Abstract
Background
Myocarditis is an inflammatory disease of the myocardium that can result from various etiologies, most commonly viral or bacterial infections and autoimmune processes. This study aimed to evaluate the predictive value of the Pan-Immune-Inflammatory Value (PIV) index for the duration of hospitalization.
Methods
Laboratory parameters, comorbidities, and treatment data of patients diagnosed with myocarditis were retrospectively analyzed. Patients were divided into two groups: those discharged within 48 hours and those hospitalized for more than 48 hours. The relationship between the PIV index and the duration of hospital stay was evaluated.
Results
Patients with a hospital stay longer than 2 days were significantly younger (p < 0.001). Red cell distribution width, C-reactive protein, and troponin levels were significantly higher in patients with prolonged hospitalization (p < 0.001, p < 0.001, p = 0.013, respectively). PIV values were significantly higher in patients with pericardial effusion and in those receiving intravenous steroid therapy (p < 0.001).
Conclusions
Although PIV alone was not a statistically significant predictor of hospital stay duration, it was associated with markers of systemic inflammation and disease severity. PIV may serve as a supportive biomarker in the clinical assessment of myocarditis patients.
Keywords: Inflammation, Length of hospital stay, Myocarditis, Pan-Immune-Inflammatory Value
Abbreviations
ACE, Angiotensin-converting enzyme
ANCOVA, Analysis of covariance
AUC, Area under the curve
BNP, B-type natriuretic peptide
CRP, C-reactive protein
DM, Diabetes mellitus
EF, Ejection fraction
HL, Hyperlipidemia
HRR, Hemoglobin/red blood cell distribution width ratio
HT, Hypertension
IV, Intravenous
IVIG, Intravenous immunoglobulin
MRI, Magnetic resonance imaging
PIV, Pan-Immune-Inflammatory Value
RAR, Red blood cell distribution width/albumin ratio
RDW, Red cell distribution width
ROC, Receiver operating characteristic
WBC, White blood cell
INTRODUCTION
Myocarditis is an inflammatory disease of the myocardium that can arise from a variety of etiologies, most commonly viral or bacterial infections and autoimmune processes.1,2 Its prevalence varies depending on the population studied and the diagnostic criteria used, with an estimated incidence of 10 to 22 cases per 100,000 individuals annually.3,4 Patients may present with a wide spectrum of clinical manifestations, including chest pain mimicking myocardial infarction, fatigue, dyspnea, and palpitations.5-7 Diagnostic evaluation typically includes electrocardiography, echocardiography, cardiac magnetic resonance imaging (MRI), and, in selected cases, endomyocardial biopsy.8-10
The duration of hospitalization in patients with myocarditis varies considerably and depends on several clinical factors, including disease severity, therapeutic response, and the presence of complications.9,11 Patients with heart failure, arrhythmias, or hemodynamic instability often require prolonged hospitalization, whereas those with mild symptoms may be managed with shorter observation periods or outpatient follow-up.12
The prognosis of myocarditis is closely related to clinical presentation and response to treatment.13 While many patients recover fully, a subset may develop chronic cardiac dysfunction or life-threatening complications such as severe heart failure or malignant arrhythmias.14 Therefore, early identification of patients at risk for a more severe disease course is essential for optimal management.
The Pan-Immune-Inflammatory Value (PIV) is a novel biomarker that reflects the overall inflammatory and immune status of the patient by incorporating neutrophil, platelet, monocyte, and lymphocyte counts.15,16 Elevated PIV levels have been associated with increased inflammatory burden and worse clinical outcomes in various cardiovascular conditions. Given that inflammation plays a central role in the pathophysiology of myocarditis, PIV may provide valuable insights into disease severity and clinical progression.
Although several inflammatory indices, such as hemoglobin/red blood cell distribution width ratio (HRR), red blood cell distribution width/albumin ratio (RAR), and HALP, have been investigated in cardiac inflammatory conditions, data regarding the role of PIV in myocarditis are lacking. To the best of our knowledge, no previous study has specifically evaluated the relationship between PIV and the duration of hospital stay in patients with myocarditis.
Therefore, this study aimed to investigate the potential predictive value of the PIV index in determining the duration of hospitalization in patients with acute myocarditis.
METHODS
Compliance with ethical standards
The study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Ethics Committee of Necmettin Erbakan University (approval number: 2024/4933, date: 03/05/2024). Written informed consent was obtained from all participants. No artificial intelligence-assisted technologies were used in the conduct of this study.
Study design and population
This retrospective observational study included 260 patients diagnosed with acute myocarditis who were admitted to our hospital between January 2014 and January 2024.
Patients were divided into two groups according to the duration of hospitalization: those discharged within 48 hours and those hospitalized for more than 48 hours.
Patient evaluation and data collection
The diagnosis of myocarditis was based on clinical findings, cardiac biomarkers, and imaging modalities. Coronary angiography or coronary computed tomography angiography was performed when necessary to exclude coronary artery disease.
Patients presenting with persistent chest pain, hypotension, pericardial effusion, progressive reduction in ejection fraction (EF), or lack of response to medical therapy were considered to have severe disease.
Demographic characteristics, cardiovascular risk factors, comorbidities, laboratory parameters, and treatment data were collected from electronic medical records.
Calculation of PIV
The PIV was calculated using the following formula:
PIV = (Neutrophil × Platelet × Monocyte) / Lymphocyte
All hematological parameters were obtained from blood samples collected at the time of hospital admission.
Inclusion and exclusion criteria
Patients aged ≥ 18 years with a confirmed diagnosis of acute myocarditis were included in the study.
Exclusion criteria
• History of myocardial infarction
• Chronic kidney disease
• Chronic liver disease
• Malignancy
• Incomplete medical records
• Use of medications affecting glucose or triglyceride levels prior to diagnosis
Patients with COVID-19 infection were not included.
Follow-up and outcome measures
Laboratory parameters including lipid profile, troponin, C-reactive protein (CRP), and glycated hemoglobin were recorded during hospitalization. Follow-up data regarding major cardiac events at 1 and 6 months were obtained through the national health database and telephone interviews.
The primary outcome of the study was the duration of hospital stay.
Statistical analysis
Statistical analyses were performed using Statistical Package for the Social Sciences version 27.0 (IBM Corp., Chicago, IL, USA).
The normality of data distribution was assessed using the Kolmogorov-Smirnov test, histogram analysis, and Q-Q plots. Continuous variables were expressed as mean ± standard deviation or median (interquartile range), as appropriate.
Comparisons between groups were performed using the independent samples t-test or Mann-Whitney U test. Correlations between variables were evaluated using Spearman correlation analysis.
A p value < 0.05 was considered statistically significant.
A priori power analysis was performed assuming an effect size of 0.5, α = 0.05, and 90% power, indicating a minimum required sample size of 128 patients. With a total of 260 patients included, the post hoc power of the study was calculated as 98%.
RESULTS
Baseline characteristics
Table 1 summarizes the distribution of quantitative parameters in patients with myocarditis. The median age was 43.5 years (range: 18-74). The median white blood cell (WBC) count was 10.04 × 103/μL (8.01-23.82), and the median neutrophil count was 7.32 ×103/μL (3.62-19.93). Troponin levels ranged from 48 to 50,000 ng/L, with a median value of 456 ng/L. The median CRP level was 32 mg/L (10-348), and the median D-dimer level was 566 ng/mL (365-987).
Table 1. Summary of the general distribution of quantitative parameters in myocarditis patients.
| Parameters | Minimum | Maximum | Distribution* |
| Age (years) | 18 | 74 | 43.5 (18-74) |
| Hemoglobin (g/dL) | 10.5 | 17.7 | 14.4 (10.5-17.7) |
| White blood cell (×103/μL) | 8.01 | 23.82 | 10.04 (8.01-23.82) |
| Neutrophil (×103/μL) | 3.62 | 19.93 | 7.32 (3.62-19.93) |
| Monocyte (%) | 0.04 | 1.82 | 0.66 (0.04-1.82) |
| Lymphocyte (×103/μL) | 0.40 | 4.78 | 2.07 (0.4-4.78) |
| Platelet (×103/μL) | 146 | 366 | 244.34 ± 50.02 |
| RDW (%) | 11.2 | 17.7 | 13.45 ± 1.06 |
| Albumin (g/L) | 32.0 | 50.6 | 42.8 ± 3.05 |
| ASO (IU/mL) | 111 | 387 | 205.87 ± 69.29 |
| EF (%) | 30 | 65 | 60 (30-65) |
| Troponin (ng/L) | 48 | 50000 | 456 (48-50000) |
| CRP (mg/L) | 10 | 348 | 32 (10-348) |
| D-dimer (ng/mL) | 365 | 987 | 566 (365-987) |
| Ferritin (ng/mL) | 19 | 165 | 73 (19-165) |
| Fibrinogen (ng/dL) | 2.56 | 4.16 | 3.41 (2.56-4.16) |
| LDL (mg/dL) | 53 | 198 | 134 (53-198) |
| HDL (mg/dL) | 23 | 129 | 43 (23-129) |
| TRG (mg/dL) | 72 | 307 | 126 (72-307) |
| Glucose (mg/dL) | 77 | 167 | 97 (77-167) |
| Uric acid (mg/dL) | 3.6 | 6.2 | 4.4 (3.6-6.2) |
| PIV | 7.96 | 4346.50 | 608.11 (7.96-4346.5) |
| ICU follow-up time (day) | 1 | 10 | 1 (1-10) |
| Total hospitalization time (day) | 1 | 14 | 3 (1-14) |
* Parameters are expressed as IQR [median, min and max] or mean ± SD.
ASO, antistreptolysin O; CRP, C reactive protein; EF, ejection fraction; HDL, high density lipoprotein; ICU, intensive care unit; IQR, interquartile range; LDL, low density lipoprotein; PIV, Pan-Immune-Inflammatory Value; RDW, red cell distribution width; SD, standard deviation; TRG, triglyceride; WBC, white blood cell.
PIV according to clinical characteristics
PIV values were significantly higher in patients with pericardial effusion, those receiving inotropic support, intravenous immunoglobulin (IVIG), and intravenous (IV) steroid therapy (all p < 0.001) (Table 2).
Table 2. Comparison of PIV values according to the presence of special conditions.
| Parameters | PIV | p |
| Median (min-max) | ||
| Pericardial effusion | < 0.001 | |
| No (n = 184) | 526.09 (7.96-4346.5) | |
| Yes (n = 74) | 900.89 (141.73-4146.6) | |
| Beta blocker use | < 0.001 | |
| No (n = 139) | 690.03 (141.73-4146.6) | |
| Yes (n = 121) | 524.68 (7.96-4346.5) | |
| ACE inhibitor use | < 0.001 | |
| No (n = 139) | 690.03 (141.73-4146.6) | |
| Yes (n = 121) | 524.68 (7.96-4346.5) | |
| Inotrope support | 0.003* | |
| No (n = 251) | 589.1 (7.96-4346.5) | |
| Yes (n = 9) | 1244.19 (548.4-1894.32) | |
| IV steroid intake | < 0.001 | |
| No (n = 248) | 583.19 (7.96-4346.5) | |
| Yes (n = 12) | 1280.43 (548.4-2167.22) | |
| IVIG | 0.036* | |
| No (n = 255) | 604.76 (7.96-4346.5) | |
| Yes (n = 5) | 1244.19 (548.4-1894.32) | |
| HT | < 0.001 | |
| No (n = 139) | 675.14 (141.73-4346.5) | |
| Yes (n = 121) | 525.4 (7.96-2489.91) | |
| HL | 0.042 | |
| No (n = 188) | 617.68 (119.45-4346.5) | |
| Yes (n = 72) | 545.45 (7.96-1873.26) | |
| DM | 0.004 | |
| No (n = 208) | 623.70 (119.45-4346.5) | |
| Yes (n = 52) | 515.38 (7.96-1455.64) | |
| Smoking | 0.009 | |
| No (n = 105) | 675.14 (57.97-4146.6) | |
| Yes (n = 155) | 554.99 (7.96-4346.5) | |
| Family history | 0.550 | |
| No (n = 184) | 606.27 (57.97-4146.6) | |
| Yes (n = 76) | 615.83 (7.96-4346.5) | |
| Obesity | 0.031 | |
| No (n = 102) | 642.35 (141.73-2760.25) | |
| Yes (n = 158) | 583.19 (7.96-4346.5) | |
| Flu infection within 4 weeks | 0.154 | |
| No (n = 97) | 641.47 (141.73-1894.32) | |
| Yes (n = 163) | 574.64 (7.96-4346.5) | |
| Tonsillitis | 0.012 | |
| No (n = 162) | 567.73 (7.96-4346.5) | |
| Yes (n = 98) | 690.94 (105.32-1923.29) | |
| Gastroenteritis in 4 weeks | 0.576 | |
| No (n = 208) | 583.19 (7.96-4346.5) | |
| Yes (n = 52) | 655.72 (161.37-2167.22) | |
| Coronary CT angiography | 0.826 | |
| No (n = 197) | 591.35 (7.96-4346.5) | |
| Yes (n = 63) | 615.01 (141.73-1894.32) | |
| Coronary angiography | 0.640 | |
| No (n = 61) | 643.22 (141.73-1894.32) | |
| Yes (n = 199) | 589.09 (7.96-4346.50) |
ACE, angiotensin converting enzyme; CT, computed tomography; DM, diabetes mellitus; HL, hyperlipidemia; HT, hypertension; IV, intravenous; IVIG, intravenous immunoglobulin; PIV, Pan-Immune-Inflammatory Value.
Note: Interpret results for IVIG (n = 5) and inotrope support (n = 9) with caution due to small sample sizes.
Conversely, PIV values were significantly lower in patients using beta-blockers and angiotensin-converting enzyme (ACE) inhibitors, as well as in those with hypertension (HT), hyperlipidemia (HL), and diabetes mellitus (DM) (all p < 0.001) (Table 2).
Comparison according to hospitalization duration
Patients hospitalized for more than 2 days were significantly younger compared to those discharged within 48 hours (p < 0.001) (Table 3).
Table 3. Comparison of quantitative parameters with total hospitalization time groups.
| Parameters | Total hospitalization time | p | |
| 1-2 day (n = 127, 48.8%) | > 2 day (n = 133, 51.2%) | ||
| Distribution* | |||
| Age (years) | 47 (19-68) | 39 (18-74) | < 0.001 |
| Hemoglobin (g/dL) | 14.8 (10.5-17.7) | 14.3 (10.5-17.7) | 0.088 |
| WBC (×103/μL) | 9.66 (8.01-23.82) | 11.4 (8.23-22.71) | 0.005 |
| Neutrophil (×103/μL) | 6.51 (3.62-19.93) | 8.27 (3.67-18.47) | 0.008 |
| Monocyte (%) | 0.65 (0.04-1.37) | 0.67 (0.2-1.82) | 0.211 |
| Lymphocyte (×103/μL) | 2.22 (0.82-4.78) | 2.05 (0.4-3.95) | 0.336 |
| Platelet (×103/μL) | 248 ± 52 | 241 ± 48 | 0.304 |
| RDW (%) | 13.2 ± 1.1 | 13.7 ± 1 | < 0.001 |
| Albumin (g/L) | 43 ± 3.1 | 42.6 ± 3 | 0.202 |
| ASO (IU/mL) | 194 ± 67 | 217 ± 70 | 0.009 |
| EF (%) | 60 (45-65) | 60 (30-65) | < 0.001 |
| Troponin (ng/L) | 218 (48-18511) | 3609 (51-50000) | 0.013 |
| CRP (mg/L) | 23 (10-203) | 39 (10-348) | < 0.001 |
| D-dimer (ng/mL) | 510 (365-722) | 590 (367-987) | 0.793 |
| Ferritin (ng/mL) | 67 (19-165) | 77 (22-165) | < 0.001 |
| Fibrinogen (ng/dL) | 3.13 (2.56-3.87) | 3.61 (2.88-4.16) | 0.252 |
| LDL (mg/dL) | 132 (53-191) | 134 (71-198) | < 0.001 |
| HDL (mg/dL) | 43 (27-129) | 43 (23-57) | < 0.001 |
| TRG (mg/dL) | 118 (72-290) | 128 (77-307) | 0.720 |
| Glucose (mg/dL) | 93 (78-167) | 100 (77-145) | 0.041 |
| Uric acid (mg/dL) | 4.3 (3.6-6.1) | 4.7 (3.6-6.2) | 0.163 |
| PIV | 524.68 (7.96-4146.6) | 726.34 (105.32-4346.5) | 0.640 |
* Parameters are expressed as IQR [median, min and max] or mean ± SD.
ASO, antistreptolysin O; CRP, C reactive protein; EF, ejection fraction; HDL, high density lipoprotein; IQR, interquartile range; LDL, low density lipoprotein; PIV, Pan-Immune-Inflammatory Value; RDW, red cell distribution width; SD, standard deviation; TRG, triglyceride; WBC, white blood cell.
Red cell distribution width (RDW), CRP, and troponin levels were significantly higher in patients with prolonged hospitalization (p < 0.001, p < 0.001, and p = 0.013, respectively).
Although PIV values were numerically higher in patients with longer hospital stays, the difference did not reach statistical significance (p = 0.64) (Table 3).
Correlation Analysis
Significant negative correlations were observed between age and CRP, antistreptolysin O, and ferritin levels (Table 4).
Table 4. Examining the correlations of quantitative parameters with age, ICU stay, total hospital stay, PIV.
| Age | ICU time | Total hospitalization time | PIV | |
| Age | ||||
| ρ | - | -0.179 | -0.136 | -0.221 |
| P | - | 0.004 | 0.028 | < 0.001 |
| ICU time | ||||
| ρ | -0.179 | - | 0.444 | 0.265 |
| P | 0.004 | - | < 0.001 | < 0.001 |
| Total hospitalization time | ||||
| ρ | -0.136 | 0.444 | - | 0.315 |
| P | 0.028 | < 0.001 | - | < 0.001 |
| PIV | ||||
| ρ | -0.221 | 0.265 | 0.315 | - |
| P | < 0.001 | < 0.001 | < 0.001 | - |
| Hb | ||||
| ρ | 0.025 | -0.132 | -0.151 | -0.313 |
| P | 0.692 | 0.033 | 0.015 | < 0.001 |
| WBC | ||||
| ρ | -0.316 | 0.271 | 0.381 | 0.640 |
| P | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
| Neutrophil | ||||
| ρ | -0.265 | 0.271 | 0.371 | - |
| P | < 0.001 | < 0.001 | < 0.001 | - |
| Monocyte | ||||
| ρ | -0.305 | 0.199 | 0.184 | - |
| P | < 0.001 | 0.001 | 0.003 | - |
| Lymphocyte | ||||
| ρ | -0.025 | -0.075 | -0.064 | - |
| P | 0.693 | 0.225 | 0.302 | - |
| Platelet | ||||
| ρ | 0.095 | -0.073 | -0.058 | - |
| P | 0.127 | 0.239 | 0.351 | - |
| RDW | ||||
| ρ | 0.228 | 0.235 | 0.285 | 0.089 |
| P | < 0.001 | < 0.001 | < 0.001 | 0.152 |
| Albumin | ||||
| ρ | 0.073 | -0.223 | -0.163 | -0.332 |
| P | 0.240 | < 0.001 | 0.008 | < 0.001 |
| ASO | ||||
| ρ | -0.734 | 0.117 | 0.150 | 0.138 |
| P | < 0.001 | 0.060 | 0.016 | 0.027 |
| EF | ||||
| ρ | -0.449 | -0.074 | -0.247 | 0.106 |
| P | < 0.001 | 0.233 | < 0.001 | 0.087 |
| Troponin | ||||
| ρ | -0.365 | 0.241 | 0.652 | 0.245 |
| P | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
| CRP | ||||
| ρ | -0.612 | 0.321 | 0.414 | 0.359 |
| P | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
| D-dimer | ||||
| ρ | -0.152 | 0.326 | 0.587 | 0.337 |
| P | 0.014 | < 0.001 | < 0.001 | < 0.001 |
| Ferritin | ||||
| ρ | -0.602 | 0.288 | 0.172 | 0.376 |
| P | < 0.001 | < 0.001 | 0.005 | < 0.001 |
| Fibrinogen | ||||
| ρ | -0.058 | 0.330 | 0.610 | 0.228 |
| P | 0.349 | < 0.001 | < 0.001 | < 0.001 |
| LDL | ||||
| ρ | 0.353 | 0.180 | 0.235 | 0.040 |
| P | < 0.001 | 0.004 | < 0.001 | 0.524 |
| HDL | ||||
| ρ | -0.456 | -0.058 | -0.044 | 0.172 |
| P | < 0.001 | 0.350 | 0.476 | 0.005 |
| TRG | ||||
| ρ | -0.008 | 0.308 | 0.374 | 0.272 |
| P | 0.899 | < 0.001 | < 0.001 | < 0.001 |
| Glucose | ||||
| ρ | 0.217 | 0.231 | 0.257 | 0.072 |
| P | < 0.001 | < 0.001 | < 0.001 | 0.245 |
| Uric acid | ||||
| ρ | -0.086 | 0.333 | 0.345 | 0.277 |
| P | 0.169 | < 0.001 | < 0.001 | < 0.001 |
ASO, antistreptolysin O; CRP, C reactive protein; EF, ejection fraction; HDL, high density lipoprotein; ICU, intensive care unit; LDL, low density lipoprotein; PIV, Pan-Immune-Inflammatory Value; RDW, red cell distribution width; TRG, triglyceride; WBC, white blood cell.
Significant positive correlations were found between total hospital stay and troponin, fibrinogen, and D-dimer levels. In addition, a strong positive correlation was observed between PIV and WBC count (Table 4).
Adjusted analysis (ANCOVA)
After adjustment for age, sex, comorbidities, CRP, and troponin levels, ANCOVA analysis (with logarithmic transformation of PIV) demonstrated that PIV values remained significantly higher in patients with pericardial effusion (p < 0.001).
However, no significant differences were observed in relation to inotropic support (p = 0.277) or IVIG administration (p = 0.329) (Table 5).
Table 5. Comparison of PIV values according to specific conditions potentially associated with disease severity, after adjustment of covariates.
| Variable | Median (min-max) | ANCOVA* | ||
| F | ηp2 | p | ||
| Pericardial effusion | 22.566 | 0.082 | < 0.001 | |
| No (n = 184) | 526.09 (7.96-4346.5) | |||
| Yes (n = 74) | 900.89 (141.73-4146.6) | |||
| Inotrope support | 1.189 | 0.005 | 0.277 | |
| No (n = 251) | 589.10 (7.96-4346.5) | |||
| Yes (n = 9) | 1244.19 (548.4-1894.32) | |||
| IVIG | 0.956 | 0.004 | 0.329 | |
| No (n = 255) | 604.76 (7.96-4346.5) | |||
| Yes (n = 5) | 1244.19 (548.4-1894.32) |
* Covariates used for adjustments: age, gender, comorbidity, CRP and troponin.
Note: A logarithmic transformation was performed on the PIV variable before the ANCOVA analysis to reduce its skewed distribution and convert it to a normal distribution pattern.
Note: Subgroup results for IVIG and inotrope support are based on small samples (n = 5 and n = 9, respectively) and should be interpreted with caution.
ANCOVA, analysis of covariance; CRP, C-reactive protein; IVIG, intravenous immunoglobulin; PIV, Pan-Immune-Inflammatory Value.
ROC analysis
Receiver operating characteristic (ROC) analysis demonstrated that troponin had the highest predictive performance for hospitalization longer than 2 days [area under the curve (AUC): 0.873, p < 0.001].
CRP showed moderate predictive ability (AUC: 0.692, p < 0.001), while PIV demonstrated lower but still significant discriminatory performance (AUC: 0.651, p < 0.001) (Table 6, Figure 1).
Table 6. ROC analysis in terms of hospitalization time (> 2 days) and predictive values for PIV, CRP and troponin.
| AUC (95% CI) | p value | Cut-off | Sensitivity | Specificity | |
| PIV | 0.651 (0.585-0.718) | < 0.001 | ≥ 794.07 | 47.4% | 81.1% |
| CRP | 0.692 (0.627-0.757) | < 0.001 | ≥ 32.5 | 67.7% | 70.1% |
| Troponin | 0.873 (0.827-0.919) | < 0.001 | ≥ 1055.5 | 75.9% | 94.5% |
AUC, area under the curve; CI, confidence interval; CRP, C-reactive protein; PIV, Pan-Immune-Inflammatory Value; ROC, receiver operating characteristic.
Figure 1.
ROC curve analysis. AUC, area under the curve; CRP, C-reactive protein; PIV, Pan-Immune-Inflammatory Value; ROC, receiver operating characteristic.
DISCUSSION
The relationship between the PIV index and the duration of hospital stay in patients with myocarditis is a multifaceted issue that warrants detailed exploration. In our study, PIV levels were notably higher in patients with pericardial effusion and in those treated with IV steroids, whereas lower values were observed in patients receiving beta-blockers and ACE inhibitors. These findings suggest that PIV may be influenced by both the clinical presentation of myocarditis and the therapeutic interventions applied. Notably, although PIV did not reach statistical significance in predicting the duration of hospital stay, it was numerically higher in patients with prolonged hospitalization.
In addition, PIV values were significantly elevated in patients receiving inotropic support (n = 9) and those treated with IVIG (n = 5), suggesting an association with more severe clinical conditions requiring advanced therapies. However, these subgroup analyses were based on small sample sizes, and therefore, the findings should be interpreted with caution due to limited statistical power and generalizability. A higher PIV was also observed in patients with recent infectious conditions such as tonsillitis, supporting the link between systemic inflammation and PIV elevation. Furthermore, smoking and obesity appeared to be associated with increased PIV levels, indicating a potential contribution to worse clinical outcomes. In contrast, chronic comorbidities such as HT, HL, and DM were not associated with increased PIV in our cohort, suggesting a more complex interaction between chronic and acute inflammatory states.
Previous studies have highlighted the prognostic importance of inflammatory and clinical markers in myocarditis. In acute myocarditis, features such as persistent chest pain, pericardial effusion, cardiac tamponade, hypotension, reduced EF, low cardiac output, and sustained ventricular arrhythmias have been associated with a more severe and rapidly progressive disease course.17 The Lombardy registry, a multicenter Italian study involving 443 hospitalized patients with confirmed myocarditis, identified severe hemodynamic compromise at admission as the strongest predictor of cardiac mortality.18-20 Similarly, a multicenter study including 220 patients with biopsy-confirmed myocarditis demonstrated that hemodynamic compromise at presentation was the main determinant of both short- and long-term outcomes.21-23 In fulminant myocarditis, symptoms often develop rapidly within 2 days to 2 weeks, leading to significant hemodynamic deterioration and the need for aggressive supportive therapies, including vasopressors and mechanical circulatory support.24-26
Wu et al. reported that elevated PIV levels are associated with worse outcomes in various cardiovascular conditions, reflecting an increased inflammatory burden.27 Our findings are consistent with this observation, suggesting that higher PIV values may reflect more severe inflammatory responses in myocarditis and may be associated with prolonged hospitalization. However, the lack of statistical significance in our study (p = 0.64) indicates that PIV alone may not be sufficient as an independent predictor. Supporting this, ROC analysis demonstrated that PIV had moderate discriminatory ability (AUC: 0.651), whereas CRP and troponin showed superior predictive performance (AUC: 0.692 and 0.873, respectively), highlighting the importance of combining inflammatory and myocardial injury markers for risk stratification.
Our results also showed that patients with longer hospital stays were significantly younger, suggesting that younger individuals may present with more severe inflammatory responses requiring extended medical care. This observation is consistent with previous reports indicating that younger myocarditis patients may exhibit more acute and pronounced immune activation. Additionally, elevated RDW, CRP, and troponin levels were significantly associated with prolonged hospitalization, in line with previous studies emphasizing their role as markers of disease severity and prognosis.28
Interestingly, although PIV was not a significant predictor of hospitalization duration, it showed a strong correlation with WBC count, supporting its role as a marker of systemic inflammation. Previous studies have similarly demonstrated that elevated inflammatory indices are associated with adverse cardiovascular outcomes.29,30 The components of the PIV index reflect different aspects of the immune response: neutrophils and monocytes contribute to inflammation and tissue injury, lymphopenia may indicate immune dysregulation, and platelets are involved in both inflammation and endothelial activation. Therefore, PIV represents a composite marker of immune-inflammatory status that may be relevant in myocarditis.
Another noteworthy finding was the lower PIV values observed in patients with chronic comorbidities such as HT, HL, and DM. This may be explained by the long-term use of medications with anti-inflammatory properties, such as statins and ACE inhibitors. In addition, chronic inflammatory conditions may involve different immunological mechanisms compared to the acute inflammatory response observed in myocarditis, which could account for these findings.
The observed associations between hospitalization duration and biomarkers such as troponin, CRP, D-dimer, and fibrinogen further emphasize the importance of these parameters in clinical assessment. Elevated levels of these markers reflect both myocardial injury and systemic inflammation, which are key determinants of disease severity and clinical course.31
After adjustment for potential confounders including age, sex, comorbidities, CRP, and troponin levels, the association between PIV and pericardial effusion remained significant. However, this association was no longer observed in subgroups requiring inotropic support or IVIG therapy, suggesting that these relationships may be influenced by disease severity and treatment-related factors. Therefore, caution is warranted when interpreting subgroup analyses, as these findings may not reflect independent associations.
Previous research has primarily focused on other inflammatory indices such as HRR and RAR in myocarditis or on PIV in different cardiovascular conditions. In contrast, our study is the first to specifically evaluate the relationship between PIV and duration of hospital stay in patients with myocarditis, providing a novel perspective on the role of systemic inflammation in the clinical course of this disease.
Limitations
This study has several limitations that should be acknowledged. First, the diagnosis of myocarditis in our cohort was based on clinical presentation and non-invasive methods rather than endomyocardial biopsy or cardiac MRI, which are considered the gold standards for definitive diagnosis. The absence of these modalities may have led to potential misclassification or underestimation of disease presence and severity.
Second, B-type natriuretic peptide (BNP) levels were not available in our dataset. As a well-established biomarker reflecting cardiac dysfunction and hemodynamic status, the lack of BNP data may have limited a more comprehensive evaluation of cardiac involvement in our study population.
In addition, body mass index was not assessed, which may represent another limitation given its potential association with inflammatory status and clinical outcomes.
Furthermore, the small number of patients in certain subgroups, particularly those receiving IVIG or inotropic support, limits the reliability of subgroup analyses and may have affected statistical significance.
The retrospective design of the study introduces the possibility of selection and information bias. The use of medical records as the primary data source may have resulted in incomplete or inaccurate data collection, which could have influenced the study findings. Moreover, residual confounding factors that were not accounted for in the analysis may have affected the observed associations.
Finally, although previous studies have evaluated inflammatory indices in cardiovascular diseases, our study differs in terms of both the patient population (myocarditis) and the clinical endpoint (duration of hospital stay). The data and analyses presented in this study are original and have not been previously published.
CONCLUSION
In conclusion, our findings suggest that although the PIV was not an independent predictor of hospital stay duration in patients with myocarditis, it remains a clinically relevant marker associated with systemic inflammatory response. Higher PIV levels observed in patients with more severe clinical presentations, along with their correlations with established inflammatory markers, highlight the complex role of immune activation in the pathophysiology of myocarditis.
While conventional biomarkers such as troponin and CRP demonstrated superior predictive performance, PIV may still provide complementary information in the assessment of disease severity. These findings support the concept that a multimarker approach may be more effective for risk stratification in myocarditis.
Further prospective studies with larger cohorts are needed to clarify the prognostic value of PIV and to better define its role in clinical decision-making. To the best of our knowledge, this study is among the first to explore the association between PIV and hospitalization duration in myocarditis patients.
DECLARATION OF CONFLICT OF INTEREST
The authors have no conflict of interest to declare.
AUTHOR CONTRIBUTIONS
Concept – A.E.; Design – A.T.S.; Supervision – H.E.; Resources – A.E.; Materials – A.E., H.E.; Data Collection and/or Processing – A.E.; Analysis and/or Interpretation – A.T.S.; Literature Review – A.E.; Writing the Article – H.E.; Critical Review – A.E., A.T.S.
FINANCIAL DISCLOSURE
The authors declared that this study did not receive any financial support.
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