QT Interval and QT Dispersion Abnormalities in Hospitalized Patients with Epilepsy: A Multi-Lead Electrocardiographic Study

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Ventricular repolarization abnormalities, particularly QT prolongation and QT dispersion, may contribute to arrhythmogenic risk. however, data remain limited and inconsistent, especially in hospitalized Middle Eastern populations. Methods This retrospective cross-sectional study evaluated QT parameters in 104 hospitalized epilepsy patients admitted between March 2022 and March 2024. Standard 12-lead interictal ECGs were analyzed to measure QT, corrected QT (QTc), mean QTc, QT dispersion (QTd), and corrected QT dispersion (QTcd). Associations between QT parameters and age, sex, epilepsy duration, treatment status, and serum electrolytes were examined. Results QTc prolongation was observed in 28.8% of patients. QTd and QTcd were 52 ± 2 and 63 ± 26 milliseconds (ms) on average. QTd and QTcd exceeding 65 ms were observed in 21.1% and 44.2% of patients respectively. lead I QTc was significantly lower in men (p = 0.013). No significant differences in QT parameters were observed by epilepsy duration or treatment status. Age showed a significant positive correlation solely with mean QTc (r = 0.222, P = 0.024). Among serum electrolytes, only potassium demonstrated a significant inverse correlation with mean QTc (r = − 0.230, P = 0.019). Conclusions High frequencies of increased QT interval, QT dispersion, and arrhythmic and mortality risks were demonstrated in our population. QTc prolongation correlated with female sex (lead-dependent), advanced age and lower physiological levels of potassium, which provides insight into modulators of ventricular repolarization in epilepsy and role of QT markers in arrhythmia risk stratification and SUDEP pathophysiology. Epilepsy QT Interval QT dispersion Ventricular Repolarization Electrocardiography Sudden Unexpected Death in Epilepsy (SUDEP) Background Epilepsy is a chronic brain disorder characterized by a persistent predisposition to generate recurrent unprovoked seizures [ 1 ]. It affects over 50 million people worldwide, slightly more prevalent in men than in women, and represents a major cause of neurological morbidity. [ 2 , 3 ] Epilepsy incidence follows a bimodal age distribution, with peaks in early childhood and late adulthood. Overall, it is one of the most common chronic neurological disorders worldwide, imposing substantial medical and socioeconomic burden [ 4 ]. According to the International League Against Epilepsy (ILAE), epilepsy etiologies are categorized into six major groups: genetic, structural, metabolic, autoimmune, infectious, and unknown [ 5 ]. The diagnosis of epilepsy is primarily clinical and within a stepwise approach, involving confirming the epileptic nature of the event and defining the epilepsy syndrome by integrating seizure type and pattern, age at onset, electroencephalographic findings, etiology, and associated comorbidities [ 5 ]. Beyond its high prevalence, epilepsy is associated with a markedly increased risk of premature mortality. Patients with epilepsy experience a two- to three-fold higher risk of early death compared with the general population [ 6 ], a disparity that is particularly pronounced in low- and middle-income countries [ 5 ]. Among epilepsy-related causes, sudden unexpected death in epilepsy (SUDEP) is a leading contributor. SUDEP is defined as a sudden, unexpected, non-traumatic, and non-drowning death in individuals with epilepsy, occurring in the absence of a toxicological or structural cause identified at autopsy [ 7 ]. The incidence of SUDEP is estimated at approximately 1.16 per 1,000 persons with epilepsy per year. In terms of years of life lost among neurological disorders, SUDEP ranks second only to stroke, largely because it predominantly affects young adults between 20 and 40 years of age [ 8 ]. Despite being a leading cause of epilepsy-related mortality, the precise etiology of SUDEP remains unclear. Cardiac arrhythmias, autonomic nervous system dysfunction, and respiratory abnormalities are considered among the most plausible pathophysiological mechanisms [ 9 ]. The lack of a clearly defined etiology has hindered the development of reliable strategies for SUDEP prediction and prevention [ 10 ]. Accumulating evidence indicates that epileptic seizures can exert significant effects on both the function and structure of the heart [ 11 ]. Therefore, evaluation of cardiac parameters provides valuable insights into arrhythmogenic risks and SUDEP mechanisms. QT prolongation is a known risk factor for life-threatening arrhythmias such as Torsades de Pointes [ 12 ], and abnormalities in ventricular repolarization have been increasingly implicated in SUDEP pathophysiology [ 13 ]. Clinical research is consistently showing elevated QT intervals in epilepsy patients compared to healthy controls [ 14 ]. There is evidence that seizures themselves and certain antiepileptic drugs may exacerbate QT prolongation, increasing the risk of SUDEP [ 15 ]. Within this context, QT dispersion has emerged as a noninvasive electrocardiographic (ECG) marker reflecting heterogeneity of ventricular repolarization. QT dispersion, defined as the difference between the maximum and minimum QT intervals across ECG leads, has been shown in multiple studies to correlate with autonomic dysfunction, ventricular arrhythmias, and sudden cardiac death in diverse populations [ 16 , 17 ]. Despite growing interest in the cardiological aspects of epilepsy, data on ventricular repolarization abnormalities—particularly QT dispersion and corrected QT dispersion—remain limited and inconsistent, especially in Middle Eastern populations. Although lead II is traditionally used for QT interval measurement, prior research has demonstrated that the lead showing the maximum QT interval holds the greatest prognostic value, underscoring the importance of comprehensive multi-lead assessment in epilepsy patients [ 18 ]. Many previous studies have relied on single-lead ECGs and one or two QT measurements or have not systematically examined the interaction between cardiac repolarization, demographic variables, epilepsy characteristics, and biochemical factors such as serum electrolytes. The present study addresses these gaps by providing a comprehensive 12-lead electrocardiographic assessment of multiple QT interval parameters, including corrected QT interval (QTc), mean QTc, QT dispersion (QTd), and corrected QT dispersion (QTcd), all in a cohort of hospitalized patients with epilepsy. By integrating detailed ECG analysis with various clinical and epidemiologic characteristics, treatment status, and serum electrolyte profiles in an under-studied population, this study contributes novel regional data to the emerging field of cardio-neurology. These findings may enhance understanding of arrhythmogenic risk in epilepsy and support the development of noninvasive strategies for identifying patients at increased risk of adverse cardiac outcomes, including SUDEP. Methods This retrospective cross-sectional study evaluated QT interval parameters and their clinical associations in patients with epilepsy admitted to Qazvin Bouali-Sina Hospital between March 2022 and March 2024. During the two-year study period, a total of 198 patients with epilepsy were admitted. Of these, records of 104 patients were randomly selected for analysis from the hospital database, a sample size calculated based on previous literature to ensure adequate statistical power and precision [ 17 ]. Eligible participants were those with a confirmed diagnosis of epilepsy established through clinical history, neurological examination, and EEG findings. Patients with known cardiovascular diseases (including congestive heart failure and bundle branch blocks), use of antiarrhythmic or QT-prolonging medications, structural brain lesions such as hemorrhages or tumors, severe electrolyte imbalances, or substance abuse were excluded to minimize confounding factors affecting cardiac repolarization. Dependent variables in this study were QT interval parameters (in milliseconds) including: QT interval: The time interval measured from the onset of the Q wave to the end of the T wave in each ECG lead, representing total ventricular depolarization and repolarization duration. Corrected QT interval (QTc): QT interval adjusted for heart rate using Bazett’s formula (QT/√RR), where RR is the interval between successive R waves, to standardize QT measurements across variable heart rates [ 19 ]. Prolonged QTc interval is defined as QTc > 460 milliseconds (ms) in women and > 440 ms in men, with severe QTc prolongation being > 500 ms [ 20 ]. Mean QTc interval: The average QTc value across all 12 leads. QT dispersion (QTd): The difference between the maximum and minimum QT intervals across all leads, reflecting heterogeneity of myocardial repolarization. Corrected QT dispersion (QTcd): The difference between maximum and minimum QTc intervals, indicating corrected repolarization variability. These continuous dependent variables were analyzed for associations with independent variables of age, sex, epilepsy duration (the time in months elapsed since the first seizure episode), treatment status (antiepileptic drug use within seven days prior to admission), and serum electrolyte levels (mmol/L) including sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), and phosphorus (P) measured via laboratory blood tests. The chosen Standard 12-lead ECGs were all obtained by trained technicians during interictal phases, using a paper speed of 25 mm/s and a voltage of 10 mm/mV. QT intervals were manually measured for each lead from the onset of Q wave to the return of T wave to the isoelectric line, using the small box method, and calculations of QT dispersion and corrected QT parameters were performed accordingly. These ECG parameters along with the relevant demographic data, vital signs, clinical characteristics, and serum electrolyte levels were extracted carefully from medical records into a standardized data collection form. Statistical analyses were performed using SPSS v27. Normality was assessed with the Kolmogorov-Smirnov test. Group comparisons (sex, treatment status) employed independent t-tests or ANOVA, while correlations between continuous variables (age, disease duration, electrolytes) and QT parameters were examined using Pearson’s correlation coefficient. A P-value of less than 0.05 was considered statistically significant. This methodology enables comprehensive evaluation of the interplay between epilepsy characteristics, treatment, electrolyte status, and cardiac repolarization indices, potentially informing risk stratification for arrhythmias and sudden cardiac death in this vulnerable population. Results Among the 104 patients randomly selected for analysis, the mean age of the sample was 36.61 ± 15.70 years with a range of 12 to 83 years. Men comprised most (58.7%, n = 61) of the cohort. The mean duration of epilepsy was 177.39 ± 166.57 months, ranging from 1 to 840 months. Regarding epilepsy characteristics, generalized tonic-clonic seizures were predominant, accounting for 88.5% (n = 92) of cases, with minor representation from myoclonic, tonic and other seizure types. Treatment status indicated that 64.4% (n = 67) were under antiepileptic therapy at admission, while 35.6% (n = 37) were untreated. Analysis of ECG parameters revealed that 28.8% (n = 30) of patients exhibited prolonged QTc intervals in at least one lead, one of whom showed severe QTc prolongation. Normality testing via Kolmogorov-Smirnov test demonstrated that QTd (p < 0.001) and QTc in lead V6 (p = 0.039) deviated from normal distribution, whereas other variables followed a normal distribution. Notably, V6 QTc was normally distributed within each sex subgroup. Table 1 QT parameters of epileptic patients (in seconds) Parameter Number Minimum Maximum Average Std. Deviation QTd 104 0.0200 0.1000 0.0526 0.0021 QTcd 104 0.0208 0.1443 0.0631 0.0266 Mean QTc 104 0.3437 0.4652 0.4049 0.0261 The average QT dispersion was 52 ± 2 ms, with 21.1% (n = 22) of patients having QTd > 65 ms. The average corrected QT dispersion (QTcd) was 63 ± 26 ms, with 51% (n = 53) exceeding 58 ms and 44.2% (n = 46) surpassing 65 ms (Table 1 ). Table 2 Lead I QTc, Mean QTc and QTcd parameters (in seconds) compared by sex Parameter Sex Average Std. Deviation Mean Std. Error P-Value Lead I QTc Male 0.3960 0.0329 0.0043 0.013 Female 0.4128 0.0331 0.0051 QTcd Male 0.0656 0.0285 0.0036 0.259 Female 0.0596 0.0236 0.0036 Mean QTc Male 0.4019 0.0268 0.0034 0.165 Female 0.4092 0.0249 0.0038 Given the non-normal distribution of QT dispersion, the Mann-Whitney U test was applied for this parameter, which found no significant QTd differences between sexes (P > 0.05). Independent samples t-tests were used for the rest of QT parameters that were normally distributed (Table 2 ). QTc values were generally lower in men compared to women across all leads, but a statistically significant difference was found only in lead I (p = 0.013). No significant differences were observed between sexes regarding QTc dispersion or mean QTc (P > 0.05). Regarding treatment status, no significant differences were detected between the 67 treated and 37 untreated participants for QT dispersion, QTc dispersion, or mean QTc values (P > 0.05). Pearson correlation analysis was applied to find correlations between QT parameters with age and disease duration. A statistically significant positive association was demonstrated between age and mean QTc (r = 0.222, P = 0.024). No significant correlations were found between age and QT dispersion or QTc dispersion (P > 0.05). None of the QT parameters showed significant correlations with epilepsy duration (P > 0.05). Table 3 Correlation between QT parameters and serum electrolytes Parameter Sodium Potassium Calcium Magnesium Phosphorus QTd Pearson Correlation -0.056 -0.067 0.080 0.134 0.085 P-value 0.576 0.504 0.437 0.194 0.423 QTcd Pearson Correlation -0.070 -0.104 0.087 0.107 0.063 P-value 0.483 0.297 0.399 0.299 0.548 Mean QTc Pearson Correlation 0.064 -0.230 -0.075 0.002 0.074 P-value 0.523 0.019 0.466 0.984 0.482 Among serum electrolytes (Table 3 ), only potassium levels showed a significant inverse correlation with mean QTc in Pearson correlation analysis (r= -0.230, P = 0.019). No significant correlations were observed between sodium, calcium, magnesium, or phosphorus levels and QT parameters (P > 0.05). Discussion Notably, 28.8% of our cohort exhibited QTc prolongation in at least one lead, a prevalence substantially higher than the 14.2% reported by Kishk et al. [ 21 ]. Our observed average QTd was 52 ± 2 ms, with more than one-fifth of patients demonstrating QTd values higher than 65 ms, a threshold that has been associated with increased risk of malignant ventricular arrhythmias and sudden cardiac death (SCD) [ 22 ]. Average QTcd was 63 ± 26 ms in our study, with nearly half of patients exceeding the 65 ms cutoff, surpassing values reported by Sheng et al. (58.37 ± 15.54 ms) and Dogan et al. (55 ± 18 ms) [ 17 , 18 ]. Collectively, these findings indicate a high prevalence of repolarization instability in our cohort. Applying established mortality risk thresholds based on QTd metrics [ 23 , 24 ], over half of our patients fell into higher-risk categories (QTcd > 58 ms), a prevalence notably higher than previous reports [ 25 , 26 ]. This suggests a potentially elevated arrhythmogenic risk profile and reinforces the relevance of QT abnormalities in epilepsy and SUDEP pathophysiology. The significant positive correlation between age and mean QTc in this cohort indicated modest age-related prolongation of ventricular repolarization. This aligns with prior reports of increased QTc duration with advancing age due to chronic alterations in autonomic regulation, myocardial ion channel function, and cardiac structure [ 27 ]. In contrast, no significant associations were identified between age and QTd or QTcd, suggesting that while global repolarization lengthens with age, repolarization heterogeneity remains relatively preserved. This distinction may be relevant for arrhythmia risk stratification in epilepsy populations. Similar dissociation between QTc prolongation and dispersion has been reported, supporting the notion that QT dispersion is more strongly influenced by pathological stressors rather than aging alone [ 28 ]. Sex differences in QT parameters have been inconsistently studied in epilepsy. Although QT dispersion can be influenced by autonomic tone and sex hormones [ 29 ], our findings revealed no significant difference in QTd between men and women, consistent with prior reports suggesting limited sex influence on repolarization heterogeneity [ 30 ]. Although QTc is typically shorter in men than women across both epileptic and non-epileptic populations [ 31 , 32 ], our data demonstrated a significant sex difference only in lead I. This attenuation of expected sex differences may relate to our participants’ wide age range, as previous findings suggest that sex differences in QTc diminish with advancing age [ 28 , 32 ]. Furthermore, factors including autonomic dysfunction and seizure-related electrophysiological stress may obscure traditional sex-based QTc patterns [ 33 ]. Together, our findings suggest that while sex differences in QTc are well-established in the general population, their expression in epilepsy may be heterogeneous and lead-dependent. In the present cohort, antiepileptic treatment status did not significantly influence QT parameters. This finding challenges the assumption that antiepileptic medication invariably increases QTc intervals and SUDEP risk, corroborating some previous observations [ 15 ]. Prior studies report mixed findings: some antiseizure drugs —particularly sodium channel blockers and agents inhibiting cardiac potassium currents—have been linked to QT prolongation in susceptible individuals [ 34 , 35 ] whereas others demonstrate no clinically significant impact on QT indices [ 36 ]. Our results align with evidence that therapeutic antiseizure medication exposure does not uniformly affect ventricular repolarization in patients without underlying cardiac disease [ 36 ]. Nevertheless, given the complex interaction between epilepsy, autonomic regulation, and arrhythmogenic pathways, continued investigation of epilepsy medication effects on cardiac electrophysiology remains warranted. No significant association between epilepsy duration and QT parameters were found, suggesting that QT abnormalities and arrhythmogenic risks may stem more from epilepsy etiology or intrinsic autonomic dysfunction rather than cumulative disease effects. Similar to aging, studies have indicated that QT alterations in epilepsy are more closely related to seizure burden, peri-ictal autonomic dysregulation, and individual susceptibility rather than disease duration [ 37 , 38 ]. Given the dynamic fluctuation of autonomic imbalance in epilepsy, absence of a linear relationship between illness duration and repolarization indices is plausible. QT dispersion may reflect transient electrophysiological instabilities rather than long-term structural remodeling [ 26 ]. Our serum electrolyte analysis revealed a significant inverse correlation between serum potassium levels within the normal range and mean QTc. This finding is concordant with data linking hypokalemia to longer action potential duration and QTc prolongation in the general population [ 39 , 40 ]. In contrast, no significant correlations were observed between QT parameters and sodium, calcium, magnesium, or phosphorus physiological levels, consistent with evidence that these electrolytes only influence QT dynamics when markedly abnormal [ 40 , 41 ]. These findings highlight the importance of potassium homeostasis in modulating QTc duration and its potential relevance for arrhythmia risk assessment in epilepsy. The researchers faced several limitations during the study course. Absence of a control group restricts definitive conclusions regarding excess cardiovascular risk. The retrospective design and manual QT measurements introduce potential observer bias, and reliance on Bazett’s correction formula may reduce accuracy at extreme heart rates, where alternative correction methods could improve precision [ 42 ]. Unmeasured autonomic and clinical factors may also have confounded results. In conclusion, this study provides a comprehensive evaluation of QT-based repolarization indices in Iranian hospitalized epileptic patients and demonstrates a high prevalence of QTc prolongation and increased QT dispersion, exceeding values reported in prior studies. A substantial proportion of patients met repolarization thresholds associated with increased arrhythmic and mortality risk. QT abnormalities were independent of epilepsy duration and treatment status, suggesting that intrinsic disease-related and autonomic factors play a more prominent role than cumulative exposure or medication effects. The observed age-related QTc prolongation without corresponding increases in dispersion, along with the influence of serum potassium within physiological ranges, provides novel insight into modulators of ventricular repolarization in epilepsy. Collectively, these results reinforce the potential relevance of QT-based ECG markers as accessible, noninvasive tools for identifying patients at elevated arrhythmogenic risk and contribute to the growing evidence linking cardiac repolarization instability to SUDEP pathophysiology. Further prospective, controlled studies are warranted to clarify their prognostic utility and clinical integration. Declarations Acknowledgements: Author Contributions Statement: All authors contributed to the study conception and design. R. M. and A. P. designed the study and supervised the project. A. G. collected the data. A. J. performed the statistical analysis. S. G. drafted the manuscript. All authors reviewed and approved the final version. Sources of Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Ethics statement: This study was approved by the Ethics Committee of Qazvin University of Medical Sciences and was conducted in accordance with the principles of the Declaration of Helsinki. (Reference code: IR.QUMS.REC.1402.136) Data Access Statement: The data supporting the findings of this study are available from the corresponding author upon reasonable request. Competing interest: The authors declare that they have no competing interests. References Beghi E, Giussani G, Nichols E, Abd-Allah F, Abdela J, Abdelalim A, Abraha HN, Adib MG, Agrawal S, Alahdab F, Awasthi A. Global, regional, and national burden of epilepsy, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology. 2019 Apr 1;18(4):357-75. World Health Organization. Epilepsy [Internet]. Geneva: World Health Organization; 2019 [cited 2025 Jan 14]. 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Effects of calcium, magnesium, and potassium concentrations on ventricular repolarization in unselected individuals. Journal of the American College of Cardiology. 2019 Jun 25;73(24):3118-31. Yang Y, Chen C, Duan P, Thapaliya S, Gao L, Dong Y, Yin X, Yang X, Zhang R, Tan R, Hui S. The ECG characteristics of patients with isolated hypomagnesemia. Frontiers in physiology. 2021 Jan 27;11:617374. Andršová I, Hnatkova K, Šišáková M, Toman O, Smetana P, Huster KM, Barthel P, Novotný T, Schmidt G, Malik M. Influence of heart rate correction formulas on QTc interval stability. Scientific Reports. 2021 Jul 12;11(1):14269. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8482625","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":571487014,"identity":"dfd9fa69-f1a3-4371-9a3f-3b0b36152d00","order_by":0,"name":"Amirabbas Ghasemi","email":"","orcid":"","institution":"Qazvin University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Amirabbas","middleName":"","lastName":"Ghasemi","suffix":""},{"id":571487018,"identity":"7e02ddeb-36a2-4f6f-9cd2-f9cacee6d9f0","order_by":1,"name":"Soha Ghasemi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIiWNgGAWjYFACHgYGxgYQA0Sy2YAYjQdI0ZIGZhCrBQTYDoMpvFrk23sPfvy6w86eX+xwA9ONsvN2a9sPA22psYnGpcXgzLlkadkzyYkzZyc2MOecu5287UwiUMuxtNwGXFokcgykJduYEwxuA7Xktt1ONjsA1MLYcBinFvkZOca/Jdvq7e0hWs4lm51/iF8Lw40cM8mPbYcZN0iDtRywM7tBwBaDM2fMrBnbjifOANpyOOdccoLZDaAtCXj8It/eY3zzZ1u1Pf/s9IePc8rs7M3Opz988KHGBrfDgICZB8o4AMSJYJUJeJSDAOMPJI49AcWjYBSMglEwAgEA0axm+goKjGMAAAAASUVORK5CYII=","orcid":"","institution":"Qazvin University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Soha","middleName":"","lastName":"Ghasemi","suffix":""},{"id":571487022,"identity":"8d9fc94a-c198-4175-8c9c-ac347a685179","order_by":2,"name":"Ali Pazoki","email":"","orcid":"","institution":"Qazvin University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Pazoki","suffix":""},{"id":571487024,"identity":"239deac9-035b-4e78-862d-9232994851b7","order_by":3,"name":"Amir Javadi","email":"","orcid":"","institution":"Qazvin University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Amir","middleName":"","lastName":"Javadi","suffix":""},{"id":571487028,"identity":"eeb02470-3506-4971-9c04-4a98654a8f59","order_by":4,"name":"Roghayeh Mehrdel","email":"","orcid":"","institution":"Qazvin University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Roghayeh","middleName":"","lastName":"Mehrdel","suffix":""}],"badges":[],"createdAt":"2025-12-30 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08:58:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":540326,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8482625/v1/70e8a91a-a294-4d52-baae-d411aa2246f0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"QT Interval and QT Dispersion Abnormalities in Hospitalized Patients with Epilepsy: A Multi-Lead Electrocardiographic Study","fulltext":[{"header":"Background","content":"\u003cp\u003eEpilepsy is a chronic brain disorder characterized by a persistent predisposition to generate recurrent unprovoked seizures [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It affects over 50\u0026nbsp;million people worldwide, slightly more prevalent in men than in women, and represents a major cause of neurological morbidity. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] Epilepsy incidence follows a bimodal age distribution, with peaks in early childhood and late adulthood. Overall, it is one of the most common chronic neurological disorders worldwide, imposing substantial medical and socioeconomic burden [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to the International League Against Epilepsy (ILAE), epilepsy etiologies are categorized into six major groups: genetic, structural, metabolic, autoimmune, infectious, and unknown [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The diagnosis of epilepsy is primarily clinical and within a stepwise approach, involving confirming the epileptic nature of the event and defining the epilepsy syndrome by integrating seizure type and pattern, age at onset, electroencephalographic findings, etiology, and associated comorbidities [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeyond its high prevalence, epilepsy is associated with a markedly increased risk of premature mortality. Patients with epilepsy experience a two- to three-fold higher risk of early death compared with the general population [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], a disparity that is particularly pronounced in low- and middle-income countries [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Among epilepsy-related causes, sudden unexpected death in epilepsy (SUDEP) is a leading contributor.\u003c/p\u003e \u003cp\u003eSUDEP is defined as a sudden, unexpected, non-traumatic, and non-drowning death in individuals with epilepsy, occurring in the absence of a toxicological or structural cause identified at autopsy [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The incidence of SUDEP is estimated at approximately 1.16 per 1,000 persons with epilepsy per year. In terms of years of life lost among neurological disorders, SUDEP ranks second only to stroke, largely because it predominantly affects young adults between 20 and 40 years of age [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Despite being a leading cause of epilepsy-related mortality, the precise etiology of SUDEP remains unclear. Cardiac arrhythmias, autonomic nervous system dysfunction, and respiratory abnormalities are considered among the most plausible pathophysiological mechanisms [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The lack of a clearly defined etiology has hindered the development of reliable strategies for SUDEP prediction and prevention [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccumulating evidence indicates that epileptic seizures can exert significant effects on both the function and structure of the heart [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, evaluation of cardiac parameters provides valuable insights into arrhythmogenic risks and SUDEP mechanisms. QT prolongation is a known risk factor for life-threatening arrhythmias such as Torsades de Pointes [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and abnormalities in ventricular repolarization have been increasingly implicated in SUDEP pathophysiology [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Clinical research is consistently showing elevated QT intervals in epilepsy patients compared to healthy controls [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. There is evidence that seizures themselves and certain antiepileptic drugs may exacerbate QT prolongation, increasing the risk of SUDEP [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Within this context, QT dispersion has emerged as a noninvasive electrocardiographic (ECG) marker reflecting heterogeneity of ventricular repolarization. QT dispersion, defined as the difference between the maximum and minimum QT intervals across ECG leads, has been shown in multiple studies to correlate with autonomic dysfunction, ventricular arrhythmias, and sudden cardiac death in diverse populations [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite growing interest in the cardiological aspects of epilepsy, data on ventricular repolarization abnormalities\u0026mdash;particularly QT dispersion and corrected QT dispersion\u0026mdash;remain limited and inconsistent, especially in Middle Eastern populations. Although lead II is traditionally used for QT interval measurement, prior research has demonstrated that the lead showing the maximum QT interval holds the greatest prognostic value, underscoring the importance of comprehensive multi-lead assessment in epilepsy patients [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Many previous studies have relied on single-lead ECGs and one or two QT measurements or have not systematically examined the interaction between cardiac repolarization, demographic variables, epilepsy characteristics, and biochemical factors such as serum electrolytes.\u003c/p\u003e \u003cp\u003eThe present study addresses these gaps by providing a comprehensive 12-lead electrocardiographic assessment of multiple QT interval parameters, including corrected QT interval (QTc), mean QTc, QT dispersion (QTd), and corrected QT dispersion (QTcd), all in a cohort of hospitalized patients with epilepsy. By integrating detailed ECG analysis with various clinical and epidemiologic characteristics, treatment status, and serum electrolyte profiles in an under-studied population, this study contributes novel regional data to the emerging field of cardio-neurology. These findings may enhance understanding of arrhythmogenic risk in epilepsy and support the development of noninvasive strategies for identifying patients at increased risk of adverse cardiac outcomes, including SUDEP.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis retrospective cross-sectional study evaluated QT interval parameters and their clinical associations in patients with epilepsy admitted to Qazvin Bouali-Sina Hospital between March 2022 and March 2024. During the two-year study period, a total of 198 patients with epilepsy were admitted. Of these, records of 104 patients were randomly selected for analysis from the hospital database, a sample size calculated based on previous literature to ensure adequate statistical power and precision [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEligible participants were those with a confirmed diagnosis of epilepsy established through clinical history, neurological examination, and EEG findings. Patients with known cardiovascular diseases (including congestive heart failure and bundle branch blocks), use of antiarrhythmic or QT-prolonging medications, structural brain lesions such as hemorrhages or tumors, severe electrolyte imbalances, or substance abuse were excluded to minimize confounding factors affecting cardiac repolarization.\u003c/p\u003e \u003cp\u003eDependent variables in this study were QT interval parameters (in milliseconds) including:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eQT interval: The time interval measured from the onset of the Q wave to the end of the T wave in each ECG lead, representing total ventricular depolarization and repolarization duration.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCorrected QT interval (QTc): QT interval adjusted for heart rate using Bazett\u0026rsquo;s formula (QT/\u0026radic;RR), where RR is the interval between successive R waves, to standardize QT measurements across variable heart rates [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Prolonged QTc interval is defined as QTc\u0026thinsp;\u0026gt;\u0026thinsp;460 milliseconds (ms) in women and \u0026gt;\u0026thinsp;440 ms in men, with severe QTc prolongation being \u0026gt;\u0026thinsp;500 ms [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMean QTc interval: The average QTc value across all 12 leads.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eQT dispersion (QTd): The difference between the maximum and minimum QT intervals across all leads, reflecting heterogeneity of myocardial repolarization.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCorrected QT dispersion (QTcd): The difference between maximum and minimum QTc intervals, indicating corrected repolarization variability.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThese continuous dependent variables were analyzed for associations with independent variables of age, sex, epilepsy duration (the time in months elapsed since the first seizure episode), treatment status (antiepileptic drug use within seven days prior to admission), and serum electrolyte levels (mmol/L) including sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), and phosphorus (P) measured via laboratory blood tests.\u003c/p\u003e \u003cp\u003eThe chosen Standard 12-lead ECGs were all obtained by trained technicians during interictal phases, using a paper speed of 25 mm/s and a voltage of 10 mm/mV. QT intervals were manually measured for each lead from the onset of Q wave to the return of T wave to the isoelectric line, using the small box method, and calculations of QT dispersion and corrected QT parameters were performed accordingly. These ECG parameters along with the relevant demographic data, vital signs, clinical characteristics, and serum electrolyte levels were extracted carefully from medical records into a standardized data collection form.\u003c/p\u003e \u003cp\u003eStatistical analyses were performed using SPSS v27. Normality was assessed with the Kolmogorov-Smirnov test. Group comparisons (sex, treatment status) employed independent t-tests or ANOVA, while correlations between continuous variables (age, disease duration, electrolytes) and QT parameters were examined using Pearson\u0026rsquo;s correlation coefficient. A P-value of less than 0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eThis methodology enables comprehensive evaluation of the interplay between epilepsy characteristics, treatment, electrolyte status, and cardiac repolarization indices, potentially informing risk stratification for arrhythmias and sudden cardiac death in this vulnerable population.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAmong the 104 patients randomly selected for analysis, the mean age of the sample was 36.61\u0026thinsp;\u0026plusmn;\u0026thinsp;15.70 years with a range of 12 to 83 years. Men comprised most (58.7%, n\u0026thinsp;=\u0026thinsp;61) of the cohort. The mean duration of epilepsy was 177.39\u0026thinsp;\u0026plusmn;\u0026thinsp;166.57 months, ranging from 1 to 840 months.\u003c/p\u003e \u003cp\u003eRegarding epilepsy characteristics, generalized tonic-clonic seizures were predominant, accounting for 88.5% (n\u0026thinsp;=\u0026thinsp;92) of cases, with minor representation from myoclonic, tonic and other seizure types. Treatment status indicated that 64.4% (n\u0026thinsp;=\u0026thinsp;67) were under antiepileptic therapy at admission, while 35.6% (n\u0026thinsp;=\u0026thinsp;37) were untreated.\u003c/p\u003e \u003cp\u003eAnalysis of ECG parameters revealed that 28.8% (n\u0026thinsp;=\u0026thinsp;30) of patients exhibited prolonged QTc intervals in at least one lead, one of whom showed severe QTc prolongation. Normality testing via Kolmogorov-Smirnov test demonstrated that QTd (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and QTc in lead V6 (p\u0026thinsp;=\u0026thinsp;0.039) deviated from normal distribution, whereas other variables followed a normal distribution. Notably, V6 QTc was normally distributed within each sex subgroup.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQT parameters of epileptic patients (in seconds)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStd. Deviation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQTd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQTcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean QTc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.4049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe average QT dispersion was 52\u0026thinsp;\u0026plusmn;\u0026thinsp;2 ms, with 21.1% (n\u0026thinsp;=\u0026thinsp;22) of patients having QTd\u0026thinsp;\u0026gt;\u0026thinsp;65 ms. The average corrected QT dispersion (QTcd) was 63\u0026thinsp;\u0026plusmn;\u0026thinsp;26 ms, with 51% (n\u0026thinsp;=\u0026thinsp;53) exceeding 58 ms and 44.2% (n\u0026thinsp;=\u0026thinsp;46) surpassing 65 ms (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLead I QTc, Mean QTc and QTcd parameters (in seconds) compared by sex\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean Std. Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLead I QTc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQTcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean QTc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eGiven the non-normal distribution of QT dispersion, the Mann-Whitney U test was applied for this parameter, which found no significant QTd differences between sexes (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Independent samples t-tests were used for the rest of QT parameters that were normally distributed (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). QTc values were generally lower in men compared to women across all leads, but a statistically significant difference was found only in lead I (p\u0026thinsp;=\u0026thinsp;0.013). No significant differences were observed between sexes regarding QTc dispersion or mean QTc (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eRegarding treatment status, no significant differences were detected between the 67 treated and 37 untreated participants for QT dispersion, QTc dispersion, or mean QTc values (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003ePearson correlation analysis was applied to find correlations between QT parameters with age and disease duration. A statistically significant positive association was demonstrated between age and mean QTc (r\u0026thinsp;=\u0026thinsp;0.222, P\u0026thinsp;=\u0026thinsp;0.024). No significant correlations were found between age and QT dispersion or QTc dispersion (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). None of the QT parameters showed significant correlations with epilepsy duration (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between QT parameters and serum electrolytes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSodium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePotassium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCalcium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMagnesium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePhosphorus\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQTd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQTcd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.548\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean QTc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePearson Correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.482\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong serum electrolytes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), only potassium levels showed a significant inverse correlation with mean QTc in Pearson correlation analysis (r= -0.230, P\u0026thinsp;=\u0026thinsp;0.019). No significant correlations were observed between sodium, calcium, magnesium, or phosphorus levels and QT parameters (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eNotably, 28.8% of our cohort exhibited QTc prolongation in at least one lead, a prevalence substantially higher than the 14.2% reported by Kishk et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Our observed average QTd was 52\u0026thinsp;\u0026plusmn;\u0026thinsp;2 ms, with more than one-fifth of patients demonstrating QTd values higher than 65 ms, a threshold that has been associated with increased risk of malignant ventricular arrhythmias and sudden cardiac death (SCD) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Average QTcd was 63\u0026thinsp;\u0026plusmn;\u0026thinsp;26 ms in our study, with nearly half of patients exceeding the 65 ms cutoff, surpassing values reported by Sheng et al. (58.37\u0026thinsp;\u0026plusmn;\u0026thinsp;15.54 ms) and Dogan et al. (55\u0026thinsp;\u0026plusmn;\u0026thinsp;18 ms) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCollectively, these findings indicate a high prevalence of repolarization instability in our cohort. Applying established mortality risk thresholds based on QTd metrics [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], over half of our patients fell into higher-risk categories (QTcd\u0026thinsp;\u0026gt;\u0026thinsp;58 ms), a prevalence notably higher than previous reports [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This suggests a potentially elevated arrhythmogenic risk profile and reinforces the relevance of QT abnormalities in epilepsy and SUDEP pathophysiology.\u003c/p\u003e \u003cp\u003eThe significant positive correlation between age and mean QTc in this cohort indicated modest age-related prolongation of ventricular repolarization. This aligns with prior reports of increased QTc duration with advancing age due to chronic alterations in autonomic regulation, myocardial ion channel function, and cardiac structure [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In contrast, no significant associations were identified between age and QTd or QTcd, suggesting that while global repolarization lengthens with age, repolarization heterogeneity remains relatively preserved. This distinction may be relevant for arrhythmia risk stratification in epilepsy populations. Similar dissociation between QTc prolongation and dispersion has been reported, supporting the notion that QT dispersion is more strongly influenced by pathological stressors rather than aging alone [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSex differences in QT parameters have been inconsistently studied in epilepsy. Although QT dispersion can be influenced by autonomic tone and sex hormones [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], our findings revealed no significant difference in QTd between men and women, consistent with prior reports suggesting limited sex influence on repolarization heterogeneity [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough QTc is typically shorter in men than women across both epileptic and non-epileptic populations [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], our data demonstrated a significant sex difference only in lead I. This attenuation of expected sex differences may relate to our participants\u0026rsquo; wide age range, as previous findings suggest that sex differences in QTc diminish with advancing age [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Furthermore, factors including autonomic dysfunction and seizure-related electrophysiological stress may obscure traditional sex-based QTc patterns [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Together, our findings suggest that while sex differences in QTc are well-established in the general population, their expression in epilepsy may be heterogeneous and lead-dependent.\u003c/p\u003e \u003cp\u003eIn the present cohort, antiepileptic treatment status did not significantly influence QT parameters. This finding challenges the assumption that antiepileptic medication invariably increases QTc intervals and SUDEP risk, corroborating some previous observations [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Prior studies report mixed findings: some antiseizure drugs \u0026mdash;particularly sodium channel blockers and agents inhibiting cardiac potassium currents\u0026mdash;have been linked to QT prolongation in susceptible individuals [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] whereas others demonstrate no clinically significant impact on QT indices [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Our results align with evidence that therapeutic antiseizure medication exposure does not uniformly affect ventricular repolarization in patients without underlying cardiac disease [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Nevertheless, given the complex interaction between epilepsy, autonomic regulation, and arrhythmogenic pathways, continued investigation of epilepsy medication effects on cardiac electrophysiology remains warranted.\u003c/p\u003e \u003cp\u003eNo significant association between epilepsy duration and QT parameters were found, suggesting that QT abnormalities and arrhythmogenic risks may stem more from epilepsy etiology or intrinsic autonomic dysfunction rather than cumulative disease effects. Similar to aging, studies have indicated that QT alterations in epilepsy are more closely related to seizure burden, peri-ictal autonomic dysregulation, and individual susceptibility rather than disease duration [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Given the dynamic fluctuation of autonomic imbalance in epilepsy, absence of a linear relationship between illness duration and repolarization indices is plausible. QT dispersion may reflect transient electrophysiological instabilities rather than long-term structural remodeling [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur serum electrolyte analysis revealed a significant inverse correlation between serum potassium levels within the normal range and mean QTc. This finding is concordant with data linking hypokalemia to longer action potential duration and QTc prolongation in the general population [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In contrast, no significant correlations were observed between QT parameters and sodium, calcium, magnesium, or phosphorus physiological levels, consistent with evidence that these electrolytes only influence QT dynamics when markedly abnormal [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. These findings highlight the importance of potassium homeostasis in modulating QTc duration and its potential relevance for arrhythmia risk assessment in epilepsy.\u003c/p\u003e \u003cp\u003eThe researchers faced several limitations during the study course. Absence of a control group restricts definitive conclusions regarding excess cardiovascular risk. The retrospective design and manual QT measurements introduce potential observer bias, and reliance on Bazett\u0026rsquo;s correction formula may reduce accuracy at extreme heart rates, where alternative correction methods could improve precision [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Unmeasured autonomic and clinical factors may also have confounded results.\u003c/p\u003e \u003cp\u003eIn conclusion, this study provides a comprehensive evaluation of QT-based repolarization indices in Iranian hospitalized epileptic patients and demonstrates a high prevalence of QTc prolongation and increased QT dispersion, exceeding values reported in prior studies. A substantial proportion of patients met repolarization thresholds associated with increased arrhythmic and mortality risk. QT abnormalities were independent of epilepsy duration and treatment status, suggesting that intrinsic disease-related and autonomic factors play a more prominent role than cumulative exposure or medication effects. The observed age-related QTc prolongation without corresponding increases in dispersion, along with the influence of serum potassium within physiological ranges, provides novel insight into modulators of ventricular repolarization in epilepsy. Collectively, these results reinforce the potential relevance of QT-based ECG markers as accessible, noninvasive tools for identifying patients at elevated arrhythmogenic risk and contribute to the growing evidence linking cardiac repolarization instability to SUDEP pathophysiology. Further prospective, controlled studies are warranted to clarify their prognostic utility and clinical integration.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor Contributions Statement:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eAll authors contributed to the study conception and design.\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eR. M. and A. P. designed the study and supervised the project. A. G. collected the data. A. J. performed the statistical analysis. S. G. drafted the manuscript. All authors reviewed and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eSources of Funding:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/em\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics statement:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Qazvin University of Medical Sciences and was conducted in accordance with the principles of the Declaration of Helsinki. (Reference code:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eIR.QUMS.REC.1402.136)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Access Statement:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interest:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBeghi E, Giussani G, Nichols E, Abd-Allah F, Abdela J, Abdelalim A, Abraha HN, Adib MG, Agrawal S, Alahdab F, Awasthi A. Global, regional, and national burden of epilepsy, 1990\u0026ndash;2016: a systematic analysis for the Global Burden of Disease Study 2016. 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The ECG characteristics of patients with isolated hypomagnesemia. Frontiers in physiology. 2021 Jan 27;11:617374.\u003c/li\u003e\n \u003cli\u003eAndr\u0026scaron;ov\u0026aacute; I, Hnatkova K, \u0026Scaron;i\u0026scaron;\u0026aacute;kov\u0026aacute; M, Toman O, Smetana P, Huster KM, Barthel P, Novotn\u0026yacute; T, Schmidt G, Malik M. Influence of heart rate correction formulas on QTc interval stability. Scientific Reports. 2021 Jul 12;11(1):14269.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Epilepsy, QT Interval, QT dispersion, Ventricular Repolarization, Electrocardiography, Sudden Unexpected Death in Epilepsy (SUDEP)","lastPublishedDoi":"10.21203/rs.3.rs-8482625/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8482625/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEpilepsy is associated with increased premature mortality, including sudden unexpected death in epilepsy (SUDEP), in which cardiac arrhythmias are implicated. Ventricular repolarization abnormalities, particularly QT prolongation and QT dispersion, may contribute to arrhythmogenic risk. however, data remain limited and inconsistent, especially in hospitalized Middle Eastern populations.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective cross-sectional study evaluated QT parameters in 104 hospitalized epilepsy patients admitted between March 2022 and March 2024. Standard 12-lead interictal ECGs were analyzed to measure QT, corrected QT (QTc), mean QTc, QT dispersion (QTd), and corrected QT dispersion (QTcd). Associations between QT parameters and age, sex, epilepsy duration, treatment status, and serum electrolytes were examined.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eQTc prolongation was observed in 28.8% of patients. QTd and QTcd were 52\u0026thinsp;\u0026plusmn;\u0026thinsp;2 and 63\u0026thinsp;\u0026plusmn;\u0026thinsp;26 milliseconds (ms) on average. QTd and QTcd exceeding 65 ms were observed in 21.1% and 44.2% of patients respectively. lead I QTc was significantly lower in men (p\u0026thinsp;=\u0026thinsp;0.013). No significant differences in QT parameters were observed by epilepsy duration or treatment status. Age showed a significant positive correlation solely with mean QTc (r\u0026thinsp;=\u0026thinsp;0.222, P\u0026thinsp;=\u0026thinsp;0.024). Among serum electrolytes, only potassium demonstrated a significant inverse correlation with mean QTc (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.230, P\u0026thinsp;=\u0026thinsp;0.019).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHigh frequencies of increased QT interval, QT dispersion, and arrhythmic and mortality risks were demonstrated in our population. QTc prolongation correlated with female sex (lead-dependent), advanced age and lower physiological levels of potassium, which provides insight into modulators of ventricular repolarization in epilepsy and role of QT markers in arrhythmia risk stratification and SUDEP pathophysiology.\u003c/p\u003e","manuscriptTitle":"QT Interval and QT Dispersion Abnormalities in Hospitalized Patients with Epilepsy: A Multi-Lead Electrocardiographic Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 11:09:24","doi":"10.21203/rs.3.rs-8482625/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"393de912-95bc-4382-acc9-e9ed086041e4","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-05T08:57:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-12 11:09:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8482625","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8482625","identity":"rs-8482625","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}