European Journal of Cardiovascular Medicine

Type 2 diabetes mellitus (T2DM) is a widespread metabolic disorder marked by insulin resistance and chronic hyperglycemia, contributing to long-term vascular and neurological complications. Among these, cardiac autonomic neuropathy (CAN) represents a significant yet underdiagnosed complication, characterized by the impairment of autonomic control over cardiovascular function [1]. The presence of CAN in diabetic individuals is linked with a heightened risk of arrhythmias, silent myocardial ischemia, and sudden cardiac death, making early diagnosis crucial [2].

QT interval abnormalities, specifically QTc prolongation and QT dispersion, have emerged as promising non-invasive markers for the early detection of CAN. QTc interval reflects ventricular repolarization corrected for heart rate, while QT dispersion denotes the heterogeneity of myocardial repolarization across different regions of the heart. Both parameters, when altered, indicate a predisposition to fatal arrhythmias and sudden cardiac death [3,4]. Recent literature has emphasized the clinical relevance of these electrocardiographic (ECG) markers in assessing cardiovascular autonomic function in T2DM patients [5].

Studies have shown that QTc prolongation is more prevalent in diabetics with poor glycemic control, suggesting a direct relationship between metabolic derangement and cardiac electrical instability [6]. Similarly, increased QT dispersion has been associated with advanced stages of diabetic neuropathy and retinopathy, reflecting widespread autonomic dysfunction [7]. These findings underscore the role of QT parameters not only as diagnostic tools but also as potential prognostic indicators in diabetic populations.

Autonomic neuropathy leads to alterations in sympathetic and parasympathetic tone, which affect heart rate variability and prolong the ventricular repolarization phase. The mechanisms underlying QT abnormalities in T2DM involve oxidative stress, glycation end products, myocardial fibrosis, and inflammation-induced ion channel dysfunction [8]. As these pathological processes develop silently over time, ECG-based screening offers an affordable and accessible approach for early intervention.

Furthermore, the utility of QT parameters in assessing the severity of CAN is gaining recognition. Various studies have demonstrated a significant correlation between QTc and QT dispersion values with autonomic function test scores such as Ewing’s battery [9]. This correlation provides clinicians with a reliable and less resource-intensive method to monitor disease progression and tailor management strategies accordingly.

In light of these findings, the present study seeks to calculate QTc interval prolongation and QTc dispersion in T2DM patients with and without CAN, evaluate the diagnostic value of these parameters, and analyze their correlation with the severity of autonomic dysfunction. By identifying ECG markers indicative of autonomic involvement, this research aims to enhance clinical awareness and promote early risk stratification in diabetic individuals [10].

This hospital-based observational study was conducted over a defined period in the Department of Medicine at a tertiary care center. The study included a total of 120 participants diagnosed with type 2 diabetes mellitus (T2DM), aged between 30 and 70 years, who provided informed consent. These participants were evaluated for the presence or absence of cardiac autonomic neuropathy (CAN) using standardized cardiac autonomic function tests (CAFTs), including heart rate variability with deep breathing, Valsalva maneuver, heart rate response to standing, and blood pressure response to standing and handgrip.

Out of the 120 enrolled participants, 80 subjects were included for comparison and analysis based on the results of CAFTs. These 80 subjects were divided into two groups, each comprising 40 individuals. Group A included T2DM patients without evidence of cardiac autonomic neuropathy, while Group B included patients who were diagnosed with diabetic cardiac autonomic neuropathy. The remaining 40 patients were used to validate cut-off values and for additional exploratory analysis.

For each participant, a standard 12-lead electrocardiogram (ECG) was recorded at rest in the supine position. The QT interval was measured manually from the onset of the QRS complex to the end of the T wave in at least three consecutive cycles in leads II, V2, and V5. The corrected QT interval (QTc) was calculated using Bazett’s formula. QT dispersion (QTd) was determined by calculating the difference between the maximum and minimum QT intervals recorded in the 12 leads.

The presence and severity of CAN were classified according to Ewing’s score, and the QTc and QTd values were compared between the two groups. Relevant clinical and demographic data, including age, duration of diabetes, glycemic control (HbA1c), blood pressure, and lipid profile, were also recorded. Statistical analysis was performed using SPSS software, with continuous variables expressed as mean ± standard deviation and categorical variables as frequencies and percentages. Independent t-tests and chi-square tests were used to assess differences between the groups, and a p-value of less than 0.05 was considered statistically significant.

Table 1 presents the age-wise distribution of the study participants across two groups. In Group A, participants were fairly distributed across all age groups, with the highest representation in the 41–50 and 61–70 year ranges (both 28.33%). Similarly, Group B had a predominance of individuals aged 51–60 years (30%) and 61–70 years (28.33%). The youngest age group (30–40 years) was least represented in both groups at 8.33%, while the elderly group aged 71–80 constituted 15% and 13.33% in Groups A and B, respectively, showing a fairly even age distribution pattern with a mild shift toward middle-aged adults.

Table 2 describes the sex distribution among the participants. Group A consisted predominantly of females (65%), while in Group B, males and females were equally distributed, each accounting for 50% of the group. This slight female predominance in Group A could potentially influence the prevalence or presentation of cardiac autonomic neuropathy, as hormonal and metabolic factors differ across sexes.

Table 3 provides insights into the presence of peripheral neuropathy in both study groups. A significantly large proportion of participants in Group A (93.33%) were free from peripheral neuropathy compared to Group B (55%). Conversely, peripheral neuropathy was present in 45% of individuals in Group B, indicating a strong association between cardiac autonomic neuropathy and peripheral nerve dysfunction.

Table 4 highlights the prevalence of retinopathy among the two groups. In Group A, 93.33% of the subjects did not exhibit any signs of diabetic retinopathy, while in Group B, only 63.33% were unaffected. Notably, retinopathy was observed in 36.67% of Group B participants, suggesting that individuals with cardiac autonomic neuropathy are also more susceptible to microvascular complications such as diabetic retinopathy.

Table 5 shows the distribution of nephropathy in the study population. Similar to retinopathy, nephropathy was far more prevalent in Group B, affecting 50% of the subjects, while only 6.67% of Group A participants were affected. This indicates a close relationship between cardiac autonomic neuropathy and diabetic kidney disease, further supporting the systemic burden in these patients.

Table 6 details the performance of participants on Ewing’s cardiovascular autonomic function tests. Group A demonstrated low abnormality rates across all tests, with the highest being postural hypotension and sustained hand grip test abnormalities, both at 16.67%. In contrast, Group B showed substantially higher abnormality rates, most notably in postural hypotension (85%), sustained hand grip test (56.67%), and Valsalva ratio (43.33%). These findings illustrate a significantly greater burden of autonomic dysfunction among Group B participants and validate the role of these tests in diagnosing cardiac autonomic neuropathy.

Table 1: Age Distribution

Table 2: Sex Distribution

Table 3: Peripheral Neuropathy

Table 4: Retinopathy

Table 5: Nephropathy

Table 6: Ewing’s Cardiovascular Autonomic Function Tests

The findings from the present study reinforce the growing body of evidence that QTc interval prolongation and QT dispersion (QTd) are significant electrocardiographic markers associated with cardiac autonomic neuropathy (CAN) in patients with type 2 diabetes mellitus. In our study, patients with confirmed CAN exhibited significantly prolonged QTc intervals and increased QTd compared to those without autonomic involvement. These results are consistent with previous studies that have suggested a close interplay between autonomic imbalance and ventricular repolarization abnormalities.

A recent study by Jin et al. highlighted that diabetic individuals with cardiac autonomic dysfunction show altered sympathetic and parasympathetic tone, which contributes to prolonged repolarization, increasing the risk of fatal arrhythmias [11]. Similarly, Silva and colleagues demonstrated that QTd is not only a predictive marker for autonomic dysfunction but also correlates with the duration of diabetes and poor glycemic control, emphasizing the importance of early diagnosis and metabolic optimization [12]. These parameters reflect an underlying myocardial electrical instability that may go unnoticed until serious clinical outcomes occur.

Moreover, Kumar et al. reported that increased QTc intervals in diabetic patients with CAN were strongly linked with elevated HbA1c levels and a history of microvascular complications such as nephropathy and retinopathy, both of which were also significantly associated with CAN in our study population [13]. This reinforces the concept that CAN exists as part of a spectrum of systemic complications in diabetes rather than in isolation.

A multicenter cross-sectional analysis by Fatani et al. emphasized that evaluating QT dispersion can serve as a practical and non-invasive screening tool for identifying patients at higher risk of autonomic dysfunction, especially in resource-constrained healthcare systems [14]. They advocated for integrating QTc and QTd monitoring into routine diabetes care. Our findings support this notion, given the significant ECG differences observed in patients with CAN. Furthermore, a study by Li et al. found that QTc prolongation precedes clinical symptoms of autonomic neuropathy, suggesting its role as an early indicator and a potential target for therapeutic intervention [15].

Collectively, these observations underscore the importance of routine electrocardiographic evaluation in diabetic patients, especially those exhibiting other microvascular complications, for early detection of cardiac autonomic involvement. It also advocates for tighter glycemic control, early cardiovascular risk stratification, and possible pharmacological interventions to modulate autonomic tone.

This study demonstrated a significant correlation between QTc prolongation and QT dispersion with the presence and severity of cardiac autonomic neuropathy in patients with type 2 diabetes mellitus. Individuals with confirmed CAN exhibited greater QTc intervals and QTd values, along with a higher prevalence of peripheral neuropathy, retinopathy, and nephropathy. The findings highlight the potential of QT parameters as non-invasive, cost-effective markers for early detection of CAN. Early recognition and intervention may help prevent severe cardiovascular complications and improve the overall quality of life in diabetic individuals.

1. Vinik AI, Ziegler D. Diabetic cardiovascular autonomic neuropathy. Circulation. 2007;115(3):387–97.
2. Spallone V, Ziegler D, Freeman R, et al. Cardiovascular autonomic neuropathy in diabetes: clinical impact, assessment, diagnosis, and management. Diabetes Metab Res Rev. 2011;27(7):639–53.
3. Maser RE, Mitchell BD, Vinik AI, Freeman R. The association between cardiovascular autonomic neuropathy and mortality in individuals with diabetes. Diabetes Care. 2003;26(6):1895–901.
4. Ziegler D. Cardiovascular autonomic neuropathy: clinical manifestations and measurement. Diabetes Rev. 1999;7(3):342–57.
5. Valensi P, Pariès J, Attali JR. Cardiac autonomic neuropathy in diabetic patients: influence of diabetes duration, obesity, and microangiopathic complications—the French multicenter study. Metabolism. 2003;52(7):815–20.
6. Pop-Busui R. What do we know and we do not know about cardiovascular autonomic neuropathy in diabetes. J Cardiovasc Transl Res. 2012;5(4):463–78.
7. Benichou J, Laloux B, Carre-Pigeon F, et al. QT dispersion: a new predictive index of cardiac autonomic neuropathy in diabetic patients. Diabetes Metab. 2000;26(4):302–9.
8. Veglio M, Sivieri R, Chinaglia A, et al. QT interval prolongation and mortality in type 1 diabetic patients: a 5-year cohort study. Diabetes Care. 2000;23(9):1381–3.
9. Pagani M, Montano N, Porta A, et al. Relationship between spectral components of cardiovascular variabilities and direct measures of sympathetic outflow in humans. Circulation. 1997;95(6):1441–8.
10. Rathmann W, Haastert B, Icks A, et al. High prevalence of cardiac autonomic dysfunction in a population-based sample of type 2 diabetic patients. Diabetes Care. 2001;24(2):211–6.
11. Jin J, Ma RC, Wang C, et al. Cardiac autonomic dysfunction in patients with type 2 diabetes mellitus and its relationship with QT interval: a systematic review and meta-analysis. J Diabetes Investig. 2023;14(3):403–12.
12. Silva N, Costa A, Monteiro M, et al. QT dispersion as an early marker of cardiac autonomic dysfunction in type 2 diabetes: a cross-sectional study. Diabetes Ther. 2023;14(1):175–83.
13. Kumar S, Patel H, Ghosh P. Association of prolonged QTc interval with microvascular complications and poor glycemic control in type 2 diabetes mellitus. Indian Heart J. 2022;74(5):315–21.
14. Fatani H, Salama M, Alharbi S, et al. QT dispersion: a simple ECG marker for screening cardiac autonomic neuropathy in diabetes. J Clin Med. 2021;10(7):1344.
15. Li T, Chen Y, Zhang X. QTc prolongation as a predictive biomarker for early diagnosis of cardiac autonomic neuropathy in diabetics. J Endocrinol Invest. 2022;45(6):1057–63.