Evaluation of heart rate variability in pediatric patients with beta thalassemia major: Cross-sectional study

Abstract

BACKGROUND

Cardiac complications are a significant cause of morbidity and mortality in patients with β-thalassemia major (TM). Early detection of subclinical cardiac involvement remains challenging, as conventional echocardiography and electrocardiography often fail to identify early dysfunction. Heart rate variability (HRV) reflects autonomic regulation of the heart and may serve as a sensitive marker for early cardiac impairment.

AIM

To evaluate HRV in children with β-TM without clinical cardiac manifestations.

METHODS

A cross-sectional study was conducted on 40 children with β-TM and 40 age- and sex-matched healthy controls. All participants underwent full clinical assessment, laboratory investigations, and 24-hour ambulatory Holter monitoring. HRV parameters were analyzed in both time and frequency domains using Cardioscan CS12 software. Statistical comparisons between groups and correlations with hemoglobin and serum ferritin levels were performed using SPSS version 27.

RESULTS

Children with β-TM showed significantly higher minimum and maximum heart rates and markedly lower HRV indices, including standard deviation of all normal-to-normal intervals (SDNN), standard deviation of the 5-minutes average normal-to-normal intervals, SDNN index, root mean square of successive differences, and percentage of normal-to-normal intervals differing by > 50 ms, compared with controls (P < 0.001). High-frequency (HF) power was significantly decreased, whereas the low-frequency/HF ratio was elevated (P < 0.001), indicating sympathetic predominance. Arrhythmias were recorded in 47.5% of patients, though HRV parameters did not differ significantly between those with and without arrhythmia. No correlation was found between HRV indices and hemoglobin or serum ferritin levels.

CONCLUSION

Children with β-TM demonstrate significant autonomic imbalance, reflecting early cardiac involvement even before the onset of clinical symptoms. Routine HRV assessment could provide a valuable, non-invasive tool for early detection and risk stratification in pediatric thalassemia management.

Key Words: β-thalassemia major; Heart rate variability; Autonomic dysfunction; Pediatric cardiology; Iron overload

Core Tip: Children with β-thalassemia major may develop cardiac dysfunction long before echocardiographic or clinical evidence appears. This study demonstrates that heart rate variability (HRV) analysis can detect early autonomic imbalance, reflecting subclinical cardiac involvement. Routine HRV monitoring in pediatric thalassemia patients offers a simple, non-invasive method to identify high-risk individuals and initiate preventive measures early, potentially improving cardiac outcomes and survival.

INTRODUCTION

β-thalassemia major (TM) is a hereditary chronic hemolytic anemia caused by defective or absent synthesis of the β-globin chain of hemoglobin[1]. Advances in transfusion and chelation therapy have markedly improved survival, yet cardiac complications remain the leading cause of morbidity and mortality in these patients[2,3]. Chronic anemia, recurrent blood transfusions, and progressive iron overload contribute to myocardial dysfunction, arrhythmias, and heart failure, which often develop silently before becoming clinically evident[1,2].

Traditional diagnostic modalities such as echocardiography and electrocardiography may fail to detect early subclinical cardiac involvement, as structural or rhythm changes usually appear late in the disease course. Therefore, identifying reliable, non-invasive markers for early cardiac dysfunction is essential for timely intervention[3].

Heart rate variability (HRV) is a physiological phenomenon characterized by changes in the intervals between heartbeats. It is a quantitative measure of variations in the intervals between consecutive heartbeats, reflecting autonomic nervous system regulation of cardiac function[4]. Reduced HRV has been associated with increased cardiovascular risk and autonomic dysfunction in several diseases, including diabetes, heart failure, and neurological disorders. As a sensitive and non-invasive tool, HRV may serve as an early predictor of cardiac autonomic imbalance before overt cardiac damage develops[4-6]. Various studies support the link between HRV and cardiovascular morbidity and mortality[7-10].

Cardiac complications are the leading cause of morbidity and mortality in TM patients. The underlying pathophysiology-chronic anemia, repeated blood transfusions, and progressive iron overload-contributes to myocardial damage. Chronic anemia and resultant tissue hypoxia can trigger a compensatory increase in sympathetic drive to maintain cardiac output. Over time, this sustained sympathetic overactivity leads to autonomic dysregulation[11]. Furthermore, progressive iron overload in the myocardium is known to cause oxidative stress and lipid peroxidation, which can directly damage the cardiac conduction system and interfere with autonomic signaling and sinoatrial node responsiveness[12]. This damage is thought to lead to subclinical myocardial fibrosis and decreased vagal (parasympathetic) modulation. HRV measures the balance between the sympathetic and parasympathetic branches of the autonomic nervous system, making it a sensitive, non-invasive tool to detect this autonomic nervous system imbalance (autonomic dysfunction) early, even before overt structural damage or clinical symptoms appear. Detecting this early shift toward sympathetic predominance is crucial, as sympathetic overactivity is linked to arrhythmogenesis and increased cardiovascular risk[13].

Given the paucity of data in pediatric β-thalassemia and the potential role of HRV in detecting early cardiac involvement, this study aimed to evaluate HRV in children with β-TM without apparent cardiac symptoms, to identify early signs of autonomic and cardiac dysfunction. We hypothesized that children with β-TM exhibit reduced HRV compared with healthy controls, reflecting early autonomic and subclinical cardiac dysfunction.

MATERIALS AND METHODS

Study setting, design, and population

This cross-sectional study was conducted in the Pediatric Haematology and Cardiology Units of the Department of Pediatrics, Faculty of Medicine, Tanta University Hospital, a tertiary care and referral center in Egypt, between April 2023 and March 2024. A total of 80 children were enrolled and divided into two groups: Group I (patients): 40 children diagnosed with β-TM (22 males/18 females); group II (controls): 40 age- and sex-matched healthy children with no history of hematologic or cardiac disorders (18 males/22 females). The sample size of 40 patients and 40 controls was determined based on previous HRV studies in pediatric populations and the available pool of eligible thalassemia patients during the study period.

Ethical approval was obtained from the Institutional Ethical Committee of the Faculty of Medicine, Tanta University (No. 36264MS112/3/23). Written informed consent was obtained from the parents or legal guardians of all participants before enrollment.

Inclusion and exclusion criteria

Children aged 1-18 years with a confirmed diagnosis of β-TM were eligible for inclusion. Patients were excluded if they had any of the following: (1) Clinical or echocardiographic evidence of symptomatic cardiac disease; (2) Congenital or acquired heart disease; or (3) Any comorbid conditions that could influence autonomic function.

To minimize selection bias, controls were matched for age and sex. All HRV analyses were performed by an investigator blinded to the participants’ clinical status.

Study variables

The primary outcome variable was HRV parameters derived from 24-hour Holter monitoring. Independent variables included age, sex, hemoglobin level, and serum ferritin concentration.

Clinical and laboratory evaluation

All participants underwent a detailed medical history and physical examination. Anthropometric parameters (weight and height) were assessed as part of the complete clinical assessment. Weight was measured using a standardized calibrated digital scale, and height was measured using a stadiometer, following standard clinical practice to calculate body mass index (BMI, kg/m²). Laboratory investigations included a complete blood count (CBC), high-performance liquid chromatography (HPLC) for hemoglobin typing, liver and renal function tests, and assessment of serum ferritin levels. Blood collection was performed using standard venipuncture techniques for routine laboratory investigations. Laboratory investigations included CBC, HPLC for haemoglobin typing, liver and renal function tests, and assessment of serum ferritin levels. Hemoglobin, mean corpuscular volume, mean corpuscular hemoglobin, and other CBC parameters were measured using an automated hematology analyzer (e.g., Coulter counter or similar validated device). Serum ferritin was quantified using a validated immunoassay method (e.g., chemiluminescence immunoassay or enzyme-linked immunosorbent assay). HPLC was used to confirm the diagnosis of β-TM and assess hemoglobin fractions.

HRV assessment

HRV was evaluated in all subjects using 24-hour ambulatory electrocardiogram (ECG) monitoring (Holter device, DMS 300-3A recorder, Cardioscan CS12 software; DM Software Inc., United States). Data were analyzed using both time-domain and frequency-domain methods (Figures 1 and 2). Time-domain parameters included[11]: Standard deviation of all normal-to-normal (NN) intervals (overall HRV) (SDNN), Standard deviation of the average NN intervals in 5-minute segments (long-term variability) (SDANN); mean of 5-minute standard deviations of NN intervals (short-term variability) (SDNN index), root mean square of successive NN interval differences (parasympathetic activity) (RMSSD), percentage of successive NN intervals differing by more than 50 ms (short-term variation) (pNN50). Frequency-domain parameters were calculated using a fast Fourier transform and included: Total power (0-0.4 Hz), high-frequency (HF) power (0.15-0.4 Hz): Indicator of parasympathetic activity; low-frequency (LF) power (0.04-0.15 Hz): Reflecting both sympathetic and parasympathetic activity; very LF (VLF) power (0.003-0.04 Hz) and ultra-LF power (0-0.003 Hz): Associated with neurohumoral and thermoregulatory mechanisms[12]. The LF/HF ratio was also calculated to assess sympathovagal balance[14,15].

Figure 1 Heart rate variability analysis in a thalassemia patient. A: Spectral and time-domain plots of heart rate variability (HRV) in an 8-year-old child with β-thalassemia major over 24 hours, showing both awake (06:00-22:00) and sleep (22:00-06:00) phases. The patient demonstrates a marked reduction in overall HRV with decreased root mean square of successive normal-to-normal interval differences (parasympathetic activity), percentage of successive normal-to-normal intervals differing by more than 50 ms (short-term variation) and high-frequency (HF) power, reflecting diminished parasympathetic activity; B: Corresponding 24-hour HRV spectral power distribution and RR interval histogram from the same patient shows significantly low total power (912.3 ms²) with a blunted HF (19.7) component. This pattern is consistent with significant autonomic imbalance and reduced parasympathetic modulation. VLF: Very low frequency; LF: Low frequency; HF: High frequency; SDNN: Standard deviation of all normal-to-normal intervals; SDANN: Standard deviation of the 5-minutes average normal-to-normal intervals; RMSSD: Root mean square of successive differences; pNN50: Percentage of successive normal-to-normal intervals differing by > 50 ms.

Figure 2 Heart rate variability analysis in a healthy control. A: Spectral and time-domain plots of heart rate variability (HRV) in a 7-year-old healthy control child over 24 hours, including awake and sleep phases. HRV parameters are within normal limits for age [e.g., standard deviation of all normal-to-normal intervals (SDNN): 124, root mean square of successive differences: 57], with clear circadian variation (e.g., SDNN 118 awake vs 108 asleep), showing balanced sympathetic and parasympathetic modulation with appropriate circadian variation; B: Corresponding 24-hour HRV spectral power distribution and RR interval histogram from the same child, demonstrating high total power (3155.0 ms²) with balanced low-frequency (608.3) and high-frequency (470.0) components, consistent with intact autonomic regulation. VLF: Very low frequency; LF: Low frequency; HF: High frequency; SDNN: Standard deviation of all normal-to-normal intervals; SDANN: Standard deviation of the 5-minutes average normal-to-normal intervals; RMSSD: Root mean square of successive differences; pNN50: Percentage of successive normal-to-normal intervals differing by > 50 ms.

Statistical analysis

Data were analyzed using IBM SPSS Statistics for Windows, Version 27.0 (IBM Corp., Chicago, IL, United States). Data normality was tested using the Shapiro-Wilk test and visual inspection of histograms. Quantitative variables were expressed as the mean ± SD for normally distributed data or as the median (interquartile range) for non-normally distributed data.

Comparisons between the two groups were performed using the independent-samples t-test or the Mann–Whitney U test, as appropriate. Categorical variables were presented as n (%) and compared using the χ² test. Correlations between HRV parameters and laboratory variables (hemoglobin and serum ferritin) were evaluated using Pearson’s or Spearman’s correlation coefficients. A two-tailed P value < 0.05 was considered statistically significant. No missing data were observed; all analyses were performed on complete datasets.

RESULTS

Demographic and clinical characteristics

Of the 85 children initially screened, 80 met the inclusion criteria and completed all assessments: 40 patients with β-TM (group I) and 40 healthy controls (group II). The mean age of the patient group was 9.24 ± 4.01 years, while that of the control group was 7.88 ± 3.82 years, with no significant difference between groups (P = 0.124). The male-to-female ratio was comparable (55% vs 45% in patients and 45% vs 55% in controls, P = 0.371). However, children with β-thalassemia had significantly lower mean weight (26.15 ± 9.94 kg vs 34.40 ± 14.41 kg, P = 0.020), height (1.20 ± 0.20 m vs 1.32 ± 0.25 m, P = 0.022), and BMI (17.57 ± 2.46 kg/m² vs 18.72 ± 2.60 kg/m², P = 0.045) compared with the controls (Table 1).

Table 1 Comparison between the two studied groups regarding demographic, clinical, and laboratory data, mean ± SD/median (25^th-75^th percentiles).

Parameter	β-thalassemia (n = 40)	Controls (n = 40)	P value
Age (years)	9.24 ± 4.01	7.88 ± 3.82	0.124
Sex (male/female)	22/18	18/22	0.371
Weight (kg)	26.15 ± 9.94	34.40 ± 14.41	0.020
Height (m)	1.20 ± 0.20	1.32 ± 0.25	0.022
BMI (kg/m2)	17.57 ± 2.46	18.72 ± 2.60	0.045
Serum ferritin (ng/mL)	970 (690-1712.5)	79 (59-99)	< 0.001
Hb (g/dL)	8.34 ± 0.96	11.08 ± 0.50	< 0.001
PLT (× 103/μL)	364.1 ± 18.20	358.4 ± 12.68	0.104
WBCs (× 103/μL)	10.85 ± 9.68	9.05 ± 1.16	0.376
MCV (fL)	67.8 ± 6.0	80.8 ± 5.2	0.001
MCH (pg)	25.5 ± 2.1	28.7 ± 1.9	0.014
RDW (%)	14.1 ± 1.2	13.8 ± 1.1	0.917
Reticulocytes (%)	6.12 ± 1.5	0.84 ± 0.22	0.001

BMI: Body mass index; Hb: Hemoglobin; PLT: Platelets; WBCs: White blood cells; MCV: Mean corpuscular volume; MCH: Mean corpuscular hemoglobin; RDW: Red cell distribution width.

As expected, laboratory investigations revealed significantly lower hemoglobin (8.34 ± 0.96 g/dL vs 11.08 ± 0.50 g/dL, P < 0.001), mean corpuscular volume (67.8 ± 6.0 fL vs 80.8 ± 5.2 fL, P = 0.001), and mean corpuscular hemoglobin (25.5 ± 2.1 pg vs 28.7 ± 1.89 pg, P = 0.014) in the patient group. Serum ferritin levels and reticulocyte counts were markedly elevated in the patient group compared with controls [970 (690-1712.5) ng/mL vs 79 (59-99) ng/mL, P < 0.001; 6.12% ± 1.5% vs 0.84% ± 0.22%, P = 0.001, respectively]. No significant difference was noted in platelet count, white blood cell count, or red cell distribution width between the groups.

Heart rate and HRV parameters

Table 2 summarizes the differences in heart rate and HRV indices between the two study groups. Children with β-thalassemia had significantly higher minimum and maximum heart rates than controls (minimum: 63.35 ± 13.06 bpm vs 58.50 ± 4.44 bpm, P = 0.031; maximum: 161.4 ± 16.98 bpm vs 147.5 ± 5.31 bpm, P < 0.001). Time-domain parameters of HRV-including SDNN, SDANN5, SDNN index, RMSSD, and pNN50%-were all significantly lower in the β-thalassemia group compared with the control group (all P < 0.001). Similarly, the HF power was significantly lower in patients [median = 323.4 (239.95-404.1) ms²] than in controls [537.0 (269.25-872.25) ms², P = 0.002]. Figures 1 and 2 are graphs obtained from HRV analysis using the Holter software, illustrating the marked difference in HRV patterns between a representative beta-thalassemia patient and a healthy control. Figure 1 displays the spectral and time-domain plots for an 8-year-old patient, showing a significantly blunted HF component and a low total power (912.3 ms²), which is indicative of diminished parasympathetic activity and significant autonomic imbalance[16]. In contrast, Figure 2, representing a 7-year-old healthy control, demonstrates a high total power (3155.0 ms²) with a balanced distribution of LF and HF components, consistent with intact and appropriate autonomic regulation. The purpose of these figures is to provide a visual and qualitative comparison that supports the quantitative findings in Table 2, highlighting the substantial reduction in overall HRV in the patient group.

Table 2 Comparison between the two studied groups regarding heart rate and heart rate variability parameters, mean ± SD/median (25^th-75^th percentiles).

Parameter	β-thalassemia (n = 40)	Controls (n = 40)	P value
Minimum HR (bpm)	63.35 ± 13.06	58.50 ± 4.44	0.031
Maximum HR (bpm)	161.4 ± 16.98	147.5 ± 5.31	< 0.001
Average HR (bpm)	100.6 ± 13.03	103.3 ± 3.49	0.216
SDNN (ms)	79.18 ± 32.08	137.2 ± 17.53	< 0.001
SDANN5 (ms)	74.43 ± 23.75	122.5 ± 19.89	< 0.001
SDNN index (ms)	41.70 ± 14.85	101.0 ± 20.14	< 0.001
RMSSD (ms)	28.43 ± 13.81	54.13 ± 14.80	< 0.001
pNN50 (%)	8.93 ± 8.12	32.65 ± 11.48	< 0.001
HF power (ms2)	323.4 (239.9-404.1)	537.0 (269.3-872.3)	0.002
LF power (ms2)	670.8 (537.3-814.2)	614.0 (335.0-733.1)	0.125
VLF power (ms2)	1283.3 (1005.2-1441.2)	1240.0 (864.4-2050.5)	1.000
LF/HF ratio	2.11 (1.64-2.68)	1.16 (0.89-1.50)	< 0.001

No significant sex-based or age-dependent differences were observed in heart rate variability parameters among the patient group, suggesting that autonomic dysfunction in β-thalassemia may not be influenced by these demographic factors. HR: Heart rate; SDNN: Standard deviation of all normal-to-normal intervals; SDANN: Standard deviation of the 5-minute average normal-to-normal intervals; RMSSD: Root mean square of successive differences; pNN50: Percentage of successive normal-to-normal intervals differing by > 50 ms; LF: Low frequency; HF: High frequency; VLF: Very low frequency.

Conversely, the LF and VLF domains showed no significant intergroup differences (P = 0.125 and P = 1.000, respectively). The LF/HF ratio, an indicator of sympathovagal balance, was markedly higher in the patient group [median = 2.109 (1.644-2.676)] than in controls [1.164 (0.885-1.498); P < 0.001], indicating increased sympathetic and reduced parasympathetic activity among patients with β-thalassemia.

Arrhythmia detection

Arrhythmias were detected in 19 of the 40 thalassemia patients (47.5%) during the 24-hour Holter monitoring (Table 3). The most frequently observed rhythm abnormalities were infrequent supraventricular ectopic beats (27.5%), followed by infrequent single ventricular ectopic beats (12.5%), frequent supraventricular ectopic beats (5%), and frequent ventricular ectopic beats and non-sustained ventricular tachycardia (2.5%). Benign arrhythmias, such as a wandering atrial pacemaker, were recorded in 10% of patients. When patients were stratified into Group IA (with arrhythmia) and Group IB (without arrhythmia), there were no statistically significant differences between the two subgroups in any HRV time or frequency-domain parameter (Table 4). This suggests that autonomic dysfunction in thalassemia may precede overt rhythm disturbances.

Table 3 Presence and type of arrhythmia in patients with β-thalassemia major.

Parameter	n (%)
Patients with arrhythmia (group IA)	19 (47.5)
Patients without arrhythmia (group IB)	21 (52.5)
Types of arrhythmia
Infrequent supraventricular ectopic beats	11 (27.5)
Infrequent ventricular ectopic beats	5 (12.5)
Frequent supraventricular ectopic beats	2 (5.0)
Frequent ventricular ectopic beats and non-sustained ventricular tachycardia	1 (2.5)
Benign arrhythmias (e.g., wandering atrial pacemaker)	4 (10.0)

Some patients exhibited more than one arrhythmia type during Holter monitoring.

Table 4 Comparison of heart rate variability parameters between patients with and without arrhythmia, mean ± SD/median (25^th-75^th percentiles).

Parameter	With arrhythmia (n = 19)	Without arrhythmia (n = 21)	P value
Minimum HR (bpm)	63.76 ± 13.16	62.89 ± 13.30	0.837
Maximum HR (bpm)	161.4 ± 19.43	161.4 ± 14.34	0.999
Average HR (bpm)	101.2 ± 11.50	99.89 ± 14.83	0.749
SDNN (ms)	78.24 ± 28.67	80.21 ± 36.26	0.649
SDANN5 (ms)	72.43 ± 23.28	76.63 ± 24.69	0.503
SDNN index (ms)	38.71 ± 11.83	45.00 ± 17.34	0.236
RMSSD (ms)	25.76 ± 13.17	31.37 ± 14.24	0.204
pNN50 (%)	7.48 ± 7.87	10.53 ± 8.30	0.169
HF power (ms2)	326.6 (254.7-349.7)	320.2 (234.4-492.1)	0.776
LF power (ms2)	667.3 (595.7-759.3)	674.2 (447.9-899.9)	0.745
VLF power (ms2)	1289.5 (1234.1-1400.5)	1234.8 (890.8-1436.5)	0.626
LF/HF ratio	1.99 (1.78-2.45)	2.29 (1.57-2.71)	0.818

HR: Heart rate; SDNN: Standard deviation of all normal-to-normal intervals; SDANN: Standard deviation of 5-minute average normal-to-normal intervals; RMSSD: Root mean square of successive differences; pNN50: Percentage of normal-to-normal intervals differing by > 50 ms; LF: Low frequency; HF: High frequency; VLF: Very low frequency.

Other ECG parameters, including waves and intervals

Different wave and interval measurements were compared between the two groups. There was a significant increase in some ECG parameters in Thalassemia patients, which were: P wave dispersion, R wave amplitude in channel 1, which is a left-sided precordial lead, and R wave amplitude in CH2, which is a right-sided precordial lead, duration of QRS, duration of PR interval, and QT corrected intervals measured by the Bazett formula (Table 5).

Table 5 Comparison between the two studied groups regarding different waves and intervals, median (25^th-75^th percentiles)/n (%).

		Patient group (n = 40)	Control group (n = 40)	P value
P wave	Amplitude (mm)	3 (2-3)	2 (2–3)	0.385
	Duration (second)	0.08 (0.08-0.08)	0.08 (0.08-0.09)	0.597
	Dispersion (second)	0.04 (0.04-0.04)	0.035 (0.02-0.04)	< 0.001
QRS complex	R wave amplitude in channel 1 (mm)	25 (23-26)	24 (23-24)	0.004
	R wave amplitude in in channel 2 (mm)	12 (8-15)	7 (4-10)	< 0.001
	S wave amplitude in in channel 1 (mm)	4 (2-7)	5 (3-7)	0.438
	S wave amplitude in channel 2 (mm)	7 (6-9)	7 (5-8)	0.081
	Duration (second)	0.12 (0.11-0.12)	0.08 (0.08-0.08)	< 0.001
PR interval	Constant	40 (100.0)	40 (100.0)
	1:1 AV conduction	40 (100.0)	40 (100.0)
	Duration (second)	0.16 (0.12-0.16)	0.12 (0.12-0.12)	< 0.001
ST segment	Normal	36 (90.0)	40 (100.0)	0.116
	Elevation	0 (0.0)	0 (0.0)
	Depression	4(10)	0 (0.0)	0.116
T wave abnormalities	Normal	39 (97.5)	40 (100.0)	1.000
	Inversion	1 (2.5)	0 (0.0)	1.000
QT corrected (msec)		464.5 (443-481)	405 (380-430)	< 0.001

AV: Atrioventricular.

Correlation between HRV and laboratory parameters

Correlation analysis revealed no significant associations between serum ferritin or hemoglobin levels and any HRV parameter (Table 6). Neither iron overload nor anemia severity showed a measurable relationship with autonomic cardiac indices.

Table 6 Correlation between serum ferritin, hemoglobin level, and heart rate variability parameters in β-thalassemia patients.

Variable	HRV parameter	Spearman’s ρ	P value
Hemoglobin	LF power	0.230	0.154
	HF power	-0.188	0.244
	SDANN	-0.162	0.317
	RMSSD	-0.070	0.666
Serum ferritin	LF power	-0.096	0.557
	HF power	-0.012	0.943
	SDANN	0.194	0.230
	RMSSD	-0.130	0.425

Correlation between heart rate variability indices and laboratory parameters assessed using Spearman’s test. None of the correlations were statistically significant (P > 0.05). LF: Low frequency; HF: High frequency; SDANN: Standard deviation of the 5-minute mean normal-to-normal intervals; RMSSD: Root mean square of successive differences; HRV: Heart rate variability.

DISCUSSION

This cross-sectional study demonstrated that children with β-TM exhibit significant autonomic dysfunction, evidenced by reduced HRV indices and elevated LF/HF ratios, even in the absence of clinical cardiac disease. HRV is a sensitive, non-invasive marker of autonomic nervous system activity and is increasingly recognized as an early indicator of cardiovascular problems[7,14,16,17]. In this study, we assessed HRV in children with β-TM without overt cardiac symptoms. Our results showed significant impairment across multiple specific parameters in both the time domain (e.g., reduced SDNN, SDANN5, RMSSD, and pNN50%) and the frequency domain (e.g., reduced HF power and elevated LF/HF ratio) compared with healthy controls. The detailed analysis of these individual parameters confirms a comprehensive autonomic dysfunction, not just an alteration in a single measure. For example, reductions in RMSSD and pNN50% specifically reflect decreased parasympathetic (vagal) activity. At the same time, the elevation in the LF/HF ratio indicates sympathetic predominance, thus providing a detailed picture of the autonomic imbalance in β-TM. These results suggest an imbalance in autonomic function, characterized by increased sympathetic and decreased parasympathetic activity, indicating early subclinical cardiac involvement in children with thalassemia[7].

Comparison with previous studies

Our results are consistent with earlier reports demonstrating reduced HRV in thalassemia patients. Rutjanaprom et al[3] found marked reductions in both time- and frequency-domain parameters in TM patients compared with controls, supporting the hypothesis that autonomic dysfunction occurs before detectable cardiac failure. Similarly, Oztarhan et al[18] and Kardelen et al[2] observed significantly decreased SDNN and RMSSD values among TM patients, even in the absence of echocardiographic abnormalities. In addition to these reports, our findings emphasize that HRV abnormalities may precede structural or symptomatic cardiac changes.

Cakan et al[1] demonstrated that red blood cell transfusion transiently improved HRV indices, implicating anemia and hypoxia as modulators of cardiac autonomic tone. However, in our study, neither hemoglobin concentration nor serum ferritin correlated significantly with HRV indices, suggesting that autonomic dysregulation in TM is multifactorial and may involve chronic oxidative stress, myocardial iron deposition, and altered baroreceptor sensitivity rather than anemia severity or iron load alone. However, we did not find a significant difference in HRV parameters between children with arrhythmia and those without, in contrast to the findings of Alp et al[19], who reported differences in HRV parameters across arrhythmia types in their study of HRV in patients with TM. However, they did not compare HRV in patients with or without arrhythmia.

Interpretation and pathophysiological insights

Several mechanisms may underlie the reduction in HRV observed in thalassemia. Chronic anemia and tissue hypoxia can increase sympathetic drive as a compensatory mechanism to maintain cardiac output. Over time, repeated transfusions lead to iron overload, triggering free radical generation and lipid peroxidation that may damage the cardiac conduction system and interfere with autonomic signaling. Moreover, subclinical myocardial fibrosis and altered sinoatrial node responsiveness have been implicated in decreased vagal modulation[20-22].

The elevated LF/HF ratio observed in our study reflects a shift toward sympathetic predominance, which has been associated with arrhythmogenesis and early ventricular dysfunction in other pediatric populations. Interestingly, almost half of our patients exhibited arrhythmic events during Holter monitoring, yet their HRV indices did not differ significantly from those without arrhythmia. This finding may indicate that HRV alterations precede clinically detectable arrhythmias, making HRV a potential early screening tool for autonomic dysfunction before rhythm disturbances emerge[3,23,24].

We concur that the lack of correlation between HRV indices and serum ferritin or hemoglobin levels suggests that autonomic dysfunction is not simply a direct consequence of the current degree of anemia or iron overload. This lack of correlation does not undermine HRV’s utility; instead, it suggests that autonomic dysregulation in beta-thalassemia is likely multifactorial, involving mechanisms such as chronic oxidative stress, microvascular injury, and subclinical myocardial damage that develop independently of the measured ferritin level[25].

Clinical implications

The present findings underscore the clinical importance of incorporating HRV assessment into the routine evaluation of children with β-TM, even in the absence of cardiac symptoms. Regular HRV monitoring can help identify patients at risk of developing cardiac autonomic dysfunction or impending heart failure, thereby allowing for timely modification of management strategies-such as optimizing transfusion schedules, early initiation of chelation therapy, and closer cardiology follow-up[26]. Furthermore, HRV analysis can serve as a complementary tool alongside echocardiography and cardiac magnetic resonance imaging (MRI) to provide a comprehensive assessment of cardiac health in thalassemia patients[27].

From a pediatric practice standpoint, early identification of autonomic imbalance through HRV monitoring offers an opportunity for preventive cardioprotection. Interventions targeting sympathetic overactivity-such as aerobic exercise programs, optimized iron chelation therapy, and antioxidant supplementation—may preserve cardiac function and improve long-term outcomes[28].

While all patients in the current study underwent 24-hour Holter monitoring, which captures different data, the primary focus of this study was mainly on HRV to assess early autonomic dysfunction in the absence of clinical cardiac disease. We note that arrhythmias are present in nearly half the patients, as well as significant abnormalities in some intervals and waves. A substantial increase in P-wave dispersion among patients indicates interatrial conduction disturbances and an increased risk of arrhythmia[29]. An increase in QRS duration could suggest inter- or intraventricular conduction delay, necessitating further evaluation of cardiac function with other tools, such as echocardiography and MRI[30]. Increased R-wave amplitude in CH1 and CH2 indicates the possibility of ventricular hypertrophy. Significantly prolonged PR intervals in some patients indicate first-degree atrioventricular block (AVB), so they should be followed for higher degrees of AVB. Additionally, patients with significant Long QTc intervals should be followed up for malignant ventricular arrhythmia[31]. For that, the clinical utility of further evaluating such ECG parameters should be considered. As we couldn’t demonstrate significant differences in HRV parameters between patients with arrhythmia and those without, this suggests that HRV can be affected early in thalassemia patients, even without clinical symptoms.

Study limitations

This study has several limitations. First, the sample size was relatively small, which may limit the generalizability of the results. Second, the cross-sectional design precludes assessment of causal relationships between changes in HRV and the development of overt cardiomyopathy. Third, we did not include echocardiographic or cardiac MRI parameters to correlate autonomic dysfunction directly with myocardial structure or iron load. Fourth, short-term variations in transfusion timing, chelation adherence, or infection status might have influenced HRV readings.

Future directions

Future longitudinal studies with larger sample sizes are warranted to evaluate the progression of HRV alterations over time and their predictive value for clinical cardiac outcomes. Combining HRV assessment with imaging modalities, serum oxidative stress markers, and chelation status could clarify underlying mechanisms and guide targeted interventions. Additionally, interventional studies exploring whether improving HRV through pharmacologic or lifestyle measures can reduce cardiac morbidity in β-thalassemia are strongly recommended. Although the study was conducted in a single tertiary center, the findings are likely generalizable to other pediatric thalassemia populations in similar healthcare settings. Taken together, these findings underscore the growing importance of HRV as a practical tool for early detection and prevention of cardiac complications in pediatric thalassemia.

CONCLUSION

In conclusion, our cross-sectional study demonstrates that children with β-TM, despite lacking overt clinical cardiac manifestations, exhibit significant impairment in HRV across both time- and frequency-domain indices (including reduced SDNN, RMSSD, and HF power). This pattern, coupled with an elevated LF/HF ratio, reflects a significant autonomic imbalance characterized by sympathetic predominance and reduced parasympathetic modulation. Importantly, this autonomic dysfunction was observed independently of the current serum ferritin concentration or hemoglobin level, suggesting that the underlying mechanism of cardiac risk in thalassemia may develop independently of the markers typically used to monitor disease severity. This finding underscores that the value of HRV lies in its ability to detect early, subclinical cardiac involvement rather than correlating with the current degree of iron overload or anemia. Therefore, non-invasive HRV analysis is a sensitive tool for early detection and risk stratification of patients, identifying those at increased risk of future cardiac complications. Integrating routine HRV assessment into the follow-up of pediatric patients with thalassemia could guide timely optimization of supportive and chelation therapy, ultimately improving long-term cardiac outcomes and quality of life. Larger, prospective studies are warranted to confirm these findings and to establish standardized HRV-based monitoring protocols. Future research should also incorporate detailed analysis of other cardiac parameters (e.g., QRS, QT intervals) and advanced cardiac imaging to provide a more comprehensive correlation between autonomic status and myocardial structure/function.

ACKNOWLEDGEMENTS

We thank the editors and the anonymous referees for their valuable suggestions.