Effect of levosimendan on plasma intestinal barrier factors in heart failure patients with reduced ejection fraction

Abstract

Objective

In addition to dyspnea and edema, gastrointestinal discomfort is common among patients with heart failure (HF). Reduced cardiac output can lead to inadequate perfusion of the intestinal mucosa and subsequent impairment of the intestinal barrier. Levosimendan, a novel inotropic agent, binds to cardiac troponin C to enhance calcium sensitivity, activates ATP-dependent potassium channels in cardiomyocytes and vascular smooth muscle cells, exerts positive inotropic and vasodilatory effects, and reduces free radical generation, thereby improving systemic hemodynamics including intestinal circulation. However, clinical evidence regarding its protective effects on the intestinal barrier in HF patients remains limited, and the underlying mechanisms require further clarification. This study aims to investigate whether levosimendan confers protective effects on the intestinal barrier in HF patients and to explore its potential mechanisms.

Methods

Network pharmacology was first used to analyze potential mechanisms of levosimendan in treating intestinal barrier dysfunction among HF patients. A total of 62 hospitalized patients with acute exacerbation of HF with reduced ejection fraction (HFrEF) were enrolled based on echocardiographic left ventricular ejection fraction. According to clinical medication regimens, patients were assigned to a conventional treatment group (n=31) or a levosimendan treatment group (n=31). The conventional treatment group received standard anti-HF therapy, while the levosimendan treatment group received levosimendan in addition to standard therapy. Enzyme-linked immunosorbent assays were used to measure plasma levels and changes in the intestinal-barrier proteins zonulin, intestinal fatty acid binding protein (I-FABP), proinflammatory cytokines [interleukin (IL)-17, IL-6, and tumor necrosis factor (TNF)-α], anti-inflammatory cytokine IL-10, and N-terminal pro-brain natriuretic peptide (NT-proBNP). Improvements in cardiac function and gastrointestinal symptoms were evaluated using the Kansas City Cardiomyopathy Questionnaire (KCCQ) and the Gastrointestinal Symptom Rating Scale (GSRS).

Results

Network pharmacology indicated that the effects of levosimendan on intestinal barrier dysfunction in HF patients may involve inflammation-related pathways such as IL-17 and TNF. Clinically, after treatment, zonulin decreased by 32.94 ng/mL in the levosimendan treatment group versus 15.05 ng/mL in the conventional treatment group (P<0.05). I-FABP decreased by 6.97 pg/mL in the levosimendan treatment group but increased by 35.16 pg/mL in the conventional treatment group (P<0.05). IL-6, IL-17, and TNF-α decreased by 1.11 pg/mL, 1.21 pg/mL, and 2.83 pg/mL, respectively, in the levosimendan treatment group, whereas they increased by 7.68 pg/mL, 0.67 pg/mL, and 2.38 pg/mL in the conventional treatment group (all P<0.05). IL-10 decreased by 24.48 pg/mL in the conventional treatment group but increased by 24.98 pg/mL in the levosimendan treatment group (P<0.05). NT-proBNP increased by 7.35 pg/mL in the conventional treatment group but decreased by 4.73 pg/mL in the levosimendan treatment group (P<0.05). KCCQ scores increased by 0.36 in the conventional treatment group and 1.86 in the levosimendan treatment group, GSRS scores decreased by 1.00 in the conventional treatment group and 2.40 in the levosimendan treatment group, respectively, but the differences were not statistically significant (both P>0.05).

Conclusion

Levosimendan not only improves HF and gastrointestinal symptoms in hospitalized patients with acute exacerbation of HFrEF but also reduces plasma intestinal barrier factor levels. These effects may be associated with decreased plasma proinflammatory cytokines and increased anti-inflammatory cytokines after treatment, potentially involving IL-17 and TNF signaling pathways.

Heart failure (HF) is a clinical syndrome and the final stage of various cardiac diseases. Patients not only experience circulatory system disorders but also multi-organ dysfunction, leading to poor quality of life and high mortality risk. According to the 2023 European Society of Cardiology (ESC) Guidelines for the Diagnosis and Treatment of Acute and Chronic Heart Failure^[1], HF phenotypes are defined by left ventricular ejection fraction (LVEF): 1) HF with reduced ejection fraction (HFrEF, LVEF≤40%); 2) HF with mildly reduced ejection fraction (HFmrEF, 40%<LVEF<50%); 3) HF with preserved ejection fraction (HFpEF, LVEF≥50%).

Globally, HFrEF has the highest prevalence among the 3 types of HF. Despite significant advances in the treatment of HFrEF in recent decades, its incidence and mortality remain high, with a 5-year survival rate of only 25% following hospitalization for HFrEF^[2]. Therefore, it is crucial to identify more effective and novel therapies for HF.

In addition to typical symptoms such as dyspnea and edema, gastrointestinal discomfort is also common in patients with chronic HF (CHF). A study^[3] found that 27% of HF patients experienced upper gastrointestinal symptoms, while over 50% had anorexia due to taste or swallowing difficulties. Constipation and loss of appetite were also frequently observed^[3]. The prevalence of constipation among hospitalized cardiovascular disease patients is approximately 50%^[4]. These gastrointestinal symptoms can impair digestive and absorption functions in HF patients, increasing the risk of malnutrition and even progressing to “cardiac cachexia”, which is characterized by protein-calorie malnutrition, muscle wasting, and peripheral edema^[5]. One potential cause of gastrointestinal dysfunction and discomfort in these patients may be intestinal barrier dysfunction.

The intestinal barrier, which separates the lumen from underlying tissues, consists of the intestinal mucosa and epithelial cells. The intestinal epithelium controls transcellular and paracellular flux of nutrients, water, and ions; paracellular permeability is governed by junctional complexes—tight junctions, adherens junctions, desmosomes, and gap junctions—of which tight-junction proteins (occludin, zonulin, and claudins) are critical for barrier integrity. Disease-associated hyperpermeability coincides with altered expression and distribution of these proteins^[6]. Zonulin, a human endogenous analog of zonula occludens (ZO) toxin, regulates intestinal permeability by disassembling the tight junction protein complex. Zonulin release increases intestinal permeability^[7]. Intestinal fatty acid binding protein (I-FABP), a 15 kD (1 D=1 u) cytosolic protein, binds and transports fatty acids, mainly located in the absorptive epithelial cells of the intestinal villi. When epithelial cells are damaged, the distribution and expression of tight junction complexes change, leading to increased levels of zonulin and I-FABP in the blood^[8].

In HF, visceral venous congestion and low cardiac output jointly disrupt the intestinal barrier: Congestion-induced hypoxia and acidosis activate sodium-hydrogen exchanger 3, altering the luminal milieu, while chronic hypoperfusion causes villous ischemia, mucosal edema, and wall thickening. The resulting epithelial injury facilitates bacterial translocation and endotoxin absorption, fuelling systemic inflammation and multi-organ failure^[9]. Therefore, both congestion and ischemia in the intestines contribute to the decline in intestinal barrier function, and the extent of this damage correlates with the severity of HF^[10-11]. I-FABP and zonulin, which are derived from intestinal epithelial cells, have been shown to be elevated in the circulation in relation to increased intestinal permeability^[12-13].

According to the ESC guidelines for HF^[1], in addition to conventional treatments such as diuretics, vasodilators, positive inotropes, angiotensin converting enzyme inhibitor (ACEI)/angiotensin receptor blockers (ARBs), β-blockers, angiotensin receptor-neprilysin inhibitors (ARNI), mineralocorticoid receptor antagonists (MRA), and sodium-dependent glucose transporters 2 (SGLT-2) inhibitors, the use of the novel positive inotropic agent levosimendan is also recommended for the treatment of severe HFrEF patients to improve quality of life, and reduce hospitalization rates.

Levosimendan, a calcium sensitizer, augments contractility via Ca²⁺ dependent binding to troponin C without impairing relaxation. It opens ATP-dependent potassium sensitive channels, dilating coronary resistance vessels, and inhibits phosphodiesterase 3 (PDE3), elevating cyclic adenosine monophosphate (cAMP)/cyclic guanosine monophosphate (cGMP) and further enhancing inotropy while reducing peripheral resistance and improving perfusion^[14-15]. Research^[16] in Wistar rat models has established that levosimendan exerts protective effects against mesenteric ischemia-reperfusion injury and associated multi-organ failure by suppressing oxidative stress, inflammation, and apoptosis. A study^[17] on septic shock pigs demonstrated that levosimendan pretreatment improved ventricular contraction, heart function, and hemodynamics, enhancing portal venous blood flow and intestinal oxygen delivery. These studies suggest that levosimendan improves both systemic hemodynamics and local blood perfusion, increasing intestinal mucosal oxygenation, preventing mucosal acidosis, and improving intestinal barrier function. However, the exact mechanism remains unclear. Network pharmacology, which has become an important tool in systematic pharmacology research, aims to elucidate drug actions and their interactions with multiple targets^[18]. This study aims to observe the changes and effects of levosimendan on plasma intestinal barrier markers and inflammatory factors in HFrEF patients and explore its potential mechanisms.

1. Materials and methods

1.1. Ethics statement

This study was approved by the Medical Ethics Committee of Xiangya Hospital of Central South University and registered and filed on the Ethics Review Cloud Platform (registration number: 202305364). This study conformed to the principles outlined in the Declaration of Helsinki. All patients provided written informed consent before enrolment in the study.

1.2. Network pharmacological analysis

Using “levosimendan” as the keyword, the related target genes of levosimendan were retrieved from the DrugBank database. Then, the therapeutic target genes related to HF and intestinal barrier diseases were searched in the GeneCards and Online Mendelian Inheritance in Man (OMIM) databases by using “heart failure” and “intestinal barrier” as keywords.

The intersection of these 3 gene sets were obtained through the online Venn diagram tool (https://jvenn.toulouse.inrae.fr/app/example.html). The intersected genes of levosimendan targets, HF therapeutic targets, and intestinal barrier therapeutic targets were imported into the STRING database (https://cn.string-db.org) for protein- protein interaction (PPI) network analysis. Network visualization analysis was performed with Cytoscape (version 3.7.2).

Then, the intersected genes were imported into the the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database (https://davidbioinformatics. nih.gov/) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A threshold of P<0.01 was set to filter the top-ranked biological processes. Histograms for biological processes, cellular components, and molecular functions, as well as bubble charts for KEGG enrichment analysis, were generated using Bioinformatics (http://www.bioinformatics.com.cn/).

1.3. Study design and participants

The study comprised 62 hospitalized patients diagnosed with HFrEF enrolled between January and August 2023. Medication use was not investigator-assigned; patients were categorized according to the therapies they actually received into 2 groups: A conventional treatment group (n=31) received conventional basic anti-HF medication, while a levosimendan treatment group (n=31) received conventional anti-HF medication alongside levosimendan treatment.

Patients were eligible if they met all the following criteria: Age 18 years or older, LVEF <40%, and hospitalization due to acute decompensation of CHF with reduced ejection fraction.

Individuals were excluded for active or recent malignancies, prior antitumor therapies such as radiotherapy or immunosuppressive drugs, or structural cardiovascular abnormalities including congenital heart defects and valvular disease. Additional exclusions comprised cardiogenic shock, mechanical obstruction affecting ventricular function, severe renal dysfunction (creatinine clearance <30 mL/min) or hepatic impairment, hypotension or tachycardia, inflammatory or functional bowel disorders, hypersensitivity to levosimendan.

All patients received standardized anti-HF therapy upon hospitalization, including oxygen therapy, dietary guidance, and based on individual patient conditions, diuretics, digitalis to alleviate HF symptoms, β-blockers to prevent cardiac sudden death, and MRA combined with ACEI or ARB or ARNI for anti-remodeling.

Patients in the levosimendan treatment group received additional intravenous levosimendan (Qilu Pharmaceutical Co., Ltd; 12.5 mg/5 mL vial; approval number H20100043). Administration followed the product label: After an initial loading dose of 6-12 μg/kg given intravenously over ≥10 min, a continuous infusion was started at 0.1 μg/(kg·min). Provided the drug was well tolerated, the rate was increased to 0.2 μg/(kg·min) after 2 hours and maintained for a total infusion duration of 24 hours.

1.4. Measurement of plasma biomarkers

Fasting venous blood samples (2 mL) were collected from all patients via antecubital venipuncture the morning following hospital admission. In the levosimendan treatment group, a second sample was obtained on the 5th day (120 hours) after initiating the levosimendan infusion, while the conventional treatment group underwent repeat sampling at the same timepoint following standard anti-HF therapy. All blood samples were centrifuged within 30 min of collection using a high-speed benchtop centrifuge at 3 000 r/min for 15 min. The resulting plasma was aliquoted into microtubes and stored at -8 ℃ until analysis.

Plasma concentrations of intestinal barrier biomarkers (zonulin and I-FABPs), pro-inflammatory cytokines [interleukin (IL)-17, IL-6, tumor necrosis factor (TNF)-α], the anti-inflammatory cytokine IL-10, and N-terminal pro-brain natriuretic peptide (NT-proBNP) were quantified using commercially available enzyme-linked immunosorbent assay (ELISA) kits (Shanghai Yuanquan Biotechnology Center, China).

1.5. Patient-reported outcome assessments

The Gastrointestinal Symptom Rating Scale (GSRS) and the Kansas City Cardiomyopathy Questionnaire (KCCQ) were administered to all patients on the evening of hospital admission and on the 5th day of hospitalization (120 hours post-enrollment).

The GSRS assesses gastrointestinal dysfunction across 5 domains: Reflux, abdominal pain, indigestion, diarrhea, and constipation. This 15-item instrument employs a 7-point Likert scale, where 1 indicates absence of bothersome symptoms and 7 represents severe symptom burden^[19].

The KCCQ, recognized by the U.S. Food and Drug Administration as a validated clinical outcome assessment and recommended for quantifying quality-of-care metrics^[20], evaluates HF-related symptoms, physical limitations, and quality of life. Scores range from 0 to 100, with higher values reflecting milder symptoms, fewer activity restrictions, and improved well-being.

1.6. Statistical analysis

Statistical analysis was performed using SPSS 26.0 and GraphPad Prism 9.0 softwares. Normally distributed continuous variables were expressed as mean±standard deviation and analyzed using independent samples t-test. Non-normally distributed data were presented as median (interquartile range) and analyzed using Mann-Whitney U test. Categorical variables were compared using χ ² test. Spearman’s rank correlation analysis was employed to assess variable associations, with statistical significance defined as two-tailed P<0.05. The Spearman correlation heatmap was generated using the Chiplot online platform (https://www.chiplot.online/).

2. Results

2.1. Results of network pharmacological analysis

Target genes associated with levosimendan (103 genes, DrugBank), HF (12 763 genes, OMIM/GeneCards), and intestinal barrier dysfunction (5 716 genes) were intersected to identify 92 overlapping candidates (Figure 1A). PPI network analysis (STRING database) revealed 8 hub genes (CASP3, MMP9, NFKBIA, MAPK14, NGF, MAPK8, RELA, MPO) with degree values ≥ 4×median (Figure 1B).

Figure 1. Key gene identification.

A: Venn diagram of targets of levosimendan, heart failure disease and intestinal barrier; B: Protein-protein interaction network diagram of intersection genes of levosimendan, heart failure, and intestinal barrier.

KEGG pathway analysis (DAVID database, P<0.01, FDR<0.01) highlighted the IL-17 and TNF signaling pathways as central mechanisms (Figure 2B). These pathways exhibited the strongest associations (red-hued bubbles, smallest P-values) and highest gene counts, suggesting their critical role in levosimendan’s therapeutic effects on HF and intestinal barrier regulation.

Figure 2. Result of enrichment analysis.

A: Diagram of intersection gene GO enrichment analysis; B: KEGG enriched bubble map of interacting genes. GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; MAP: Mitogen-activated protein; TNF: Tumor necrosis factor; IL: Interleukin.

2.2. Characteristics of study population

The demographic, clinical and biochemical data for both groups are shown in Table 1. In the 2 groups with different modes of administration, there were no statistically significant differences in gender, age, body mass index (BMI), diabetes, hypertension, coronary heart disease, dilated cardiomyopathy, fasting blood glucose, NT-proBNP (electrochemiluminescence immunoassay), total cholesterol (TC), triglyceride (TG), high-density lipo-protein (HDL), and low-density lipoprotein (LDL) (all P>0.05). The levosimendan treatment group showed significantly higher white blood cell (WBC) and neutrophil (NEUT) counts than the conventional treatment group (both P<0.05).

Table 1.

Comparison of baseline clinical characteristics of HFrEF patients between the 2 groups

Group	n	Age/year	Male/[No.(%)]	BMI/(kg·cm-2)	Hypertension/[No.(%)]	Diabetes/ [No.(%)]
Conventional treatment group	31	69.63±10.11	22(70.97)	23.00±3.48	15(48.39)	8(25.81)
Levosimendan treatment group	31	67.94±10.71	18(58.06)	23.30±3.82	17(54.84)	13(41.94)
t/U/χ 2		-0.682*	1.127†	-0.324*	0.258†	1.790†
P		0.946	0.288	0.747	0.611	0.180

Group	Coronary artery disease/ [No.(%)]	Dilated cardiomyopathy/[No.(%)]	Fasting plasma glucose/ (mmol·L-1)	NT-proBNP/(pg·mL-1)	TC/ (mmol·L-1)
Conventional treatment group	14(45.16)	5(16.13)	5.34(4.31, 6.13)	6 985.88(3 311.01, 17 262.12)	3.69±1.28
Levosimendan treatment group	18(58.06)	7(22.58)	5.50(4.78, 8.85)	7 332.66(2 926.63, 15 299.82)	5.08±3.47
t/U/χ 2	1.033†	0.413†	139.000‡	501.000‡	1.704*
P	0.309	0.520	0.331	0.773	0.270

Group	TG/ (mmol·L-1)	HDL/(mmol·L-1)	LDL/(mmol·L-1)	WBC/ (109·L-1)	NEUT/ (109·L-1)	EF/%	LV/mm
Conventional treatment group	1.12(0.65, 1.85)	0.92±0.24	2.40±0.90	6.55(4.38, 7.70)	4.90(3.18, 5.62)	40.70±13.50	56.22±8.36
Levosimendan treatment group	1.22(0.78, 1.48)	1.03±0.28	2.74±0.89	7.15(5.60, 11.50)	5.15(3.58, 8.88)	35.27±13.08	60.47±12.02
t/U/χ 2	193.000‡	1.368*	1.228*	236.000‡	236.500‡	1.607*	-1.616*
P	0.496	0.776	0.721	0.004	0.004	0.128	0.131

Normally distributed continous variables are expressed as mean±standard deviation, normally distributed continous variables are expressed as median (the 1st quartile, the 3rd quartile), *t value, †χ ² value, ‡U value. HFrEF: Heart failure with reduced ejection fraction; BMI: Body mass index; NT-proBNP: N-terminal pro-brain natriuretic peptide; TC: Total cholesterol; TG: Triglyceride; HDL: High-density lipoprotein; LDL: Low-density lipoprotein; WBC: White blood cell; NEUT: Neutrophil; EF: Ejection fraction; LV: Left ventricle.

2.3. Changes in intestinal barrier markers

Prior to treatment, no statistically significant differences were observed in serum levels of intestinal barrier markers (zonulin and I-FABPs) between the 2 groups. As shown in Table 2, both groups exhibited reduced plasma zonulin levels post-treatment. Compared to the conventional treatment group, the levosimendan treatment group demonstrated a more pronounced decrease in zonulin levels after the treatment (P<0.05). Specifically, the levosimendan treatment group showed a reduction of 32.94 ng/mL in plasma zonulin, whereas the conventional treatment group had a decrease of 15.05 ng/mL (Table 2).

Table 2.

Comparison of intestinal barrier factor levels of HFrEF patients between the 2 groups (n=31)

Group	Zonulin/(ng·mL-1)			I-FABPs/(pg·mL-1)
	Pre-treatment	Post-treatment	Change value	Pre-treatment	Post-treatment	Change value
Conventional treatment group	501.46±121.58	487.66±50.77	-15.05(-39.70, 17.21)	750.02±190.07	785.18±139.97	35.16±72.74
Levosimendan treatment group	519.83±261.74	473.35±55.10	-32.94(-59.82, -11.90)	816.62±383.68	809.65±415.96	-6.97±79.61
t	-0.354	1.062	290.000	-0.866	-0.310	2.156
P	0.725	0.344	0.028	0.391	0.757	0.035

I-FABPs: Intestinal fatty acid-binding protein.

I-FABPs levels increased moderately in the conventional treatment group post-treatment (35.16 pg/mL), whereas a decline of 6.97 pg/mL was observed in the levosimendan treatment group (Table 2).

2.4. Changes in inflammatory and anti-inflammatory cytokines

No significant intergroup differences were detected in baseline levels of inflammatory cytokines (IL-6, TNF-α, IL-17) or anti-inflammatory cytokine IL-10 between the conventional treatment group and the levosimendan treatment group (all P>0.05, Table 3).

Table 3.

Comparison of inflammatory and anti-inflammatory factor levels of HFrEF patients between the 2 groups (n=31)

Group	IL-6/(pg·mL-1)			IL-17/(pg·mL-1)
	Pre-treatment	Post-treatment	Change value	Pre-treatment	Post-treatment	Change value
Conventional treatment group	31.34±7.34	39.02±7.05	7.68±7.21	22.65±4.96	23.32±4.97	0.67±2.21
Levosimendan treatment group	33.34±15.05	32.23±16.98	-1.11±3.17	23.81±11.46	22.60±12.02	-1.21±2.56
t	-0.665	2.056	6.210	-0.517	0.308	3.100
P	0.510	0.044	<0.001	0.606	0.759	0.003

Group	TNF-α/(pg·mL-1)			IL-10/(pg·mL-1)
	Pre-treatment	Post-treatment	Change value	Pre-treatment	Post-treatment	Change value
Conventional treatment group	49.84±12.84	52.22±13.60	2.38±4.54	551.90±122.59	527.42±107.48	-24.48±62.28
Levosimendan treatment group	54.38±23.93	51.55±23.50	-2.83±5.62	515.31±114.16	540.29±115.31	24.98±110.91
t	-0.931	0.137	4.014	-0.313	-0.454	-2.162
P	0.357	0.902	<0.001	0.756	0.651	0.035

IL: Interleukin; TNF: Tumor necrosis factor.

Statistically significant intergroup differences were observed in these pro-inflammatory cytokine changes (all P<0.05). Regarding anti-inflammatory responses, plasma IL-10 levels decreased in the conventional treatment group (24.48 pg/mL), while the levosimendan treatment group demonstrated a significant increase (24.98 pg/mL) with statistical significance compared to conventional treatment group (P<0.05, Table 3).

2.5. Treatment efficacy

Before the treatment, there were no statistically significant differences between the 2 groups in terms of NT-proBNP levels (enzyme-linked immunosorbent assay), KCCQ questionnaire scores, or GSRS questionnaire scores (all P>0.05, Table 4). After the treatment, there was a slight increase in plasma NT-proBNP levels in the conventional treatment group, while a significant decrease in NT-proBNP levels was observed in the levosimendan treatment group, with the difference between the 2 groups being statistically significant (P<0.05, Table 4). Both groups showed an increase in KCCQ questionnaire scores, with the levosimendan treatment group exhibiting higher scores than the conventional treatment group; however, the difference was not statistically significant (P>0.05, Table 4). Both groups also demonstrated a decrease in GSRS questionnaire scores, indicating improvement in gastrointestinal symptoms. The decrease in GSRS scores was more pronounced in the levosimendan treatment group compared to the conventional treatment group, although the difference was not statistically significant (P>0.05, Table 4).

Table 4.

Comparison of NT-proBNP and questionnaire scores in HFrEF patients between the 2 groups (n=31)

Group	NT-proBNP/(pg·mL-1)			KCCQ
	Pre-treatment	Post-treatment	Change value	Pre-treatment	Post-treatment	Change value
Conventional treatment group	251.67±55.53	258.79±57.28	7.35±16.60	44.30±2.10	44.66±1.93	0.36±1.35
Levosimendan treatment group	271.88±134.07	268.09±135.82	-4.73±22.89	43.58±2.19	45.44±2.01	1.86±2.07
t	-0.775	-0.351	2.378	1.321	-1.560	-1.913
P	0.441	0.727	0.022	0.191	0.124	0.072

Group	GSRS
	Pre-treatment	Post-treatment	Change value
Conventional treatment group	34.30±8.42	33.30±8.76	-1.00±2.49
Levosimendan treatment group	38.20±10.43	35.80±11.25	-2.40±1.71
t	-1.620	-0.976	1.463
P	0.110	0.332	0.161

KCCQ: Kansas City Cardiomyopathy Questionnaire; GSRS: Gastrointestinal Symptom Rating Scale.

2.6. Correlation analysis of change values for intestinal barrier factors and inflammatory cytokines with NT-proBNP change values

Spearman’s rank correlation analysis was performed between post-treatment changes in inflammatory cytokines (IL-17, IL-6, TNF-α, and IL-10) and intestinal barrier markers (zonulin and I-FABP) with NT-proBNP level alterations, without FDR correction for multiple comparisons. The analysis revealed significant positive correlations between therapeutic changes in several biomarkers and NT-proBNP modifications (Figure 3): IL-17 demonstrated a strong positive association (r=0.479, P<0.001), followed by IL-6 (r=0.468, P<0.001) and TNF-α showing the highest correlation (r=0.500, P<0.001). Although IL-10 exhibited a negative correlation coefficient with NT-proBNP changes, this relationship did not reach statistical significance. Regarding gut permeability markers, both zonulin (r=0.341, P<0.01) and I-FABP (r=0.455, P<0.001) showed significant positive correlations with NT-proBNP alterations following treatment.

Figure 3. Spearman correlation between post-treatment changes in inflammatory cytokines or intestinal barrier markers and NT-proBNP levels Changes in IL-17, IL-6, TNF-α, IL-10, zonulin, and I-FABP are correlated with corresponding NT-proBNP change by Spearman’s rank test. **P<0.01, ***P<0.001. IL: Interleukin; TNF: Tumor necrosis factor; I-FABP: Intestinal fatty acidbinding protein; NT-proBNP: N-terminal pro-brain natriuretic peptide.

3. Discussion

In this clinical study, both groups of patients receiving anti-HF therapy exhibited reductions in plasma zonulin levels. However, the decline was more pronounced in the levosimendan treatment group compared to the conventional treatment group. Additionally, the study found that intestinal inflammation markers I-FABPs and IL-17 increased in the conventional treatment group after the therapy, whereas these markers decreased in the levosimendan treatment group. These findings suggest that levosimendan supplementation partially reversed intestinal barrier dysfunction and reduced hyperpermeability. The observed improvements may be attributed to levosimendan’s positive inotropic effects, which enhance cardiac output and systemic hemodynamics in HF patients. Furthermore, levosimendan activates ATP-dependent potassium channels in vascular smooth muscle, dilating coronary arteries and terminal vascular beds, including intestinal arteries, thereby ameliorating intestinal ischemia. A clinical trial^[21] corroborates this mechanism, demonstrating that levosimendan improves microcirculation and splanchnic blood flow more effectively than dobutamine. Analysis of inflammatory mediators revealed distinct patterns between groups. The levosimendan treatment group showed reductions in pro-inflammatory cytokines IL-6, IL-17, and TNF-α, accompanied by an elevation in anti-inflammatory IL-10. Conversely, the conventional treatment group exhibited increased pro-inflammatory markers and decreased IL-10. These intergroup differences in cytokine profiles were statistically significant, indicating that levosimendan not only alleviates HF symptoms but also modulates systemic inflammation.

Under physiological conditions, the intestinal mucosa serves as a functional barrier separating luminal contents from systemic circulation^[15]. Reduced cardiac output in HF compromises intestinal perfusion, leading to villous structural damage and barrier disruption^[22]. The balance between T helper cell (Th)1 (TNF-α and IL-6), Th2 (IL-10), and Th17 (IL-17) cytokines is critical for immune homeostasis^[23-24]. Intestinal barrier injury disrupts this equilibrium, elevating Th1/Th17 associated inflammatory cytokines while suppressing Th2/Treg mediators. The observed cytokine normalization in the levosimendan treatment group aligns with network pharmacology predictions implicating IL-17 and TNF signaling pathways in HF-related intestinal barrier dysfunction. IL-17A, a potent pro-inflammatory cytokine, amplifies inflammation by sustaining TNF-α and IL-6 release while activating neutrophil-associated genes^[25-26]. Th17-derived TNF-α further exacerbates mucosal damage through mitogen-activated protein kinase (MAPK) and nuclear factor kappa-B (NF-κB) pathways, synergizing with IL-17 to impair epithelial integrity^[27].

Objective HF indicators demonstrated divergent trends: NT-proBNP levels increased slightly in the conventional group, reflecting progressive disease despite symptomatic improvement, whereas levosimendan significantly reduced NT-proBNP, suggesting acute HF stabilization. Both groups showed improved KCCQ scores and reduced GSRS scores, with greater improvements observed in the levosimendan treatment group. However, intergroup differences lacked statistical significance, potentially due to short observation periods or limited sample size affecting subjective symptom reporting.

The treatment of the current observational study was not randomized but determined based on patients’ clinical conditions and physicians’ judgment. Hospitalized patients with HFrEF frequently present with concurrent infection, manifested by elevated NEUT and WBC. The higher NEUT and WBC values in the levosimendan treatment group indicate more severe infection and HF, providing a rationale for levosimendan use in this group. Despite the differences noted, key indices of HF severity (NT-proBNP and LVEF) were balanced: Although numerically worse in the levosimendan treatment group, the disparity was nonsignificant, confirming comparable baseline cardiac impairment and preserving the validity of subsequent comparisons. Importantly, the discrepancy in inflammatory cell counts did not influence outcomes. Patients with the greatest baseline inflammatory burden achieved pronounced reductions in inflammatory levels after levosimendan therapy, underscoring its efficacy against both HFrEF and its concomitant infectious-inflammatory state.

These findings collectively indicate that levosimendan confers dual benefits in HF management by improving hemodynamics and modulating the gut-inflammatory axis, potentially altering disease progression beyond conventional therapies. Traditional positive inotropic agents provide unstable improvements in visceral perfusion and may increase myocardial oxygen demand and the risk of arrhythmias. In contrast, levosimendan improves cardiac output without significantly increasing myocardial oxygen consumption, while also dilating mesenteric vessels. This action helps relieve mesenteric hypoperfusion and venous congestion, enhances oxygen supply to the intestinal mucosa, and improves the inflammatory state.

In a word, this study showed that in hospitalized patients with acute HFrEF attack, levosimendan can improve HF and gastrointestinal symptoms while reducing the level of plasma intestinal barrier factor, which may be associated with the decrease of plasma pro-inflammatory factor and the increase of anti-inflammatory factor after the treatment, and its effects may be related to IL-17 and TNF signaling pathways. We speculated that this may be due to the opening of ATP-dependent potassium channels by levosimendan, however, the specific underlying mechanism needs to be further verified.

Contributions: WU Youxuan Research design, experimental implementation, data collection and analysis/interpreation, and paper drafting; HU Xiaolei Research design, data analysis/interpretation, paper modification, critical review of the intellectual content, and supervision; MAO Xiaoxiao, LIU Huijun, LI Shanshan Research implementation, data collection, and supportive contributions; ZENG Youjie, XU Pingsheng Supervision and supportive contributions; XIAO Haiyan Supportive contributions; LI Dai, XIA Ke Paper modification, critical review of the intellectual content, supervision, and supportive contributions. The final version of the manuscript has been read and approved by all authors.

Funding Statement

This work was supported by the Hunan Provincial Science and Technology Major Special Fund (2021SK1020), the Natural Science Foundation of Hunan Province (2023JJ30948), the Health Commission of Hunan Province (202203014687), and the International Medical Exchange Cardiovascular Multidisciplinary Integrated Thinking Research Foundation (Z-2016-23-2101-20), China.

Conflict of Interest

The authors declare that they have no conflicts of interest to disclose.

Note

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