Distinguishing myocarditis from perimyocardial syndromes in children presenting to the emergency department: a biomarker-based approach

Abstract

Introduction

Myocarditis and perimyocardial syndromes share overlapping features but differ in management. Differentiating them in children presenting with chest pain or palpitations remains difficult, particularly in non-fulminant cases. This study evaluated the diagnostic value of inflammatory biomarkers, especially the Systemic Immune-Inflammation Index (SII), in distinguishing perimyocardial syndromes from isolated myocarditis in the pediatric emergency department (PED).

Method

We retrospectively analyzed patients aged 1–18 years diagnosed with myocarditis, perimyocardial syndromes, or acute pericarditis between 2015 and 2021. Clinical characteristics, laboratory, ECG and echo findings of all patients were recorded. SII was calculated using neutrophil, platelet, and lymphocyte counts obtained within six hours of PED admission. ROC analysis assessed diagnostic performance.

Results

166 eligible subjects were enrolled (74 cases of myocarditis, 63 cases of myopericarditis, 21 cases of perimyocarditis, and 8 cases of acute pericarditis). The median age was 15 (12–17) years, and 76.5% of the patients were male. The median WBC, ANC and SII were respectively 7.44 (IQR 6.22–9.32), 3.93 (IQR 3.38-5.00), and 418 (IQR 286–679) in the myocarditis and significantly lower than the other groups (p < 0.001). In estimation of perimyocardial syndromes, AUC was 0.735 for WBC, 0.805 for ANC, 0.803 for SII (p < 0.001). The optimal cut-off values determined by the Youden Index were 8.24(x109/L) for WBC, 4.85(x109/L) for ANC, and 693 for SII, with corresponding sensitivities of 67.4%, 76.1%, and 73.9%, and specificities of 61.6%, 67.1%, and 75.3%, respectively.

Conclusions

SII and ANC are useful, accessible biomarkers for differentiating perimyocardial syndromes from myocarditis. Their integration into early diagnostic strategies may support efficient triage and decision-making in the PED.

Introduction

Myocarditis, pericarditis, and perimyocardial involvement represent inflammatory cardiac conditions that may present with clinical findings in children, yet their clinical course and management strategies may differ significantly [1]. In the pediatric emergency department (PED), children frequently present with chest pain, palpitations, or vague complaints, making the differentiation between myocardial and pericardial involvement particulary challenging. Establishing an accurate diagnosis is clinically important, as delayed recognition of myocardial involvement may increase the risk of adverse outcomes, whereas overdiagnosis may lead to unnecessary investigations and treatments in self-limiting conditions.

Although electrocardiographic and cardiac imaging modalities remain central to the diagnostic evaluation, the potential role of systemic inflammatory biomarkers in supporting differential diagnosis has not been fully clarified in pediatric populations [1, 2]. In recent years, the Systemic Immuno-Inflammatory Index (SII), derived from neutrophil, lymphocyte, and platelet counts, has gained increasing recognition as a useful marker in various cardiovascular diseases, including coronary artery disease, acute coronary syndromes, fulminant myocarditis, and heart failure. Higher SII values ​​have been associated with increased disease severity and adverse clinical outcomes [3–5].

However, despite growing evidence in adult populations, its prognostic utility in pediatric inflammatory cardiac conditions remains insufficiently defined. In pediatric myocarditis, SII has primarily been studied as a prognostic marker and has been linked to an increased risk of fulminant disease [6, 7]. The role of SII in differentiating types of inflammatory cardiac involvement in children remains unclear.

Similarly, commonly used inflammatory markers such as C-reactive protein (CRP), absolute neutrophil count (ANC), and troponin have been investigated in this context, yet their diagnostic contribution in pediatric cases is still not clearly defined [8].

Moreover, inflammatory responses in pediatric patients may differ from those observed in adults, especially in subacute or non-fulminant presentations, which may further complicate clinical decision-making [9].

In this study, we aimed to determine the diagnostic value of inflammatory biomarkers, particularly SII, in distinguishing myocarditis from perimyocardial syndromes in children presenting with chest pain or palpitations to the PED.

Materials and methods

Study design and patient selection

This single-center retrospective cohort study was performed in tertiary PED between January 1, 2015 and October 1, 2021. Pediatric patients aged 1–18 years who presented with chest pain and/or palpitations and were subsequently diagnosed with myocarditis or perimyocardial syndromes (including pericarditis and perimyocarditis) were eligible for inclusion.

Patients were excluded if they had medical conditions known to influence hematologic or inflammatory parameters, including sepsis, chronic inflammatory disorders, malignancy, or primary or secondary immunodeficiency. Patients receiving immunosuppressive or oncologic treatments, as well as those with incomplete or insufficient medical records, were also excluded from the analysis. In addition, patients with fulminant myocarditis and cardiac tamponade were excluded due to their distinct clinical severity, requirement for intensive care interventions, and their potential to confound the assessment of inflammatory biomarkers.

Data collection

Patients information was obtained from electronic medical records and hospital databases. Variables included demographic characteristics (age, gender), presenting symptoms, vital signs at admission, comorbidities, chronic medications, electrocardiographic (ECG) and echocardiographic (echo) findings, final clinical diagnosis, treatment approaches, duration of hospitalization, and in-hospital complications were also documented.

Electrocardiographic and echo findings included in the analysis were limited to those obtained at the time of initial presentation to the PED. Follow-up assessments during hospitalization were not included. Left ventricular ejection fraction (LVEF), obtained from patients’ echo reports, was calculated using the Teichholz method based on M-mode measurements at the mitral valve level.

Laboratory parameters collected at presentation included white blood cell (WBC), ANC, absolute lymphocyte counts (ALC), platelet count (PLT), erythrocyte sedimentation rate (ESR), CRP, percentage of immature granulocytes (IG), serum troponin I, creatine kinase (CK), creatine kinase-myocardial band (CK-MB), pro-Brain Natriuretic Peptide (BNP) levels.

Systemic Immune-Inflammation Index values were calculated using laboratory measurements obtained within the first six hours following admission to the PED. SII was calculated using the formula: neutrophil count x platelet count/lymphocyte count [10].

When available, cardiac magnetic resonance imaging (CMR) findings were reviewed for evidence of myocardial inflammation or fibrosis.

Diagnostic definitions

Myocarditis was diagnosed when at least two of the following findings were present: clinical manifestations suggestive of acute cardiac dysfunction, such as dyspnea, exercise intolerance, syncope, exertional chest pain, tachypnea, unexplained tachycardia, hepatomegaly, or gallop rhythm; elevated serum troponin I levels; echo evidence of ventricular dysfunction including reduced LVEF or regional wall motion abnormalities, in the absence of structural heart disease; recent history of viral or gastrointestinal prodromal illness within the preceding two weeks; or ECG abnormalities consistent with myocardial injury or arrhythmia [11, 12]. Endomyocardial biopsy remains the gold standard for definitive diagnosis. Also CMR imaging is currently considered the most valuable non-invasive modality for confirming myocardial inflammation.

Acute pericarditis was defined by the presence of at least two of the following criteria: characteristic pericarditic chest pain, pericardial friction rub, new widespread ST-segment elevation or PR-segment depression on ECG, or new or increasing pericardial effusion. Supportive evidence of pericardial inflammation on cardiac imaging modalities, including echo, CMR, or computed tomography, together with elevated inflammatory biomarkers, was also considered in establishing the diagnosis [8].

Myopericarditis was defined as fulfillment of diagnostic criteria for acute pericarditis accompied by elevated cardiac enzyme levels without evidence of newly developed left ventricular (LV) systolic dysfunction. Perimyocarditis was defined as acute pericarditis with elevated cardiac enzymes together with new focal or global LV systolic dysfunction demonstrated on echo or CMR.

All cases were retrospectively reviewed using electronic medical records. Final diagnoses were determined through the combined evaluation of clinical presentation, laboratory findings, and cardiac imaging results (ECG results, and echo assessment). Diagnostic classification was independently performed by two pediatric cardiologists and one pediatric emergency physician based on electronic medical records. Following independent assessments, discrepancies in diagnostic classification were established by consensus.

Outcomes

The primary outcome of the study was to evaluate the diagnostic performance of inflammatory biomarkers, including SII, ANC, and CRP, in differentiating myocarditis from perimyocardial syndromes.

Secondary outcomes included assessment of clinical course, treatment strategies, duration of hospitalization, and development of complications.

Statistical analysis

All statistical analyses were performed using of IBM SPSS Statistics for Windows, Version 28.0 package program. Descriptive statistics were presented as percentages for categorical variables and as mean ± standard deviation (SD) or median with interquartile range (IQR) for continuous variables, depending on data distribution.

Comparisons between two independent groups were performed using the Chi-square or Fisher’s exact test for categorical variables. Continuous variables were analyzed using the Student’s t-test or Mann–Whitney U test according to the normality of distribution. For comparisons involving more than two groups, one-way analysis of variance (ANOVA) or the Kruskal–Wallis test was applied, followed by Bonferroni-adjusted post hoc analyses when appropriate.

Receiver Operating Characteristic (ROC) curve analyses were conducted to evaluate the diagnostic performance of inflammatory markers including SII, WBC, ANC, CRP. Optimal cut-off values for each marker were determined using The Youden Index. Diagnostic performance was assessed by calculating the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

A p-value < 0.05 was considered statistically significant.

Ethical approval

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Clinical Research Ethics Committee of SBU Ankara Dr. Sami Ulus Gynecology, Child Health and Diseases Training and Research Hospital (Approval number: E-21/11–243, Date: 17 November 2021).

Results

A total of 166 patients were included in the study, comprising 74 with myocarditis, 63 with myopericarditis, 21 with perimyocarditis, and 8 with acute pericarditis (Fig. 1). The median age was 15 years (IQR 12–17), and 76.5% were male. Baseline demographic and clinical characteristics are given in Table 1. There were no statistically significant differences in age or gender distribution among the diagnostic groups.

Fig. 1.

Flow chart of the patients. *Patients with an active disease that could significantly affect blood cell count and clinical status, including sepsis, fulminant myocarditis, cardiac tamponade, chronic inflammatory condition, malignancy, and immunodeficiency, and those receiving malignancy and/or immunosuppressive therapy

Table 1.

Baseline features and managements of the patients

	Total	Myocarditis	Myopericarditis	Perimyocarditis	Pericarditis	P value
Patients, n(%)	166	74 (44.5)	63 (37.9)	21 (12.6)	8 (4.8)	-
Age, median (IQR), years	15 (12–17)	15 (10–16)	15 (13–17)	15 (14–17)	14 (9–15)	0,123
Gender, n(%)
Male	127 (76.5)	55 (74.3)	47 (74.6)	18 (85.7)	7 (87.5)	0,604
Female	39 (23.4)	19 (25.6)	16 (21.6)	3 (14.2)	1 (12.5)
Chronic disease, n(%)	22 (13.2)	10 (13.5)	10 (15.8)	1 (4.7)	1 (12.5)	0,637
Drug use, n(%)	13 (7.8)	7 (9.4)	4 (6.3)	1 (4.7)	1 (12.5)	0,806
Viral infection, n(%)	45 (27.1)	19 (25.6)	20 (31.7)	6 (28.5)	0	0,289
Length of stay in hospital, days, median (IQR)	4 (3–5)	4 (3–5)	4 (4–6)	5 (3.5-6)	7.5 (4.25-11)	0,002
PICU admission, n(%)	6 (3.6)	2 (2.7)	3 (4.7)	0	1 (12.5)	0,214
Length of stay in PICU, > 48 h, n(%)	3(1.8)	1(1.3)	1 (1.58)	0	1 (12.5)	0,132
Management, n(%)
NSAI	80 (48.1)	10 (13.5)	46 (73)	18 (85.7)	6 (75)	< 0,001
ACEi/ARB	8 (4.8)	5 (6.7)	3 (4.7)	0	0	0,549
Diuretic	1 (0.6)	0	1 (1.58)	0	0	-
Intravenous immunglobulin	2 (1.2)	0	2 (3.1)	0	0	-
Antiarrhythmic	2 (1.2)	1 (1.3)	1 (1.58)	0	0	0,931
Pericardiocentesis	2 (1.2)	0	0	0	2 (25)	-
Complication*, n(%)	31 (18.6)	13 (17.5)	10 (15.8)	5 (23.8)	3 (37.5)	0,455

PICU, pediatric intensive care unit; NSAI, nonsteroidal anti-inflammatory; ACEi, angiotensin converting enzyme inhibitors; ARB, angiotensin receptor blockers

*Valve (mitral, tricuspid, pulmonary, aortic) regurgitation, hypertension, ventricular extra systole, chest pain with exertion, transient left ventricular hypertrophy

Value in bold font indicates statistically significant

Biomarkers analysis

The comparison of the inflammatory biomarkers across diagnostic groups is presented in Table 2. The median values for WBC, ANC and SII were respectively 7.44 × 10⁹/L (IQR 6.22–9.32), 3.93 × 10⁹/L (IQR 3.38-5.00), and 418 (IQR 286–679) in the myocarditis group, significantly lower than in other groups (p < 0.001). The median ALC was 1.70 × 10⁹/L (IQR 1.40–2.22) in the myopericarditis and significantly lower than the other groups (p = 0.006) The median CRP were respectively 69.5 mg/L (IQR 25.2-120.7) and 104.5 mg/L (IQR 16.6-176.7) in the perimyocarditis and pericarditis, and significantly higher than the other groups (p < 0.001).

Table 2.

Comparison of patients’ biomarkers by groups

Laboratory, median (IQR)	Total	Myocarditis	Myopericarditis	Perimyocarditis	Pericarditis	P value
WBC, x109/L	8.53 (6.80–11.00)	7.44 (6.22–9.32)	9.20 (7.49–11.3)	10.64 (8.49–12.87)	11.0 (7.62–14.74)	< 0,001
ANC, x109/L	5.19 (3.89–7.89)	3.93 (3.38-5.00)	6.30 (4.55–8.90)	7.90 (5.81–8.86)	7.85 (4.68–11.12)	< 0,001
ALC, x109/L	2.00 (1.59–2.55)	2.20 (1.66–2.96)	1.70 (1.40–2.22)	2.00 (1.28–2.65)	2.10 (1.55–2.38)	0,006
PLT, x109/L	258 (213–307)	256 (201–300)	262 (222–312)	258 (212–338)	267 (234–359)	0,452
SII, x109/L	699.00 (405.00-1144.50)	418 (286–679)	952 (612–1607)	999 (802–1558)	1173 (545–2148)	< 0,001
CRP, mg/L	27.0 (8.15-74.0)	16.0 (3.2–44.0)	32 (9.5–80)	69.5 (25.2-120.7)	104.5 (16.6-176.7)	< 0,001
ESR, mm/hour	20 (8–43)	17 (8-37.7)	19 (5–40)	57 (14–70)	43 (4.7–56.5)	0,274
IG %	0.3 (0.2–0.4)	0.2 (0.1–0.32)	0.3 (0.2–0.4)	0.3 (0.22–0.47)	0.1 (0.01-)	0,929
Troponin, ng/mL	4.58 (0.3–13.2)	2.09 (0.22–9.95)	9.7 (3.0–20.0)	7.25 (0.76–15.2)	0.00 (-0.02)	0,026
CK-MB	31 (18–57)	28 (18–45)	38 (24-66.5)	33 (18–58)	13 (11–25)	0,233
Creatine kinase	240 (144–614)	223 (138–448)	308 (175–814)	384 (152–656)	89 (50-)	0,517
pro-BNP, pg/ml	1399 (281–3020)	1399 (1247-)	2273 (296–3760)	213 (-)	-	0,535

WBC, white blood cell count; ANC, absolute neutrophil count; ALC, absolute lymphocyte count; PLT, platelet count; SII, systemic immune-inflammatory index; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; IG, immature granulocytes; BNP, brain natriuretic peptide

Value in bold font indicates statistically significant

ROC analysis

In estimation of pericardial inflammatory syndromes, AUC was 0.735 for WBC [95% confidence interval (CI): 0.646–0.824, p < 0.001], 0.805 for ANC (95% CI: 0.725–0.884), p < 0.001), 0.803 for SII (95% CI: 0.722–0.884, p < 0.001), 0.680 (95% CI: 0.588–0.773, p = 0.001) for CRP (Table 3). The ROC curves of the markers for the pericardial inflammatory syndromes are shown in Fig. 2. The optimum cut-off values for predicting pericardial involvement were 8240/µL, 4850/µL, 693 and 24 mg/L for WBC, ANC, SII and CRP, respectively.

Table 3.

Efficiency of inflammation markers in predicting inflammatory myopericardial syndromes

	Cut-off	AUC	OR (95% CI)	Sensitivity	Specificity	PPV	NPV
WBC, x109/L	8.24	0.735	3.30 (1.74–6.31)	67.4	61.6	68.9	60.0
ANC, x109/L	4.85	0.805	6.49 (3.27–12.87)	76.1	67.1	74.5	69.0
SII, x109/L	693.0	0.803	8.65 (4.26–17.55)	73.9	75.3	79.1	69.6
CRP, mg/L	24.0	0.680	3.04 (1.45–6.36)	65.8	61.2	73.2	52.6

WBC, white blood cell count; ANC, absolute neutrophil count; SII, systemic immune-inflammatory index; ESR, erythrocyte sedimentation rate; IG, immature granulocytes; AUC, area under the curve; OR, odds ratio; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value

Fig. 2.

ROC curves of inflammation markers to predict perimyocardial syndromes. WBC, white blood cell count; ANC, absolute neutrophil count; SII, systemic immune-inflammatory index; CRP, C-reactive protein

ECG, echo, telecardiography and CMR findings

The most common ECG rhythms; sinus rhythm [(n = 50(30%)] and ST-segment elevation [(n = 65 (39.1%)]. Others include sinus tachycardia [(n = 19(11.4%)], ST depression [(n = 6(3.6%)], negative T waves [(n = 11(6.6%)], and other ECG abnormalities (such as right bundle branch block, ventricular extrasystole, early repolarization, and first-degree atrioventricular block) [(n = 15(9%)]. The mean Qtc interval was 389.6 ms (± SD 22.6) in the overall cohort, 392.0 (± SD 22.8) in the myocarditis, 386.4 (± SD 20.6) in the myopericarditis, 394.4 (± SD 22.7) in the perimyocarditis, and 378.7 (± SD 32.2) in the pericarditis (p = 0.164).

The median LVEF was 70% (IQR 55.0–70.0) in the overall cohort, 55% (IQR 45.0–65.0) in the myocarditis, 69.0% (65–72) in the myopericarditis, 67.0% (63–71) in the perimyocarditis, and 69.5% (61–70) in the pericarditis (p = 0.562). Valve regurgitation and velocities of all patients are given in Table 4. Mitral regurgitation was in 48 (28.9%) patients, tricuspid regurgitation in 158 (95%) patients, pulmonary regurgitation in 12 (7.2%) patients, and aortic regurgitation in 10 (6%) patients. There were no significant intergroup differences in valve regurgitation or velocity measurement.

Table 4.

Comparison of ECG, echo and telecardiography findings

	Total	Myocarditis	Myopericarditis	Perimyocarditis	Pericarditis	P value
Patients, n(%)	166	74	63	21	8
ECG, n(%)						0,034
Sinus rhythm	50 (30)	25 (33.7)	16 (25.3)	7 (33.3)	2 (25)
Sinus tachycardia	19 (11.4)	13 (17.5)	3 (4.7)	3 (14.2)	0
ST elevation	65 (39.1)	21 (28.3)	31 (49.2)	9 (42.8)	4 (50)
ST depression	6 (3.6)	1 (1.3)	4 (6.3)	1 (4.7)	0
T negativity	11 (6.6)	3 (4)	6 (11.1)	0	2 (25)
Arrhythmia*	15 (9)	11 (14.8)	3 (4.7)	1 (4.7)	0
Echo
Mitral regurgitation, n(%)						0,010
Minimal	45 (27.1)	22 (29.7)	15 (23.8)	7 (33.3)	1 (12.5)
First-degree	2 (1.2)	1 (1.3)	1 (1.5)	0	0
Second-degree	0	0	0	0	0
Third-degree	1 (0.6)	0	0	0	1 (12.5)
Mitral annular velocity, m/sec, median (IQR)	3.1 (2.55–3.6)	3.3 (2.65–3.6)	3.1 (2.4-4.0)	2.95 (2.67–3.15)	4.8	0,370
Tricuspid regurgitation, n(%)						0,966
Minimal	151 (90.9)	69 (93.2)	56 (88.8)	19 (90.4)	7 (87.5)
First-degree	6 (3.6)	2 (2.7)	3 (4.7)	1 (4.7)	0
Second-degree	1 (0.6)	1 (1.3)	0	0	0
Tricuspid annular velocity, m/sec, median (IQR)	2.0	2.0	2.0 (2.0-2.1)	2.0 (2.0-2.15)	2.0 (2.0-2.1)	0,618
Pulmonary regurgitation, n(%)
Minimal	12 (7.2)	6 (8.1)	5 (7.9)	1 (4.7)	0	0,814
Pulmonary annular velocity, m/sec, median (IQR)	1.75 (1.42–1.9)	1.55 (1.2–1.9)	1.9 (1.5–1.95)	2.0	-	0,169
Aortic regurgitation, n(%)						0,454
Minimal	9 (5.4)	3 (4)	6 (9.5)	0	0
First-degree	1 (0.6)	0	1 (1.5)	0	0
Aortic annular velocity, m/sec, median (IQR)	3.5 (2.2-)	3.5	3.0 (2.2-)	-	-	0,990
Pathological findings on chest radiograph †	15 (9.0)	1 (1.3)	5 (7.9)	4 (19)	5 (62.5)	< 0.001

ECG, electrocardiography; Echo, echocardiography

*Right bundle branch block, ventricular extrasystole, early repolarization, first degree atrioventricular block

† Cardiomegaly, findings consistent with effusion

Value in bold font indicates statistically significant

Telecardiography showed pathological findings (primarily cardiomegaly and pericardial effusion) in 15 (9%) patients [(62.5% of patients with pericarditis, 1.3% of patients with myocarditis, 7.9% of patients with myopericarditis, 19% of patients with perimyocarditis (p < 0.001)].

Cardiac magnetic resonance imaging was performed in 9 patients (5 with myocarditis, 4 with myopericarditis).

Management and prognosis

Treatment and outcomes are detailed in Table 1. The median lenght of stay in hospital were 7.5 (4.25-11) days and 5 (3.5-6) days for pericarditis and perimyocarditis, respectively, which was statistically longer than the other groups. In a total cohort, 6 (3.6%) patients were admitted to pediatric intensive care unit. Ibuprofen was given as anti-inflammatory therapy in 85.7% of patients with acute perimyocarditis, 75% of those with pericarditis, and 73% of patients with myopericarditis. In patients with myocarditis and myopericarditis, an angiotensin-converting enzyme inhibitor was given in 6.7% to 4.7% of patients. Pericardiocentesis was performed in two (25%) patients with pericarditis. All patients were temporarily excluded from effort-requiring activities and absolute rest was recommended. The clinical course of the patient population was hemodynamically stable, and they did not require inotropic drugs. Of the 6 patients admitted to the pediatric intensive care unit, 2 were patients who underwent pericardiocentesis; the others were admitted primarily for preventive purposes, monitoring, and supportive care, rather than for severe hemodynamic instability. None of the patients in the study group required mechanical ventilation support, extracorporeal membrane oxygenation, or heart transplantation.

Discussion

This single-center study highlights the diagnostic potential of inflammatory biomarkers—particularly the Systemic Immune-Inflammation Index (SII)—in differentiating myocarditis from perimyocardial inflammatory syndromes among children presenting with chest pain and palpitations. Our findings suggest that systemic inflammatory indices may provide valuable supportive information in the early diagnostic evaluation of these conditions, especially in cases where clinical and imaging findings are inconclusive. Although ECG and cardiac imaging remain essential diagnostic tools, the role of easily accessible laboratory biomarkers in pediatric populations has not been sufficiently clarified.

In our cohort, SII, ANC, and CRP demonstrated superior diagnostic performance compared with conventional markers such as WBC and ESR in identifying pericardial involvement. SII showed a relatively high diagnostic accuracy, with an AUC of 0.803, sensitivity of 73.9% and a PPV of 79.1%, indicating a strong ability to differentiate inflammatory cardiac conditions. Similarly, ANC demostrated comparable diagnostic performance, whereas WBC and ESR appeared to have more limited discriminatory value in this clinical context.

Traditional inflammatory markers, including WBC, ESR, and CRP, have long been considered supportive but nonspecific indicators in pediatric inflammatory cardiac disorders, with reported sensitivities varying widely across studies [2, 7, 12, 13]. Previous investigations, such as the study by Imazio et al., reported higher WBC and CRP levels in isolated pericarditis compared with myopericarditis [14]. Consistent with these findings, our results demonstrated lower WBC values and only moderate diagnostic performance of CRP in isolated myocarditis. When interpreted individually, these conventional parameters may fail to adequately distinguish overlapping inflammatory cardiac conditions, potentially leading to diagnostic uncertainty.

To our knowledge, this study is among the first to evaluate SII primarily as a diagnostic tool rather than a prognostic marker in pediatric myocardial inflammatiory disorders. Recent pediatric studies have associated markedly elevated SII values, with cut-off levels around 1050, with fulminant myocarditis and adverse clinical outcomes [3, 6]. In contrast, our findings suggest that lower SII threshold may be clinically useful for distinguishing pericardial inflammatory involvement from isolated myocarditis. In our cohort, an SII cut-off value above 693 demostrated good discriminatory performance, indicating that SII may reflect not only disease severity but also the extent of combined myocardial and pericardial inflammation. This distinction may have practical implications in emergency department settings, where early diagnostic clarification is essential.

The ANC mirrored the SII (AUC 0.805), reflecting its significant weight in the SII formula. Since both parameters are derived from routine complete blood count measurements, they can be obtained rapidly without additional cost or invasive procedures, making them potentially valuable tools during early clinical assessment in PED.

The significantly lower levels of WBC, ANC, and SII in the myocarditis group compared to perimyocardial inflammatory syndromes may stem from fundamental differences in the underlying inflammatory mechanisms. In pediatric patients, myocarditis is often characterized by localized myocardial inflammation of viral or immune-mediated origin, which may not be reflected in peripheral blood inflammatory markers. In contrast, pericarditis and perimyocardial involvement are typically associated with a more pronounced systemic inflammatory response, resulting in higher circulating inflammatory indices such as WBC, ANC, and SII [1]. Taken together, these findings suggest that SII, a composite marker reflecting systemic inflammation, may better reflect the inflammatory burden associated with pericardial involvement rather than isolated myocardial inflammation. This could explain its relatively low values ​​in myocarditis and its stronger discriminative performance in identifying perimyocardial inflammatory syndromes in a PED setting.

Cardiac-specific biomarkers, including troponin, CK-MB, and CK levels, remain essential indicators of myocardial injury. However, their ability to differentiate between types of inflammatory cardiac involvement appears limited [15–18]. In our cohort, troponin, CK-MB and CK levels were comparable between diagnostic groups, consistent with previous studies involving mixed myopericarditis populations [14, 17, 18]. Therefore, while an elevated troponin levels may prompt further cardiac evaluation and rhytm monitoring, these markers alone are insufficient for distinguishing myocarditis from pericardial inflammatory syndromes. When interpreted alongside inflammatory indices such as SII or ANC, however, they may contribute to more accurate early risk stratification and clinical decision-making.

Study limitations

This study has several limitations that warrant consideration. First, its retrospective design may have introduced selection and information bias inherent to medical record-based analyses. Diagnostic confirmation with advanced modalities such as CMR or endomyocardial biopsy was not available for all patients, and biopsy was performed in only a limited number of cases. Given the overlapping clinical features of myocarditis, myopericarditis, and pericarditis, this may have introduced a potential risk of misclassification. An important limitation of this study is the exclusion of patients with fulminant myocarditis and cardiac tamponade. These conditions were deliberately excluded due to their distinct clinical severity and the potential to confound the evaluation of inflammatory biomarkers. As a result, the study population represents a relatively clinically stable cohort, which may limit the generalizability of the findings to more severe cases. Previous multicenter studies focusing on fulminant myocarditis have reported substantially higher SII thresholds, suggesting that inflammatory responses may vary across different disease severities. Third, patients with systemic conditions known to significantly affect inflammatory biomarkers—such as sepsis, malignancy, or chronic inflammatory diseases—were excluded to minimize confounding effects. Fourth, ProBNP levels were available in only a limited number of patients (n = 8), which limits the generalizability of the findings. Furthermore, treatments such as IVIG and diuretics were administered in a small, select number of cases based on clinical discretion, further limiting the ability to draw definitive conclusions about treatment effects. Consequently, the incidence of severe complications or intensive care unit admissions may have been underestimated in our cohort. Finally, this was a single-center study with a relatively limited sample size, which may restrict the generalizability of the results. Prospective, multicenter studies with larger patients populations and broader inclusion criteria are needed to confirm and expand upon these findings.

Conclusions

In pediatric emergency department setting, SII and ANC appear to be rapid, accessible, and cost-effective inflammatory biomarkers that may assist in distinguishing pericardial inflammatory syndromes from isolated myocarditis. Incorporating these parameters into early diagnostic evaluation may support clinical decision-making, potentially reducing reliance on advanced imaging modalities in selected patients. Further large prospective studies will confirm optimal cut-offs and clarify whether SII-guided pathways translate into faster diagnosis and better resource utilization.

Abbreviations

PED

Pediatric emergency department

Echo

Echocardiographic

ECG

Electrocardiographic

WBC

White blood cell

ANC

Absolute neutrophil count

ALC

Absolute lymphocyte counts

PLT

Platelet counts

ESR

Erythrocyte sedimentation rate

CRP

C-reactive protein

IG%

Percentage of immature granulocytes

CK

Creatine kinase

CK-MB

Creatine kinase myocardial band

BNP

Pro-Brain Natriuretic Peptide

SII

Systemic immune-inflammation index

CT

Computed tomography

CMR

Cardiac magnetic resonance

LVEF

Left ventricular ejection fraction

Author contributions

MD Yaradılmış, MD Güngör and Prof Tuygun, Karacan conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised the manuscript. Drs Öztürk, Göktuğ, Güneylioğlu, Akkaya and Kaya designed the data collection instruments, collected data, reviewed, and revised the manuscript. Drs Yaradılmış, Bodur, Aydin and Prof Örün carried out the initial analyses, reviewed and revised the manuscript.All authors approved the final version of manuscript and accept all the responsibilities.

Funding

None.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Declarations

Ethical approval

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Clinical Research Ethics Committee of SBU Ankara Dr. Sami Ulus Gynecology, Child Health and Diseases Training and Research Hospital (Approval number: E-21/11–243, Date: 17 November 2021). Due to the retrospective nature of the study and the use of anonymized patient data, the requirement for informed consent was waived by the ethics committee.

Consent to participate

None.

Consent for publication

None.

Financial/other relationships

The authors have no conflicts of interest to disclose. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Competing interests

The authors declare no competing interests.