis revealed that low systolic blood pressure upon ICU admission and increased LVEDD were independent risk factors for the development of SIC (Table 3).

Outcomes of SIC

There was no significant difference between SIC patients and non-SIC patients in 28-day all-cause mortality (24.5% vs. 26.3%, P=0.936), length of ICU stay in days (15.4±13.8 vs. 12.4±20.2, P=0.249), ICU mortality (26.5% vs. 24.3%, P=0.882), and inhospital mortality (36.7% vs 36.7%, P=1.000) (Table 4). Among 31 patients who survived in the hospital, 25 were discharged home and six were transferred to another hospital. Cause of death for those who died in the hospital were as follows: primary infection-related multiple organ failure (n=10), respiratory failure (n=3), end of life decision (n=4), sudden cardiac arrest (n=1).
SIC patients were divided into survivors and non-survivors according to 28-day all-cause mortality, as shown in Table 5. Non-survivors showed higher APACHE II (32.1±8.3 vs. 24.4± 8.9, P=0.012) and SOFA scores (11.7±3.3 and 9.1±3.0, P=0.015) than survivors. Non-survivors showed significantly lower platelet counts (54.0; interquartile range [IQR], 29.0–138.5 vs. 155.0; IQR, 76.0–271.0; P=0.024) and higher DNI (26.1; IQR, 3.0–45.9 vs. 3.2; IQR, 1.1–9.5; P=0.049) than survivors. Regarding vital signs on admission, non-survivors showed a higher heart rate than survivors (134.3±25.8 vs. 101.5±25.2, P<0.001). Cox hazard proportional regression analysis for 28-day mortality in SIC patients revealed that APACHE II (hazard ratio [HR], 1.10; 95% confidential interval [CI], 1.02 to 1.18; P=0.009) and DNI (HR, 1.02; 95% CI, 1.00 to 1.08; P=0.026) were independent risk factors, while TEE parameters and cardiac biomarkers did not show statistically significant correlations with 28- day mortality. Cox hazard proportional regression analysis for 28-day mortality in sepsis patients as a whole revealed that APACHE II (HR, 1.04; 95% CI, 1.01 to 1.07; P=0.004), DNI (HR, 1.02; 95% CI, 1.00 to 1.03; P=0.044), and lactate (HR, 1.07; 95% CI, 1.02 to 1.13; P=0.007) were independent risk factors (Table 6). These variables are known to represent sepsis severity [12-14]. This suggests that sepsis severity, rather than TTE parameters and cardiac biomarkers, has the most important effect on SIC mortality.
Using the definition of SIC delineated in this study, patients with reversible LV function deterioration due to sepsis were compared with non-SIC patients. Of 83 patients who showed LV function deterioration, 15 patients with persistent LV dysfunction in follow-up TTE and 19 patients without follow-up TTE were excluded. The mortality outcomes of these two excluded groups are shown in Figure 1. While patients with persistent LV dysfunction revealed similar mortality outcomes as SIC and non-SIC patients, the group of patients without follow-up TTE showed a significantly poorer mortality outcome (28-day mortality, 73.7%). Follow-up TTE data were not available within 14 days from the first TTE in this group of patients for the following reasons. Eight patients (42.1%) died within 72 hours after ICU admission, end-of-life decisions were made for six patients (31.6%) mostly due to terminal underlying diseases (e.g., cancer), two patients were transferred to other hospitals, and three patients (15.8%) recovered from sepsis.

DISCUSSION

In this study, we demonstrated the clinical features, predictors, and survival outcomes of SIC. Low systolic blood pressure and increased LVEDD were revealed to be independent predictors of SIC. There was no significant difference between SIC and sepsis patients as a whole in terms of 28-day all-cause mortality. However, high APACHE II scores and DNI, which reflect sepsis severity, were independent risk factors for 28-day all-cause mortality in SIC patients.
To define SIC, we used a definition commonly applied in previous studies [2,7,10]. In these studies, the inclusion of preexisting cardiac diseases was controversial. In some studies, patients with pre-existing cardiac disease were excluded to reduce false-positive errors in detecting SIC [4,5,10,15-17]. However, those with pre-existing cardiac disease should be included and evaluated if this condition alters the risk of SIC development and survival. Our study revealed that neither heart failure nor coronary artery disease was a risk factor for SIC development or mortality.
Recently, several studies have indicated differences in the pathophysiology of SIC and stress-induced cardiomyopathy, also known as Takotsubo cardiomyopathy, in which sepsis is the source of stress [7,9,10]. Endotoxins, inflammatory cytokines, and nitric oxides are major contributors to the development of SIC [18,19]. In contrast, elevated catecholamine release is a key contributor to the development of Takotsubo cardiomyopathy [20]. However, it is difficult to distinguish these two diseases based on clinical parameters. Previous studies that distinguished SIC and Takotsubo cardiomyopathy used the criterion of typical apical ballooning in TTE. However, Takotsubo cardiomyopathy has both apical ballooning type and atypical type, which are difficult to discriminate from SIC based on TTE findings [20,21]. Thus, we proposed that SIC is a syndrome characterized by reversible LV dysfunction and includes Takotsubo cardiomyopathy caused by sepsis. Endotoxins, inflammatory cytokines, nitric oxides, and catecholamine are all considered associated with SIC development.
Echocardiography revealed that LVEDD was significantly higher in SIC patients than in non-SIC patients. Diastolic ventricle size increased to compensate for decreased systolic contractility. After fluid resuscitation, stroke volume can recover while EF is temporarily decreased due to increased LVEDD. Based on this pathophysiology, the importance of diastolic dysfunction rather than systolic function has been emphasized recently with reports of correlation between a lower e’, higher E/e’ ratio, and mortality in sepsis patients [19,22]. However, in this study, the LVEDD and E/e’ ratio did not show significant differences between survivors and non-survivors. This might be due to missing TTE parameters, especially in non-survivors.
In this study, low systolic blood pressure upon ICU admission and increased LVEDD were considered predictors of SIC development. Low systolic blood pressure resulting in inadequate coronary blood flow has been proposed as a mechanism of SIC based on animal studies [23]. Dilated LVEDD is diastolic compliance to decreased systolic function [19]. The predictors of SIC identified in this study are discrepant from those previously identified, probably due to the small sample size of each study and the use of discordant definitions [7,10,24].
In SIC patients, tachycardia on ICU admission was significantly more common among non-survivors than survivors. This is explained by adapting to insufficient diastolic filling to increase stroke volume. In the Cox proportional hazard regression analysis of 28-day mortality, APACHE II score and DNI were revealed as independent risk factors for mortality in SIC patients. Both APACHE II and DNI are markers of sepsis severity. DNI is a novel biomarker that reflects the number of circulating granulocytes in blood and correlates with sepsis severity in critically ill patients [11,12,25,26]. This suggests that sepsis severity has a greater effect on SIC prognosis than TEE parameters and cardiac biomarkers.
Among the 83 patients who showed LV dysfunction, 19 had no follow-up TTE. This group of patients showed significantly poorer mortality outcome, suggesting that the cardiac function of these 19 patients deteriorated due to sepsis and they usually did not recover, resulting in mortality. This may imply that this group of patients had the same pathophysiology as patients with SIC development and poor outcome. Due to the small number of these patients, the characteristics of persistent LV dysfunction could not be analyzed in detail in this group with no follow-up TTE. Further studies should be performed to clarify the characteristics of these patients.
This study had several limitations. First, detailed information regarding fluid resuscitation and vasopressor initiation were not available. These factors strongly affect sepsis patient prognosis. However, the study was performed in a single ICU of a tertiary university hospital in which sepsis management, including fluid resuscitation and vasopressor initiation, was generally performed according to the more recent sepsis-3 guidelines. Second, baseline TTE and TTE within 48 hours were not available in 8.7% of the initial population. This selection bias may have influenced the final results. Third, TTE parameters were not documented equally among patients and laboratory data. For example, inflammatory cytokines and catecholamines were not available due to the retrospective nature of this study. Lastly, this was a single center, retrospective study, which could affect the generalizability of results. Further prospective studies are needed to validate the results of this study.
In conclusion, this study identified predictors and outcome of SIC with inclusion of pre-existing cardiac diseases and Takotsubo cardiomyopathy. We found that low systolic blood pressure and dilated LVEDD were SIC predictors. The prognosis of SIC was affected by sepsis severity rather than cardiac function. Reversible SIC does not increase mortality risk compared to non-SIC. Further studies are needed on sepsis patients with persistent LV dysfunction and on patients whose LV function could not be restored, resulting in death.

NOTES

CONFLICT OF INTEREST No potential conflict of interest relevant to this article was reported.

AUTHOR CONTRIBUTIONS

Conceptualization: MJS, MSP. Data curation, Formal analysis, & Methodology: all authors. Project administration, Visualization, & Writing–original draft: MJS, MSP. Writing–review & editing: all authors.

Figure 1.
Patient recruitment flowchart. ICU: intensive care unit; TTE: transthoracic echocardiography; LV: left ventricle; SIC: sepsis-induced cardiomyopathy. aPatients without follow-up TTE showed poor mortality outcome. Lack of follow-up TTE in this group was due to several reasons: eight patients (42.1%) died within 72 hours after ICU admission, end-of-life decisions were made for six patients (31.6%), two patients were transferred to other hospitals, and three patients (15.8%) recovered from sepsis.
acc-2020-00024f1.jpg
Table 1.
Baseline characteristics of patients
Variable Total (n=308) SIC (n=49) Non-SIC (n=259) P-value
Age (yr) 64.6±14.5 65.1±11.2 64.6±15.0 0.772
Male sex 195 (63.3) 32 (65.3) 163 (62.9) 0.877
BMI (kg/m2) 22.2±4.3 22.4±3.9 22.2±4.4 0.782
APACHE II 24.9±8.8 26.4±9.3 24.6±8.6 0.209
SOFA 9.4±3.2 9.7±3.2 9.3±3.2 0.378
Comorbidity
 Hypertension 159 (51.6) 25 (51.0) 134 (51.7) 1.000
 Diabetes mellitus 108 (35.1) 17 (34.7) 91 (35.1) 1.000
 Chronic kidney disease 67 (21.8) 11 (22.4) 56 (21.6) 1.000
 Liver cirrhosis 25 (8.1) 2 (4.1) 23 (8.9) 0.399
 Chronic liver disease 29 (9.4) 1 (2.0) 28 (10.8) 0.097
 Cancer 83 (26.9) 16 (32.7) 67 (25.9) 0.420
 Heart failure 8 (2.6) 4 (8.2) 4 (1.5) 0.029
 Coronary artery disease 30 (9.7) 7 (14.3) 23 (8.9) 0.364
 Cerebrovascular disease 42 (13.6) 6 (12.2) 36 (13.9) 0.934
Charlson comorbidity index 2.8±2.2 3.2±2.1 2.8±2.2 0.231
Acute kidney injury 73 (23.7) 14 (28.6) 59 (22.8) 0.490
ARDS 28 (9.1) 8 (16.3) 20 (7.7) 0.099
Septic shock 295 (95.8) 49 (100.0) 246 (95.0) 0.224
Blood culture (+) 113 (36.7) 22 (44.9) 91 (35.1) 0.255
Mechanical ventilation 200 (64.9) 36 (73.5) 164 (63.3) 0.229
Vital sign on admission
 SBP (mm Hg) 90.0±22.3 83.9±18.3 91.1±22.8 0.039
 MAP (mm Hg) 66.7±15.4 64.3±15.3 67.1±15.4 0.249
 HR (bpm) 103.0±27.9 109.6±28.9 101.7±27.6 0.071
Use of vasopressor and inotrope
 None 13 (4.2) 0 15 (5.1) 0.224
 Norepinephrine 262 (85.1) 44 (89.8) 247 (84.3) 0.420
 Dobutamine 3 (0.9) 2 (4.1) 1 (0.4) 0.105
Primary focus of infection 0.507
 Pulmonary 155 (50.3) 29 (59.2) 126 (48.6)
 GI tract 43 (14.0) 3 (6.1) 40 (15.4)
 Urogenital 35 (11.4) 7 (14.3) 28 (10.8)
 Pancreatobiliary 25 (8.1) 2 (4.1) 23 (8.9)
 Soft tissue/bone 17 (5.5) 4 (8.2) 13 (5.0)
 Liver 9 (2.9) 1 (2.0) 8 (3.1)
 Kidney 6 (1.9) 1 (2.0) 5 (1.9)
 Miscellaneous 18 (5.8) 2 (4.1) 16 (6.2)
Laboratory parameter
 WBC (103/µl) 15.1±10.4 12.9±10.3 15.5±10.4 0.117
 Platelet (103/µl) 159.2±120.4 162.6±139.1 158.5±116.8 0.831
 Serum albumin (g/dl) 2.5±0.5 2.4±0.5 2.5±0.5 0.032
 Serum bilirubin (mg/dl) 2.0±3.8 1.2±1.4 2.1±4.1 0.008
 Serum creatinine (mg/dl) 2.1±1.9 2.0±1.8 2.1±2.0 0.757
 Lactate (mmol/L) 4.0±4.1 3.8±3.4 4.0±4.3 0.826
 CRP 146.3±116.2 192.4±134.2 137.5±110.6 0.002
 Procalcitonin (ng/ml) 17.5±33.0 23.9±35.5 16.2±32.4 0.135
 DNI (%) 11.0±15.1 13.9±18.9 10.5±14.2 0.224

Values are presented as mean±standard deviation or number (%).

SIC: sepsis-induced cardiomyopathy; BMI: body mass index; APACHE: Acute Physiology and Chronic Health Evaluation; SOFA: Sequential Organ Failure Assessment; ARDS: acute respiratory distress syndrome; SBP: systolic blood pressure; MAP: mean arterial pressure; HR: heart rate; GI: gastrointestinal; WBC: white blood cell; CRP: C-reactive protein; DNI: delta neutrophil index.

Table 2.
Echocardiographic parameters and cardiac biomarkers of patients
Echocardiographic parameter SIC (n=49)
Non-SIC (n=259)
P-value
Individual Value Individual Value
Ejection fraction (%) 49 34.3±8.4 259 64.7±7.5 <0.001
 LVEDD (mm) 46 49.6±6.0 248 43.4±6.3 <0.001
 LVESD (mm) 46 39.5±6.4 248 28.7±4.8 <0.001
 Mitral E/e’ ratio 36 12.9±5.5 198 12.0±4.3 0.341
 FAC (%) 7 25.3±5.3 17 24.0±8.7 0.712
Cardiac biomarker
 NT-proBNP (pg/ml) 46 19,911.2±18,194.9 233 7,940.3±13,613.9 <0.001
 CK (IU/L) 49 341.7±491.8 245 635.9±3,711.8 0.235
 CK-MB (ng/ml) 49 8.0±12.8 252 11.9±60.3 0.357
 Troponin-T (pg/ml) 48 278.9±492.7 230 104.8±178.4 0.019

Values are presented as mean±standard deviation.

SIC: sepsis-induced cardiomyopathy; LVEDD: left ventricular end-diastolic diameter; LVESD: left ventricular end-systolic diameter; E: early mitral inflow velocity; e’: mitral annular early diastolic velocity; FAC: fractional area change; NT-proBNP: N-terminal pro b-type natriuretic peptide; CK: creatine kinase; CK-MB: creatine kinase-muscle/brain.

Table 3.
Logistic regression analyses for predictors of sepsis induced cardiomyopathy
Variable HR (95% CI) P-value
Univariate logistic regression analysis
 Age 0.99 (0.97–1.02) 0.714
 Male sex 0.73 (0.31–1.70) 0.460
 Diabetes mellitus 0.59 (0.25–1.38) 0.221
 Heart failure 4.79 (0.29–78.86) 0.273
 Systolic blood pressure 0.98 (0.96–1.00) 0.027
 Heart rate 1.00 (0.98–1.01) 0.748
 CRP 1.00 (1.00–1.01) 0.088
 Procalcitonin 1.01 (0.99–1.02) 0.357
 DNI 1.00 (0.97–1.02) 0.821
 Lactate 0.93 (0.83–1.05) 0.264
 Albumin 0.43 (0.20–0.94) 0.035
 Blood culture (+) 1.28 (0.57–2.87) 0.553
 NT-proBNP/1000 1.03 (1.01–1.06) 0.001
 Troponin T/10 1.03 (1.01–1.06) 0.007
 LVEDD 1.19 (1.09–1.28) <0.001
 E/e’ 1.05 (0.97–1.14) 0.195
Multivariate logistic regression analysis
 Systolic blood pressure 0.96 (0.93–0.99) 0.007
 Albumin 0.38 (0.14–1.07) 0.066
 NT-proBNP/1000 1.04 (0.99–1.04) 0.296
 Troponin T/10 1.01 (1.00–1.03) 0.068
 LVEDD 1.24 (1.13–1.37) <0.001

HR: hazard ratio; CI: confidential interval; CRP: c-reactive protein; DNI: delta neutrophil index; NT-proBNP: N-terminal pro b-type natriuretic peptide; LVEDD: left ventricular end-diastolic diameter; E: early mitral inflow velocity; e’: mitral annular early diastolic velocity.

Table 4.
Outcome of sepsis induced cardiomyopathy
Variable Total (n=308) SIC (n=49) Non-SIC (n=259) P-value
28-Day mortality 80 (26.0) 12 (24.5) 68 (26.3) 0.936
In-hospital mortality 113 (36.7) 18 (36.7) 95 (36.7) 1.000
ICU mortality 76 (24.7) 13 (26.5) 63 (24.3) 0.882
Length of ICU stay (day) 13.2±19.3 15.4±13.8 12.7±20.2 0.249

Values are presented as number (%) or mean±standard deviation.

SIC: sepsis-induced cardiomyopathy; ICU: intensive care unit.

Table 5.
Baseline characteristics of sepsis-induced cardiomyopathy patients according to 28-day all-cause mortality
Characteristics Survivor (n=37) Non-survivor (n=12) P-value
Age (yr) 65.0±11.2 65.3±11.7 0.935
Male sex 24 (64.9) 8 (66.7) 1.000
BMI (kg/m2) 22.3±3.8 22.6±4.3 0.837
APACHE II 24.4±8.9 32.1±8.3 0.012
SOFA 9.1±3.0 11.7±3.3 0.015
Charlson comorbidity index 3.0 (2.0–4.0) 3.0 (2.0–4.5) 0.715
Acute kidney injury 10 (27.0) 4 (33.3) 0.721
ARDS 8 (21.6) 0 0.173
Mechanical ventilation 25 (67.6) 11 (91.7) 0.142
Blood culture (+) 16 (43.2) 6 (50.0) 0.940
Vital sign on admission
 Systolic blood pressure (mm Hg) 83.7±18.5 84.7±18.3 0.876
 Mean arterial pressure (mm Hg) 64.8±15.1 63.1±16.7 0.746
 Heart rate (bpm) 101.5±25.2 134.3±25.8 <0.001
Use of vasopressor
 Norepinephrine 32 (86.5) 12 (100.0) 0.427
 Dobutamine 2 (5.4) 0 1.000
Laboratory parameter
 WBC (103/µl) 10.3 (7.0–17.1) 9.4 (3.0–14.7) 0.429
 Platelet (103/µl) 155.0 (76.0–271.0) 54.0 (29.0–138.5) 0.024
 Serum albumin (g/dl) 2.4±0.6 2.4±0.5 0.872
 Serum bilirubin (mg/dl) 0.7 (0.4–1.1) 1.0 (0.4–1.9) 0.470
 Serum creatinine (mg/dl) 1.3 (0.9–1.9) 2.0 (1.2–3.6) 0.212
 Lactate (mmol/L) 2.5 (1.6–3.8) 4.0 (2.0–7.6) 0.089
 CRP 179.1 (100.7–257.4) 185.9 (49.5–343.2) 1.000
 Procalcitonin (ng/ml) 5.1 (1.3–30.3) 5.6 (0.8–40.6) 0.917
 DNI (%) 3.2 (1.1–9.5) 26.1 (3.0–45.9) 0.049
Echocardiographic finding
 Ejection fraction (%) 34.9±8.7 32.6±7.5 0.410
 LVEDD (mm) 50.2±5.1 (n=35) 47.6±8.1 (n=11) 0.339
 LVESD (mm) 39.7±5.8 (n=35) 39.1±8.2 (n=11) 0.800
 Mitral E/e’ ratio 12.9±4.8 (n=31) 13.2±10.0 (n=5) 0.943
Cardiac biomarker
 NT-proBNP (pg/ml) 11,983.0 (7,514.5–30,442.0) (n=35) 22,073.0 (3,705.5–35,000.0) (n=11) 0.857
 CK (IU/L) 76.0 (35.0–331.0) 171.0 (59.0–688.0) 0.231
 CK-MB (ng/ml) 4.2 (2.0–7.2) 2.1 (1.5–5.3) 0.236
 Troponin-T (pg/ml) 156.0 (47.0–318.0) 108.0 (62.5–304.0) (n=11) 0.980

Values are presented as mean±standard deviation, number (%), or median (interquartile range).

BMI: body mass index; APACHE: Acute Physiology and Chronic Health Evaluation; SOFA: Sequential Organ Failure Assessment; ARDS: acute respiratory distress syndrome; WBC: white blood cell; CRP: C-reactive protein; DNI: delta neutrophil index; LVEDD: left ventricular end-diastolic diameter; LVESD: left ventricular end-systolic diameter; E: early mitral inflow velocity; e’: mitral annular early diastolic velocity; NT-proBNP: N-terminal pro b-type natriuretic peptide; CK: creatine kinase; CK-MB: creatine kinase-muscle/brain.

Table 6.
Cox proportional hazard regression analysis for 28-day mortality in SIC patients and sepsis patients as a whole
Variable Univariate
Multivariate
HR (95% CI) P-value HR (95% CI) P-value
SIC patient
 APACHE II 1.08 (1.02–1.14) 0.006 1.10 (1.02–1.18) 0.009
 DNI 1.03 (0.01–2.21) 0.027 1.02 (1.00–1.08) 0.026
 Lactate 1.12 (1.01–1.24) 0.036 1.12 (0.74–1.07) 0.210
 EF 0.97 (0.91–1.04) 0.381
 LVEDD 0.94 (0.85–1.04) 0.231
Sepsis patients as a whole
 APACHE II 1.06 (1.03–1.09) <0.001 1.04 (1.01–1.07) 0.004
 DNI 1.03 (0.01–1.04) <0.001 1.02 (1.00–1.03) 0.044
 Lactate 1.12 (1.07–1.16) <0.001 1.07 (1.02–1.13) 0.007
 EF 1.01 (0.99–1.03) 0.321
 LVEDD 0.96 (0.93–0.98) 0.008 0.97 (0.93–1.01) 0.118
 SIC 0.89 (0.0.48–1.65) 0.723 0.88 (0.43–1.74) 0.688

SIC: sepsis-induced cardiomyopathy; HR: hazard ratio; CI: confidential interval; APACHE: Acute Physiology and Chronic Health Evaluation; DNI: delta neutrophil index; EF: ejection fraction; LVEDD: left ventricular enddiastolic diameter.

REFERENCES

1. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016; 315: 801-10.
crossref pmid pmc
2. Parker MM, Shelhamer JH, Bacharach SL, Green MV, Natanson C, Frederick TM, et al. Profound but reversible myocardial depression in patients with septic shock. Ann Intern Med 1984; 100: 483-90.
crossref pmid
3. Jardin F, Brun-Ney D, Auvert B, Beauchet A, Bourdarias JP. Sepsis-related cardiogenic shock. Crit Care Med 1990; 18: 1055-60.
crossref pmid
4. Etchecopar-Chevreuil C, François B, Clavel M, Pichon N, Gastinne H, Vignon P. Cardiac morphological and functional changes during early septic shock: a transesophageal echocardiographic study. Intensive Care Med 2008; 34: 250-6.
crossref pdf
5. Vieillard-Baron A, Caille V, Charron C, Belliard G, Page B, Jardin F. Actual incidence of global left ventricular hypokinesia in adult septic shock. Crit Care Med 2008; 36: 1701-6.
crossref pmid
6. Bouhemad B, Nicolas-Robin A, Arbelot C, Arthaud M, Féger F, Rouby JJ. Acute left ventricular dilatation and shock-induced myocardial dysfunction. Crit Care Med 2009; 37: 441-7.
crossref pmid
7. Sato R, Kuriyama A, Takada T, Nasu M, Luthe SK. Prevalence and risk factors of sepsis-induced cardiomyopathy: a retrospective cohort study. Medicine (Baltimore) 2016; 95: e5031.
crossref pmid pmc
8. Calandra T, Cohen J, International Sepsis Forum Definition of Infection in the ICU Consensus Conference. The international sepsis forum consensus conference on definitions of infection in the intensive care unit. Crit Care Med 2005; 33: 1538-48.
crossref pmid
9. Sato R, Nasu M. A review of sepsis-induced cardiomyopathy. J Intensive Care 2015; 3: 48.
crossref pmid pmc
10. Jeong HS, Lee TH, Bang CH, Kim JH, Hong SJ. Risk factors and outcomes of sepsis-induced myocardial dysfunction and stress-induced cardiomyopathy in sepsis or septic shock: a comparative retrospective study. Medicine (Baltimore) 2018; 97: e0263.
crossref pmid pmc
11. Nahm CH, Choi JW, Lee J. Delta neutrophil index in automated immature granulocyte counts for assessing disease severity of patients with sepsis. Ann Clin Lab Sci 2008; 38: 241-6.
pmid
12. Park BH, Kang YA, Park MS, Jung WJ, Lee SH, Lee SK, et al. Delta neutrophil index as an early marker of disease severity in critically ill patients with sepsis. BMC Infect Dis 2011; 11: 299.
crossref pmid pmc pdf
13. Kruse JA, Thill-Baharozian MC, Carlson RW. Comparison of clinical assessment with APACHE II for predicting mortality risk in patients admitted to a medical intensive care unit. JAMA 1988; 260: 1739-42.
crossref pmid
14. Mikkelsen ME, Miltiades AN, Gaieski DF, Goyal M, Fuchs BD, Shah CV, et al. Serum lactate is associated with mortality in severe sepsis independent of organ failure and shock. Crit Care Med 2009; 37: 1670-7.
crossref pmid
15. Furian T, Aguiar C, Prado K, Ribeiro RV, Becker L, Martinelli N, et al. Ventricular dysfunction and dilation in severe sepsis and septic shock: relation to endothelial function and mortality. J Crit Care 2012; 27: 319.
crossref
16. Pulido JN, Afessa B, Masaki M, Yuasa T, Gillespie S, Herasevich V, et al. Clinical spectrum, frequency, and significance of myocardial dysfunction in severe sepsis and septic shock. Mayo Clin Proc 2012; 87: 620-8.
crossref pmid pmc
17. Weng L, Liu YT, Du B, Zhou JF, Guo XX, Peng JM, et al. The prognostic value of left ventricular systolic function measured by tissue Doppler imaging in septic shock. Crit Care 2012; 16: R71.
crossref pmid pmc
18. Liu YC, Yu MM, Shou ST, Chai YF. Sepsis-induced cardiomyopathy: mechanisms and treatments. Front Immunol 2017; 8: 1021.
crossref pmid pmc
19. Walley KR. Sepsis-induced myocardial dysfunction. Curr Opin Crit Care 2018; 24: 292-9.
crossref
20. Boland TA, Lee VH, Bleck TP. Stress-induced cardiomyopathy. Crit Care Med 2015; 43: 686-93.
crossref pmid
21. Templin C, Ghadri JR, Diekmann J, Napp LC, Bataiosu DR, Jaguszewski M, et al. Clinical features and outcomes of Takotsubo (Stress) cardiomyopathy. N Engl J Med 2015; 373: 929-38.
crossref pmid
22. Kakihana Y, Ito T, Nakahara M, Yamaguchi K, Yasuda T. Sepsis-induced myocardial dysfunction: pathophysiology and management. J Intensive Care 2016; 4: 22.
crossref pmid pmc
23. Bruni FD, Komwatana P, Soulsby ME, Hess ML. Endotoxin and myocardial failure: role of the myofibril and venous return. Am J Physiol 1978; 235: H150-6.
crossref pmid
24. Mehta NJ, Khan IA, Gupta V, Jani K, Gowda RM, Smith PR. Cardiac troponin I predicts myocardial dysfunction and adverse outcome in septic shock. Int J Cardiol 2004; 95: 13-7.
crossref pmid
25. Kim HW, Yoon JH, Jin SJ, Kim SB, Ku NS, Jeong SJ, et al. Delta neutrophil index as a prognostic marker of early mortality in gram negative bacteremia. Infect Chemother 2014; 46: 94-102.
crossref pmid pmc
26. Yune HY, Chung SP, Park YS, Chung HS, Lee HS, Lee JW, et al. Delta neutrophil index as a promising prognostic marker in out of hospital cardiac arrest. PLoS One 2015; 10: e0120677.
crossref pmid pmc
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