This study evaluates sepsis patients at Beth Israel Deaconess Medical Center to determine whether elevated left ventricular ejection fraction predicts 28-day mortality.
Research Article
Prognostic Implications of Elevated Left Ventricular Ejection Fraction in Patients with Sepsis
In This Article
Summary
Abstract
The role of left ventricular systolic function as a prognostic marker for sepsis patients remains an area of ongoing research and debate. The present investigation exhibited the comprehensive evaluation of the relationship between different levels of left ventricular ejection fraction (LVEF) and mortality outcomes in sepsis-diagnosed patients. A retrospective, single-center longitudinal cohort investigation was conducted involving the intensive care unit (ICU) admitted adults' patients at Beth Israel Deaconess Medical Center who underwent transthoracic echocardiography (TTE) during their hospitalization. Individuals diagnosed with sepsis and who received Doppler echocardiography were included in the analysis if transthoracic echocardiography was performed within seven days of ICU admission. All patients of age below 18 or above 90 years, a prior history of cardiac disease or cardiac surgery, and those for whom echocardiography was performed more than seven days after ICU admission were excluded. Patients were stratified into three distinct groups with relation to their LVEF levels: hyperdynamic (LVEF ≥70%), normal (LVEF 55%-70%), and depressed (LVEF ≤55%). The association between different categories of sepsis affected patients mortality outcome and left ventricular ejection fraction (LVEF) was assessed. Among the 3,363 patients analyzed, comprising 1,175 with decreased LVEF, 2,119 with normal LVEF, and 68 with hyperdynamic LVEF, multivariate Cox regression identified hyperdynamic function as the strongest predictor of 28-day mortality. Specifically, hyperdynamic LVEF was independently linked to a 3.643-fold higher hazard of death relative to the normal LVEF group. A significant link has been identified between hyperdynamic left ventricular function and elevated 28-day mortality rates in the ICU-admitted septic patients. This physiological condition underscores the need for enhanced clinical awareness due to its prognostic significance.
Introduction
Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection1. Among the organs affected, the heart is particularly susceptible. The reversible myocardial dysfunction that arises during sepsis, in the absence of underlying ischemic heart disease or pre-existing cardiac conditions, is referred to clinically as septic cardiomyopathy (SCM). The reported incidence of septic cardiomyopathy varies widely, ranging from 10% to 70%2,3.
An important clinical inquiry persists: to what extent does septic cardiomyopathy impact the prognosis of individuals diagnosed with sepsis? Several studies have attempted to address this issue; however, the underlying pathophysiological mechanisms of SCM remain incompletely understood, and a universally accepted definition is still lacking4,5,6,7. This lack of standardization contributes to inconsistencies in related research findings8. Recent molecular analyses also highlight the involvement of regulated cell death pathways and immune infiltration in cardiac dysfunction, suggesting that inflammatory signaling may play a broader role in myocardial impairment under critical illness conditions9.
In routine clinical settings, echocardiography serves as the principal method for evaluating septic cardiomyopathy because it is widely available, non-invasive, and allows for repeated assessments. Cardiac function is typically evaluated using various parameters, including stroke volume, cardiac output, and particularly left ventricular ejection fraction (LVEF), which is widely recognized as the standard measure of left ventricular systolic performance10. Although advanced imaging modalities such as speckle-tracking strain echocardiography and tissue Doppler imaging provide additional insight into myocardial mechanics, LVEF remains the most widely used and clinically accessible measure of systolic function in the ICU setting. Biomarkers such as BNP or troponin may support assessment but lack the immediate hemodynamic relevance that echocardiography offers9,11.
A considerable number of septic patients exhibit abnormalities in LVEF on color Doppler echocardiography, encompassing both decreased and excessively elevated values. Some prior studies have suggested a link between abnormal LVEF especially hyperdynamic LVEF (greater than 70%) and increased mortality among sepsis patients12. Recent advances in molecular cardiology have emphasized the need for improved diagnostic markers and mechanistic insights to better stratify cardiovascular risk across diverse pathological states13. However, these findings remain inconclusive, with other investigations reporting contradictory results6,13,14,15,16,17,18. Given these unresolved questions, A retrospective investigation was undertaken to investigate the correlation between left ventricular ejection fraction and clinical outcomes of the septic patients.
Protocol
The study was conducted using de-identified patient data from the MIMIC-IV database (version 2.2). Approval for use of this dataset was granted by the Institutional Review Board of the Beth Israel Deaconess Medical Center, with a waiver of informed consent due to the anonymized nature of the data. Access to the database was authorized under certification number 60177335. The equipment used is listed in the Table of Materials.
1. Data source
The MIMIC-IV (version 2.2) database was accessed through the PhysioNet platform after completion of the required training. Clinical, laboratory, ICU, and echocardiographic data were retrieved for patients admitted to Beth Israel Deaconess Medical Center from 2008-2019. All downloaded datasets were stored in a secure research environment in accordance with PhysioNet and institutional policies.
2. Patient selection
All ICU-admitted adult patients aged 18-90 years within the dataset were identified. Sepsis was defined according to Sepsis-3 criteria, requiring suspected infection and an acute increase in SOFA score ≥2. Patients who underwent transthoracic echocardiography (TTE) within 7 days of ICU admission were included. Exclusion criteria were applied for patients younger than 18 or older than 90 years, those with a documented history of cardiovascular disease or previous cardiac surgery, and those whose TTE was performed more than 7 days after ICU admission. Demographic and clinical characteristics, including age, sex, height, weight, vital signs, comorbidities, laboratory findings, and the use of vasoactive medications, were extracted. Severity scores, including SOFA and APACHE, were also obtained, along with ICU length of stay and total hospital stay. Only the first ICU admission for each patient was included in the analysis.
3. LVEF measurement and classification
Left ventricular ejection fraction (LVEF) values were obtained from TTE reports. The biplane method of disks (modified Simpson's method) was used to determine end-diastolic volume (EDV) and end-systolic volume (ESV). LVEF was calculated using the formula: LVEF = [(EDV − ESV) / EDV] × 100%. Based on ACC guidelines, LVEF was categorized as reduced (<55%), normal (55%-70%), or hyperdynamic (>70%). Each patient was then assigned to one of the three LVEF groups for comparative analysis.
4. Statistical methods
All analyses were performed using R software (version 4.4.3). Categorical variables were presented as frequencies and percentages, and group comparisons were conducted using the chi-square test. Continuous variables were evaluated for normality using distribution plots. Non-normal continuous variables were reported as medians with interquartile ranges (IQRs), and differences between groups were assessed using the Kruskal-Wallis test. Univariate Cox proportional hazards regression was conducted to identify mortality-associated variables, and statistically significant predictors from the univariate analysis were included in multivariate Cox regression models to determine independent associations. The primary outcome was defined as 28-day mortality, and the secondary outcome as 1-year mortality. Survival analysis was performed using Kaplan-Meier curves stratified by LVEF group, and survival distributions were compared using the log-rank test. A two-sided p-value <0.05 was considered statistically significant.
Results
Baseline characteristics
As shown in Figure 1, the final analysis included 3,362 patients. Of these, 1,175 were categorized into the reduced LVEF group (≤55%), 2,119 had normal LVEF (55%-70%), and 68 patients demonstrated hyperdynamic LVEF (>70%). Table 1 presents the baseline demographic and clinical characteristics of the study population. The cohort had a median age of 69 years (IQR 60-77), and males represented 66% (n = 2,218) of the sample. When comparing the three LVEF groups, the hyperdynamic group demonstrated: (1) a higher median heart rate (85 bpm), (2) more frequent use of norepinephrine (30.9%), and (3) the highest 28-day mortality rate (26.47%). These differences are detailed in Table 2.
Short-term outcomes (28-day mortality)
In the short-term outcome analysis, patients with hyperdynamic LVEF showed the highest 28-day mortality rate, followed by the reduced LVEF group, while the normal LVEF group had the lowest mortality. Kaplan-Meier survival curves (Figure 2) demonstrated a significant difference in 28-day survival among the three groups, with the hyperdynamic group consistently exhibiting the worst short-term survival.
Long-term outcomes (1-year mortality)
At the one-year mark, survival patterns remained consistent. The hyperdynamic LVEF group showed: (1) the lowest long-term survival probability, and(2)significantly higher cumulative mortality compared to normal and reduced LVEF groups.These findings are illustrated in Figure 3, which shows a clear separation of survival curves across the LVEF categories.
Regression analysis
Univariate analysis
The univariate Cox regression identified multiple factors associated with mortality, including age, heart rate, mean arterial pressure (MAP), respiratory rate, platelet count, creatinine, norepinephrine use, SOFA score, APACHE score, comorbidities (DM, MT, CKD), and ICU length of stay. These results are presented in Table 3.
Multivariate Cox regression models
Two multivariate models were constructed: (1) Model 1: adjusted for age and vital signs; (2); Model 2: further adjusted for significant clinical variables identified in univariate analysis. Across all models, the hyperdynamic LVEF group demonstrated the strongest association with increased 28-day mortality, with a 3.643-fold higher hazard compared to the normal LVEF group (Table 4). This elevated risk remained significant after adjustment for confounders in both models. Similarly, hyperdynamic LVEF was strongly associated with increased 1-year mortality, consistent with survival curve patterns shown in Figure 2 and Figure 3.
DATA AVAILABILITY:
Data supporting the findings of this study are provided in Supplementary File 1.
Figure 1: Schematic representation exhibiting the patient selection process for inclusion in the study; TTE: transthoracic echocardiography. Please click here to view a larger version of this figure.
Figure 2: Kaplan-Meier curves of LVEF for 28-day mortality (P＜0.001). Please click here to view a larger version of this figure.
Figure 3: Kaplan-Meier curves of LVEF for 1-year mortality (P＜0.001). Please click here to view a larger version of this figure.
| variables | Overall | depressed LVEF | normal LVEF | hyperdynamic LVEF | p_value |
| age（years） | 69 (60-77) | 69 (60-77) | 69 (61-77) | 70 (64-79) | 0.191 |
| gender | |||||
| F | 1144 (34%) | 324（27.6%） | 783（37.0%） | 37 (54.4%) | ＜0.001 |
| M | 2218 (66%) | 851（72.4%） | 1336（63.0%） | 31 (45.6%) | |
| BMI（kg/㎡） | 28.62 (25.06-32.95) | 28.65 (25.19-32.98) | 28.34 (23.12-31.88) | 27.09 (22.52-33.57) | 0.055 |
| HR | 80 (74-90) | 80 (74-89) | 84 (74-102) | 85 (74-95.25) | 0.01 |
| MAP（mmHg） | 72 (65-82) | 72 (64-81) | 75 (66-89) | 72 (63.75-87) | 0.02 |
| RR | 16 (13-19) | 15 (13-19) | 18 (15-23) | 18 (14-22) | ＜0.001 |
| temperature（℃） | 36.67 (36.44-37) | 36.67 (36.42-37) | 36.67 (36.44-37.03) | 36.78 (36.48-37.12) | 0.225 |
| WBC（10^9/L） | 11.8 (8.6-15.7) | 11.8 (8.6-15.7) | 10.5 (7.4-15.35) | 11.4 (7.68-15.15) | 0.057 |
| platelet（10^9/L） | 159 (123-206) | 158 (123-204.5) | 170 (129-232.5) | 172.5 (132-240.5) | 0.099 |
| creatinine（mg/dL） | 0.9 (0.7-1.2) | 0.9 (0.7-1.2) | 0.9 (0.7-1.35) | 1 (0.7-1.5) | 0.159 |
| norepinephrine（pg/ml） | ＜0.001 | ||||
| NO | 2806（83.46%） | 923（78.6%） | 1836（86.6%） | 47（69.1%） | |
| YES | 556（16.54%） | 252（21.4%） | 283（13.4%） | 21（30.9%） | |
| SOFA | 5 (3-7) | 5 (3-7) | 4 (3-6) | 5 (3-7) | 0.515 |
| APACHE | 36 (27-50) | 36 (27-50) | 39 (29.5-54.5) | 40 (36-55.5) | ＜0.001 |
| DM | ＜0.001 | ||||
| NO | 2339（69.57%） | 768（65.4%） | 1535（72.4%） | 36（52.9%） | |
| YES | 1023（30.43%） | 407（34.6%） | 584（27.6%） | 32（47.1%） | |
| MT | 0.796 | ||||
| NO | 2841（84.50%） | 998（84.9%） | 1787（84.3%） | 56（82.4%） | |
| YES | 521（15.50） | 177（15.1%） | 332（15.7%） | 12（17.6%） | |
| CKD | 0 | ||||
| NO | 2865(85.22%) | 961(81.8%) | 1847(87.2%) | 57(83.8%) | |
| YES | 497(14.78%) | 214(18.2%) | 272(12.8%) | 11(16.2%) | |
| hosp_day | 5.98 (4.63-7.82) | 5.95 (4.63-7.77) | 6.25 (4.52-8.29) | 6.42 (4.74-8.09) | 0.526 |
| icu_day | 2.02 (1.29-3.16) | 2 (1.29-3.13) | 2.24 (1.35-3.62) | 2.47 (1.89-3.99) | ＜0.001 |
| lvef | 56 (50-56) | 45（35-50） | 56（56-56） | 70 (70-70) | ＜0.001 |
Table 1: Baseline demographic and clinical features of the study cohort.
| group | survival | non-survival | mortality |
| depressed | 1014 | 161 | 13.70% |
| normal | 1947 | 172 | 8.12% |
| hyperdynamic | 50 | 18 | 26.47% |
Table 2: 28-day mortality among groups.
| 28-day-mortality | 1-year-mortality | |||||
| variables | OR | 95% CI | P value | OR | 95% CI | P value |
| age | 1.0108 | （1.002-1.0197） | 0.0165 | 1.0171 | （1.0096-1.0246） | ＜0.001 |
| gender | 0.6482 | （0.5177-0.8115） | 0.0004 | 0.6298 | （0.5226-0.9704） | ＜0.001 |
| BMI | 0.9667 | （0.9497-0.984） | 0.0004 | 0.9559 | （0.9417-0.9704） | ＜0.001 |
| heart rate | 1.0357 | （1.0297-1.0418) | ＜0.0001 | 1.0354 | （1.0301-1.0408） | ＜0.001 |
| MAP | 1.0113 | （1.0044-1.0182） | 0.0013 | 1.0135 | （1.0077-1.0193） | ＜0.001 |
| RR | 1.1361 | （1.1166-1.1559） | ＜0.0001 | 1.1419 | （1.124-1.16） | ＜0.001 |
| Temperature | 1.0167 | （0.9518-1.086） | 0.6228 | 0.9927 | （0.9551-1.0319） | 0.711 |
| WBC | 1.0179 | （1.0046-1.0314） | 0.0083 | 1.0075 | （0.998-1.0172） | 0.121 |
| platelet count | 1.0032 | （1.0021-1.0044） | ＜0.0001 | 1.0035 | （1.0025-1.0045） | ＜0.001 |
| creatinine | 1.3551 | （1.2666-1.4497） | ＜0.0001 | 1.4668 | （1.3649-1.5764） | ＜0.001 |
| norepinephrine | 10.0965 | （7.9495-12.8235） | ＜0.0001 | 7.0292 | （5.7213-8.6362） | ＜0.001 |
| SOFA scores | 1.383 | （1.332-1.4359） | ＜0.0001 | 1.2855 | （1.2458-1.3265） | ＜0.001 |
| APACHE scores | 1.0587 | （1.0528-1.0646） | ＜0.0001 | 1.0499 | （1.0449-1.0548） | ＜0.001 |
| DM | 0.9482 | （0.744-1.2086） | 0.6676 | 1.1551 | （0.95-1.4044） | 0.148 |
| MT | 1.695 | （1.2937-2.2208） | 0.0001 | 1.4066 | （1.1113-1.7802） | 0.005 |
| CKD | 2.2954 | （1.7698-2.977） | ＜0.0001 | 2.3315 | （1.8672-2.9113） | ＜0.001 |
| hospital stay | 0.9975 | （0.9776-1.0177） | 0.804 | 1.0503 | （1.0355-1.0635） | ＜0.001 |
| icu stay | 1.2076 | （1.1598-1.2574） | ＜0.0001 | 1.3259 | （1.2662-1.3884） | ＜0.001 |
| lvef | 0.9691 | （0.9598-0.9785） | ＜0.0001 | 0.968 | （0.96-0.976） | ＜0.001 |
Table 3: Univariate analysis of short-term (28-day) and long-term (1-year) mortality rates.
| 28-day mortality | LVEF group | HR | 95%CI | P value |
| unadjusted | normal | Ref | ||
| depressed | 1.748 | 1.410-2.168 | ＜0.001 | |
| hyperdynamic | 3.643 | 2.242-5.921 | ＜0.001 | |
| Model1 | normal | Ref | ||
| depressed | 1.649 | 1.327-2.048 | ＜0.001 | |
| hyperdynamic | 2.855 | 1.755-4.646 | ＜0.001 | |
| Model2 | normal | Ref | ||
| depressed | 1.368 | 1.098-1.703 | 0.005 | |
| hyperdynamic | 2.068 | 1.259-3.397 | 0.004 | |
| 1-year mortality | ||||
| unadjusted | normal | Ref | ||
| depressed | 1.536 | 1.294-1.823 | ＜0.001 | |
| hyperdynamic | 2.483 | 1.578-3.910 | ＜0.001 | |
| Model1 | normal | Ref | ||
| depressed | 1.45 | 1.220-1.723 | ＜0.001 | |
| hyperdynamic | 1.969 | 1.250-3.100 | 0.003 | |
| Model2 | normal | Ref | ||
| depressed | 1.258 | 1.055-1.498 | 0.011 | |
| hyperdynamic | 1.413 | 0.891-2.242 | 0.142 |
Table 4: Cox regression model（28-day and 1-year mortality).
Supplementary File 1: Data supporting the findings of this study. Please click here to view a larger version of this figure.
Discussion
This study demonstrates a significant association between hyperdynamic left ventricular ejection fraction (LVEF) and increased 28-day mortality among septic patients admitted to the intensive care unit. This association remained consistent even after adjusting for confounding variables, underscoring the robustness of the findings. These results align with previously published work that has reported similar physiological patterns among patients with hyperdynamic ventricular function, including elevated cardiac output, increased heart rates, greater reliance on vasopressor therapy, and worse clinical outcomes13,19,20,21.
Hyperdynamic LVEF is typically identified using transthoracic echocardiography and is defined as a value ≥70%22. In the present cohort, hyperdynamic systolic function occurred in 2.02% of septic patients, a lower proportion than the 18.2% reported in prior studies23. Growing evidence suggests that hyperdynamic ventricular function reflects profound disturbances in systemic vascular resistance and microcirculatory flow, and may signal severe vasoplegia or exaggerated catecholamine-driven cardiovascular activation. These mechanisms offer a physiologic explanation for the increased mortality observed in this subgroup.
Pathophysiological Implications
LVEF is influenced by preload, afterload, and myocardial contractility, and abnormalities in any of these factors can contribute to hyperdynamic function24. Previous work has demonstrated that patients with hyperdynamic LVEF often present with markedly reduced systemic vascular resistance (SVR), supporting the theory that hyperdynamic function may represent a compensatory response to severe vasoplegia. Catecholamine excess represents another contributing mechanism, frequently manifesting as tachycardia, which has been independently associated with hyperdynamic states25. In such cases, ultrashort-acting beta-blockers have shown clinical benefit. Conversely, when hyperdynamic LVEF develops in the setting of inadequate fluid resuscitation, beta-blockade may worsen hemodynamics, emphasizing the importance of accurate etiologic assessment26,27.
Methodological considerations and critical steps
Because this study relies on retrospective data extracted from the MIMIC-IV database, several methodological aspects directly influence the reliability and interpretation of findings:
Timing of echocardiography:
LVEF values were included only when measured within seven days of ICU admission. This step is essential because delayed echocardiography may reflect progression of disease severity rather than initial cardiovascular status. Early imaging improves comparability across patients and reduces temporal bias.
Use of the modified Simpson method:
LVEF extraction based on end-diastolic and end-systolic volumes calculated via the biplane Simpson method reduces measurement variability and improves alignment with ACC recommendations. Variability in measurement technique is a common limitation of echocardiographic studies, making standardized volume-based assessment a critical methodological safeguard.
Adjustment for confounding clinical variables:
The Cox models incorporated age, vital signs, organ dysfunction scores (SOFA, APACHE), vasoactive medication use, and comorbidities. Adjusting for these variables is essential because failure to do so can inflate or obscure the true association between LVEF and mortality.
Data cleaning and unit consistency:
Harmonizing units (e.g., mmHg for MAP, beats/min for HR) and excluding implausible values are necessary to ensure reproducibility, particularly when extracting data from large electronic health record repositories. These critical methodological steps should be clearly followed in future analyses to ensure accurate replication and interpretation.
Troubleshooting and Common Edge Cases
Several challenges arise when assessing LVEF in septic populations:
Poor-quality echocardiographic windows:
Septic patients may have edema, mechanical ventilation, or hemodynamic instability that limits image quality. When feasible, repeating TTE or using contrast-enhanced imaging can help improve accuracy.
Load-dependent fluctuations in LVEF:
Rapid changes in preload or afterload due to vasopressor titration, fluid administration, or diuresis can transiently alter LVEF. Clinicians should interpret borderline or unexpected hyperdynamic values in the context of hemodynamic interventions occurring near the time of imaging.
Arrhythmias:
Atrial fibrillation or frequent ectopy may distort volume measurements; averaging multiple beats or relying on additional indices (e.g., stroke volume, LVOT VTI) can improve reliability.
Missing vasopressor dosing data:
Although the presence of norepinephrine use was captured, dosage and duration were unavailable in the dataset. This limitation affects precision but is inherent to the database structure.
Comparison with alternative assessment frameworks
While LVEF is a simple and widely accessible method of assessing systolic function, it provides only a partial view of septic cardiomyopathy. Techniques such as strain echocardiography, tissue Doppler imaging, and biomarkers (e.g., BNP, troponin) can offer additional insight into myocardial mechanics, diastolic dysfunction, or cardiac stress28. However, these modalities are not consistently available in ICU settings and require more operator expertise. In contrast, LVEF, despite being load-dependent, remains the most practical measure due to its rapid acquisition, broad familiarity, and strong integration into most ICU workflows. This trade-off underscores why LVEF continues to serve as a primary marker for prognostic assessment in sepsis.
Clinical implications
From a clinical perspective, hyperdynamic LVEF may serve as an indicator of systemic vascular collapse, excessive adrenergic stimulation, or inadequate intravascular volume. Early recognition of this phenotype may encourage more cautious vasopressor titration, deeper evaluation of microvascular dysfunction, or reevaluation of fluid responsiveness. Understanding the context in which hyperdynamic LVEF arises is therefore essential for tailoring management strategies to individual patients.
Limitations
This study has several limitations. It is a single-center retrospective analysis with a relatively small hyperdynamic subgroup, which may limit generalizability. The exclusion of patients without transthoracic echocardiography introduces selection bias. Furthermore, limited echocardiographic parameters within the database prevented assessment of diastolic function, strain, or structural abnormalities. The absence of serial TTE measurements restricted the evaluation of dynamic changes in LVEF over time. Finally, the observational nature of the study precludes causal inference. Prospective multicenter studies with serial echocardiographic assessment are needed to better define the prognostic significance of LVEF trajectories in sepsis.
Conclusions
Hyperdynamic LVEF is strongly associated with increased short-term mortality in septic ICU patients. Given its accessibility and prognostic value, LVEF may serve as a clinically useful hemodynamic marker when interpreted within the broader context of vascular tone, adrenergic activation, and volume status. Future research should further explore the underlying mechanisms driving hyperdynamic function and evaluate strategies for improved clinical management of this high-risk subgroup.
Disclosures
The authors declare no competing interests.
Materials
| Name | Company | Catalog Number | Comments |
|---|---|---|---|
| Color Doppler Echocardiography unit | Siemens | Siemens Acuson X300 / X700 Series | Used to evaluate blood flow, cardiac hemodynamics, and support LVEF measurement |
| Transthoracic Echocardiography (TTE) System | Siemens | Siemens Acuson SC2000 PRIME | Used for cardiac ultrasound imaging; LVEF |
References
- Singer, M., Deutschman, C. S., Seymour, C. W. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 315 (8), 801-810 (2016).
- Hollenberg, S. M., Singer, M. Pathophysiology of sepsis-induced cardiomyopathy. Nat Rev Cardiol. 18 (6), 424-434 (2021).
- Beesley, S. J., et al. Septic Cardiomyopathy. Crit Care Med. 46 (4), 625-634 (2018).
- Sevilla Berrios, R. A., O'Horo, J. C., Velagapudi, V., Pulido, J. N. Correlation of left ventricular systolic dysfunction determined by low ejection fraction and 30-day mortality in patients with severe sepsis and septic shock: A systematic review and meta-analysis. J Crit Care. 29 (4), 495-499 (2014).
- Longino, A. A., et al. Decreased left ventricular ejection fraction is associated with increased mortality in sepsis: A retrospective cohort study. Eur J Heart Fail. 27 (1), 174-177 (2024).
- Landesberg, G., et al. Diastolic dysfunction and mortality in severe sepsis and septic shock. Eur Heart J. 33 (7), 895-903 (2011).
- Parker, M. M. Profound but reversible myocardial depression in patients with septic shock. Ann Intern Med. 100 (4), 483(1984).
- Morelli, A., et al. Effect of heart rate control with esmolol on hemodynamic and clinical outcomes in patients with septic shock: A randomized clinical trial. JAMA. 310 (16), 1683-1691 (2013).
- Zhu, Y., et al. Identification of necroptosis and immune infiltration in heart failure through bioinformatics analysis. J Inflamm Res. 18, 2465-2481 (2025).
- Monge García, M. I., Cecconi, M., Pinsky, M. R. Assessing left ventricular systolic function with ejection fraction: using a double-edged knife as a hammer. Ann Intensive Care. 9 (1), 111(2019).
- Boissier, F., et al. Left ventricular systolic dysfunction during septic shock: The role of loading conditions. Intensive Care Med. 43 (5), 633-642 (2017).
- Paonessa, J. R., et al. Hyperdynamic left ventricular ejection fraction in the intensive care unit. Crit Care. 19 (1), 288(2015).
- Huang, S. J., Nalos, M., McLean, A. S. Is early ventricular dysfunction or dilatation associated with lower mortality rate in adult severe sepsis and septic shock? A meta-analysis. Crit Care. 17 (3), R96(2013).
- McLean, A. S., et al. Prognostic values of B-type natriuretic peptide in severe sepsis and septic shock. Crit Care Med. 35 (4), 1019-1026 (2007).
- Vieillard-Baron, A., et al. Actual incidence of global left ventricular hypokinesia in adult septic shock. Crit Care Med. 36 (6), 1701-1706 (2008).
- Johnson, A. E. W., et al. a freely accessible electronic health record dataset. Sci Data. 10, 1(2023).
- Heidenreich, P. What Is a Normal Left Ventricular Ejection Fraction. Circulation. 148 (9), 750-752 (2023).
- Chotalia, M., et al. Hyperdynamic left ventricular ejection fraction in ICU patients with sepsis. Crit Care Med. 50 (5), 770-779 (2021).
- Luo, G., et al. M2 macrophage-derived exosomes induce angiogenesis and increase skin flap survival through HIF1AN/HIF-1α/VEGFA control. Arch Biochem Biophys. 751, 109822(2023).
- Dugar, S., et al. Is left ventricular systolic dysfunction associated with increased mortality among patients with sepsis and septic shock. Chest. 163 (6), 1437-1447 (2023).
- Chawla, S., et al. Correlation between tissue Doppler-derived left ventricular systolic velocity (S') and left ventricular ejection fraction in sepsis and septic shock: A retrospective cohort study. J Intensive Care. 11 (1), (2023).
- Miller, A. L., et al. Left ventricular ejection fraction assessment among patients with acute myocardial infarction and its association with hospital quality of care and evidence-based therapy use. Circ Cardiovasc Qual Outcomes. 5 (5), 662-671 (2012).
- Zhang, Y., et al. Formononetin alleviates no reflow after myocardial ischemia-reperfusion via modulation of gut microbiota to inhibit inflammation. Life Sci. 358, 123110(2024).
- Sato, R., et al. Prevalence and prognosis of hyperdynamic left ventricular systolic function in septic patients: a systematic review and meta-analysis. Ann Intensive Care. 14 (1), 22(2024).
- Sanfilippo, F., et al. Left ventricular systolic function evaluated by strain echocardiography and relationship with mortality in patients with severe sepsis or septic shock: A systematic review and meta-analysis. Crit Care. 22 (1), 183(2018).
- Petitjeans, F., et al. Is the sympathetic system detrimental in the setting of septic shock, with antihypertensive agents as a counterintuitive approach? A clinical proposition. J Clin Med. 10 (19), 4569(2021).
- Wang, J., et al. Evaluating the effects of Esmolol on cardiac function in patients with Septic cardiomyopathy by speck-tracking echocardiography-a randomized controlled trial. BMC Anesthesiol. 23 (1), (2023).
- Morelli, A., et al. Microvascular effects of heart rate control with esmolol in patients with septic shock. Crit Care Med. 41 (9), 2162-2168 (2013).