Heart rate‐corrected QT interval: A novel diagnostic biomarker for diabetic peripheral neuropathy

Abstract Aims/Introduction To explore the relationship between heart rate‐corrected QT (QTc) interval and diabetic peripheral neuropathy (DPN), and whether QTc interval has diagnostic utility for DPN beyond nerve conduction velocity. Materials and Methods A total of 965 patients with diabetes, including 473 patients with DPN and 492 patients without DPN, underwent standard 12‐lead electrocardiography and detailed assessments of peripheral neuropathy. Results Patients with DPN had longer QTc intervals than those without. Among participants, from the first to fourth quartile of QTc interval, the proportion of patients with DPN appreciably increased and the nerve conduction velocity obviously decreased (P for trend <0.001). The univariate and multivariate analyses showed that prolonged QTc interval was closely associated with increased risk of DPN (univariable odds ratio 1.112, 95% confidence interval 1.097–1.127, P < 0.001; multivariable odds ratio 1.118, 95% confidence interval 1.099–1.137, P < 0.001). Receiver operating characteristic analysis for the diagnosis of DPN showed a greater area under the curve for QTc interval of 0.894 than the median nerve motor conduction velocity of 0.691, median nerve sensory conduction velocity of 0.664 and peroneal nerve motor conduction velocity of 0.692. The optimal cut‐off point of QTc interval for DPN was 428.5 ms with sensitivity of 0.715 and specificity of 0.920 (P < 0.001). The combination of QTc interval and nerve conduction testing increased the area under the curve for the diagnosis of DPN (from 0.736 to 0.916; P < 0.001). Conclusions QTc interval with 428.5 ms has more reliable diagnostic utility for DPN than nerve conduction velocity, and prolonged QTc interval is closely associated with an increased risk of DPN.


INTRODUCTION
Diabetic peripheral neuropathy (DPN) is a common chronic complication of both type 1 and type 2 diabetes, and approximately 50% patients with diabetes develop DPN 1 . The main symptoms of DPN are distressing neuropathic pain and paresthesia, characterized by superficial burning pain and numbness in the lower limbs 2 . However, DPN might be asymptomatic in up to 50% of patients, leading to more difficulties in the timely diagnosis and effective treatment, and contributing to a higher risk of diabetic foot ulceration and non-traumatic lower limb amputation 3 . It is estimated that patients with DPN with or without limb ulceration have a high rehospitalization rate and mortality 3 .
The QT interval represents the duration of electrical depolarization and repolarization of the ventricular. As the QT interval is correlated with the heart rate; the higher heart rate, the shorter QT interval and vice versa, heart rate-corrected QT (QTc) interval is usually used clinically 4 . Prolongation of the QTc interval becomes a risk factor for malignant arrhythmia and sudden cardiac death 5 . In addition, it has been shown that the QTc interval in patients with diabetes is longer than those without diabetes 6 . Prolonged QTc interval, even within the normal reference range, has been shown to be associated with diabetic complications and metabolic diseases, including diabetic cardiac autonomic neuropathy 7 , diabetic nephropathy 8 , diabetic kidney disease 9 , insulin sensitivity 10 and non-alcoholic fatty liver disease 11 . Furthermore, prolonged QTc interval was found to be a biomarker for worse prognosis in diabetes patients 12 .
However, the role of QTc interval in the pathogenesis of DPN remains totally unclear. The present study explored that the relationship between QTc interval and DPN, and whether QTc interval has diagnostic utility for DPN beyond nerve conduction velocity.

Study design and participants
The present observational study was carried out on total of 965 patients (473 patients with DPN, 492 patients without DPN) in the endocrinology department of the Nanjing First Hospital between January 2020 and December 2020. The inclusion criteria were: (i) diagnosis of diabetes was based on the American Diabetes Association recommendation 13 ; (ii) cardiac sinus rhythm; (iii) normal heart rate (60-100 b.p.m.); (iv) normal vital sign; (v) underwent standard resting 12-lead electrocardiograph; and (vi) underwent nerve conduction testing. The exclusion criteria were: (i) taking medications that affect QTc intervals, such as antiarrhythmic drugs, triangular antipsychotic drugs, and aand b-receptor blockers; (ii) arrhythmia diseases, such as congenital long QT syndrome, tachycardia, bradycardia, pacemaker rhythms, atrial fibrillation, atrial flutter and cardiac conduction; (iii) other diseases affecting the heart rhythm and QT interval, such as hyperthyroidism; (iv) acute diabetic complications, such as diabetic ketoacidosis, hyperglycemic hyperosmolar state and hypoglycemia; and (v) other endocrine disorders might have effect on glucose metabolism, such as polycystic ovary syndrome.
The study protocol was approved by the ethics committee of the Nanjing First Hospital. Written informed consent was obtained from all participants.

Basic data collection and laboratory examination
Information about demographic characteristics, medical history, physical examinations including height, weight, waist circumference and hip circumference, and blood pressure of all participants was recorded by diabetologists. Body mass index was calculated by weight divided by the square of height (kg/m 2 ) and waist-to-hip ratio (WHR) was calculated by the ratio of waist to hip circumference. After fasting overnight, blood samples were collected on fasting and 2-h postprandial for laboratory parameters. The fasting plasma glucose (FPG) was assessed by glucose oxidase method using an automatic biochemistry analyzer (HITACHI-7180, Tokyo, Japan). Fasting Cpeptide and C-peptide 2-h post prandial (2-h C-peptide) were determined using automatic electrochemiluminescence immunoassay (Cobas E601; Roche, Basel, Switzerland). Glycosylated hemoglobinA1c (HbA1c) was measured by high-pressure liquid chromatography (D-10; Bio-Rad, Hercules, CA, USA). Alanine transaminase, aspartate transaminase, blood urea nitrogen, creatinine, uric acid (UA), total cholesterol, triglyceride, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol level were assessed by enzymatic colorimetric assay using an automatic biochemistry analyzer (HITACHI-7180, Tokyo, Japan). Midstream urine samples were obtained in the morning for urine microalbumin-to-creatinine ratio (UACR).

QTc interval analysis
Resting electrocardiograms (ECGs) were recorded with a standard 12-lead electrocardiograph (FX-8322, Nippon Fukuda Electronics Co, Tokyo, Japan) at a paper speed of 25 mm/s after standardization (10 mm = 1 mV) with filter settings. ECGs were analyzed with computerized automated analysis software imbedded in the electrocardiograph and then were confirmed by a trained cardiologist. The QT, defined as the time from the beginning of the QRS complex wave to the end of the T wave on ECG, and QTc interval was calculated by Bazett's formula: QTc interval = QT interval / square root of the RR interval (QTc = QT / [RR]1 / 2).

DPN assessment
Participants underwent neurological assessment according to the American Diabetes Association recommendations 13,14 . The diagnostic criteria for DPN are: (i) definite history of diabetes; (ii) neuropathy that occurs at or after the diagnosis of diabetes; (iii) clinical symptoms (such as burning pain, electric shock-like pain, sharp pain, soreness, cold pain, induced pain, itching, numbness and abnormal position perception) and one abnormality among the following five examinations: ankle reflexes, pinprick sensation, vibration perception, temperature perception and pressure perception (or two abnormalities among the of five examinations in diabetic patients without clinical symptoms); and (iv) exclusion of neuropathy of other causes, including neurotoxic drugs (such as chemotherapy drugs), cervical and lumbar diseases (compression, stenosis, degeneration), cerebral infarction, chronic inflammatory demyelinating neuropathy, hereditary neuropathy and vasculitis, infections (such as acquired immune deficiency syndrome) and nerve damage caused by metabolic toxins caused by renal insufficiency. The detailed ways of assessing ankle reflexes, pinprick sensation, vibration perception, temperature perception and pressure perception are described in Appendix S1.
Diabetic patients were divided into two group: (i) with DPN; and (ii) without DPN.
Nerve conduction testing was carried out with surface electrodes and electromyographic digital equipment (E3, Yuanxiang Medical Ltd, Hangzhou, China). The patients were relaxed and kept in the supine position with limb skin temperatures of 32-35°C. Bilateral measurements of nerves were carried out, including motor nerve conduction velocity (MNCV) of the median nerve, sensory nerve conduction velocity (SNCV) of the median nerve and MNCV of the peroneal nerve. Median nerve MNCV was recorded at the abductor pollicis brevis with stimulations at the radial side of the wrist and the radial artery of the cubital fossa. The median nerve SNCV was recorded at the root of the middle finger with stimulation at the radial side of the wrist. Peroneal nerve MNCV was recorded at the extensor toe brevis with stimulations at the ankle and the proximal to the fibula. Nerve conduction velocity was assessed by computerized automated analysis software imbedded in the electromyographic digital equipment. The specific normal values are shown in Appendix S1.

Statistical analysis
Statistical analyses were carried out using the SPSS statistical software 26.0 (IBM Corp., Armonk, NY, USA). In all cases, Pvalues <0.05 (P < 0.05) were considered statistically significant. Data were tested for normality using the Shapiro-Wilk test. The meanstandard deviation, n (%) and median (25th and 75th interquartile range) presented continuous variables with normal distributions, categorical variables and continuous variables with skewed distributions, respectively. The differences were compared by the independent t-test, Mann-Whitney test and the v 2 -test. Binary logistic regression analysis was carried out to compare the independent influence of the QTc interval and other metabolic parameters on the DPN, and the odds ratio (OR) and 95% confidence interval (95% CI) were determined. Receiver operating characteristic (ROC) analysis and the area under curve (AUC) were used to assess the accuracy and discriminatory ability of QTc in diagnosis of DPN.

DPN and neuropathy parameters at different QTc intervals
The neuropathy characteristics of four subgroups according to the QTc interval quartiles are shown in Table 2 and Figure 1. Among participants, from the first to fourth quartile of QTc interval, the proportion of patients with DPN increased (P for trend <0.001); inversely, the median nerve MNCV (P for trend <0.001), median nerve SNCV (P for trend <0.001) and peroneal nerve MNCV (P for trend = 0.002) significantly decreased when the QTc interval quartiles increased.

DISCUSSION
The major findings of the present study are that QTc interval is strongly associated with DPN, and the diagnostic performance of QTc interval in this study was superior to nerve conduction testing. The optimal cut-off point of QTc interval for Guidelines for the diagnosis of DPN require the presence of symptoms and signs, and nerve conduction testing or small fiber function assessment if patients are asymptomatic 1 . Data are expressed as mean -SD, n (%) and median (25th and 75th interquartile). P-values were determined by the independent t-test, Mann-Whitney test and the v 2 -test.   However, nerve conduction testing is costly, time-consuming and highly technical 15 . In the present study, nerve conduction testing was relatively crude in diagnosing DPN due to its lower AUC. In fact, this is consistent with clinical nerve conduction velocity only detecting large fiber neuropathy 16 . In contrast, we detected too few peripheral nerves, especially only a kind of sensory conduction velocity, which might weaken the diagnostic effect of nerve conduction testing on DPN. With regard to the relationship between age, diabetes duration, UACR and DPN, the Diabetes Control and Complications Trial also reported that older age, longer diabetes duration, macroalbuminuria and sustained albuminuria are most significant risk factors for DPN 17 . Therefore, these risk factors contribute to identifying early DPN. Recently, researchers have tried to discover some more reliable biological markers for DPN. Skin biopsy for intraepidermal nerve fiber density and corneal confocal microscopy have their own advantages, but the biggest common disadvantage is hard to carry out in various clinical sites 18,19 . The gold biomarker should be accurate, efficient, repeatable, economical, painless, as well as practical and practicable to apply in routine hospitals. To date, researchers have not proposed the ideal biomarker for DPN. ECG is a rapid and convenient technique, and QTc interval in multiple clinical trials has been shown to play a key role in the assessment of a variety of metabolic disease, including diabetic complications 7 , diabetic ketoacidosis 20 and non-alcoholic fatty liver 21 . Subbalakshmi et al. 22 found that only female diabetes patients with somatic neuropathy had prolonger QTc intervals compared with healthy controls. The present study expanded the number of participants, adjusted for sex interference, and extended their understanding of the association of QTc interval and DPN to broader diabetes patients. Previous studies have shown that a QTc interval of 440 ms or longer was a risk factor for all-cause and cardiovascular mortality in patients with type 2 diabetes and foot ulcers 23,24 . It has been shown that a QTc interval <440 ms is considered within the normal range 25 . Hashimoto et al. 9 reported that a QTc interval of 418 ms was a biomarker for progression of albuminuria. Thus, prolongation of the QTc interval, even within the normal range, could be a biomarker for diseases. In this regard, the diagnosis of a QTc interval of 428.5 ms in the present study was quite clear. Additionally, the QTc interval could boost the sensitivity of nerve conduction testing, meaning the combination of these two measures could further improve diagnostic accuracy.
The mechanism underlying the relationship between QTc interval and DPN is not totally elucidated. Multiple studies have also shown that the QTc interval is associated with age 26 , sex 27 , hyperglycemia 28 and diabetes duration 29 , which are the risk factors for DPN in the present study. Another potential mechanism that contributes to the association between the QTc interval and DPN is ion channel. Hyperglycemic concentration  enhances spontaneous sarcoplasmic reticulum Ca2 + release events, leading to cardiac mechanical dysfunction and arrhythmias 30 . Finally, the sympathetic nervous excitability has been associated with QTc interval 31 . In a prior study, among 47 diabetes patients, the presence of peripheral sympathetic adrenergic fibers underwent early alterations, even when there are no clinical symptoms of neuropathy 32 . It is regrettable that we did not assess the sympathetic nervous activity. The present study still had several limitations to improve. First, this was a single-site study and the sample size was relatively small. Second, the majority of DPN was caused by type 2 diabetes in our study; that is, the diagnostic utility between different types of diabetes could not be reflected. Third, as the present study was a cross-sectional study, the cause-effect relationship between QTc interval and DPN cannot be fully proved. Finally, in current clinical practice, the diagnosis of DPN mainly depends on symptoms and signs. It is regrettable we did not separately analyze the diagnostic performance of each symptom and sign.
QTc interval might be a novel biomarker in DPN, and prolonged QTc interval has more reliable diagnostic utility for DPN compared with nerve conduction velocity, which could be assessed easily in various medical facilities. Further longitudinal studies are required to research the relationship between QTc interval and the severity and prognosis of DPN.