Severe Hypoglycemia and Incidence of QT Interval Prolongation Among Adults With Type 2 Diabetes

Abstract

Context

There is a paucity of large-scale epidemiological studies on the link between severe hypoglycemia (SH) and corrected QT (QTc) interval prolongation in type 2 diabetes (T2DM).

Objective

To evaluate the association of SH with QTc prolongation in adults with T2DM.

Methods

Prospective cohort analysis of participants enrolled in the ACCORD (Action to Control Cardiovascular Risk in Diabetes) study without QTc prolongation at baseline. SH was assessed over a 24-month period. Incident QTc prolongation was ascertained using follow-up electrocardiograms. Modified Poisson regression was used to generate the risk ratio (RR) and 95% CI for QTc prolongation.

Results

Among 8277 participants (mean age 62.6 years [SD 6.5], 38.7% women, 62.8% White), 324 had ≥1 SH episode (3.9%). Over a median of 5 years, 517 individuals developed QTc prolongation (6.3%). Participants with SH had a 66% higher risk of QTc prolongation (RR 1.66, 95% CI 1.16-2.38). The incidence of QTc prolongation was 10.3% (27/261) and 14.3% (9/63) for participants with 1 and ≥2 SH, respectively. Compared with no SH, RRs for patients with 1 and ≥2 SH episodes were 1.57 (95% CI 1.04-2.39) and 2.01 (95% CI 1.07-3.78), respectively. Age modified the association of SH with QTc prolongation (P_Interaction = .008). The association remained significant among younger participants (<61.9 years [median age]: RR 2.63, 95% CI 1.49-4.64), but was nonsignificant among older participants (≥61.9 years: RR 1.37, 95% CI 0.87-2.17).

Conclusion

In a large population with T2DM, SH was associated with an increased risk of QTc prolongation independently of other risk factors such as cardiac autonomic neuropathy. The association was strongest among younger participants.

Hypoglycemia remains a key limiting factor in optimal glycemic control of diabetes mellitus (diabetes) (1). Among individuals with type 2 diabetes, severe hypoglycemia has been found to be associated with higher risks of all-cause and cardiovascular mortality (2-5). The exact mechanisms for this association are unknown, but may include sympathoadrenal activation, alterations in cardiac repolarization, and severe ventricular tachyarrhythmias (6-8). The heart rate (HR) corrected QT (QTc) interval is a measure of myocardial repolarization that is positively associated with a higher risk of fatal ventricular arrhythmias (9, 10). Prior investigations have suggested a link between severe hypoglycemia and QTc interval prolongation (6, 11-13). However, there is a paucity of large-scale epidemiological data on the association between severe hypoglycemia and incident QT interval prolongation (as assessed by the QTc interval) among people with type 2 diabetes.

We evaluated the association of severe hypoglycemia with risk of QT prolongation using data from the ACCORD (Action to Control Cardiovascular Risk in Diabetes) study—a large and diverse cohort of adults with type 2 diabetes. We hypothesized that severe hypoglycemia would be associated with an increased risk of incident QTc prolongation.

Materials and Methods

Study Design

This report followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for observational studies (14). We conducted a prospective cohort analysis of the ACCORD study. ACCORD was initially designed as double 2-by-2 factorial clinical trial which enrolled 10 251 adults with type 2 diabetes from 77 clinical centers in the United States and Canada. The ACCORD participants were adults with type 2 diabetes, aged 40-79 years old (with prevalent cardiovascular disease [CVD]) or 55-79 years old (with significant albuminuria, left ventricular hypertrophy, atherosclerosis, or at least 2 cardiovascular risk factors) (15). The participants were randomly allocated to either an intensive glycemic lowering arm aiming for hemoglobin A_1C (HbA_1C) <6% or a standard glycemic treatment arm with an HbA_1C goal of 7.0% to 7.9%. Participants were also assigned to distinct blood pressure (BP) or lipid treatment arms. The full details of ACCORD have been published previously (15).

For the present investigation, which is a cohort analysis, we excluded participants with a prolonged or missing QTc interval (calculated using the Framingham formula) at baseline (n = 360), electrocardiogram (ECG) with poor quality (n = 424), missing QTc status during follow-up (n = 756). We further excluded those with current use of antipsychotics (n = 222) or class I/III antiarrhythmics (n = 212) as these medication classes may lead to QTc prolongation. After all these exclusions, 8277 participants were included in our main analyses. The exclusion process is shown elsewhere (Figure S1 (16)).

The ACCORD study was sponsored by the National Heart, Lung, and Blood Institute (NHLBI), and was approved by the institutional review boards at the participating centers. All participants provided a written informed consent (15).

Assessment of Severe Hypoglycemia

Severe hypoglycemic episodes were assessed at visits conducted during the immediate 24 months following enrollment in ACCORD (Figure S1 (16)). The visits were scheduled for months 1, 2, 3, and 4 and every 2 months thereafter for participants in the intensive glucose–lowering arm and those in the standard glycemia plus intensive BP arms; the follow-up visits occurred at months 1, 4, and every 4 months thereafter for the remaining participants in the standard glycemic treatment arm (15). During each visit, participants were queried about the occurrence of any episode of severe hypoglycemia defined as symptomatic, severe hypoglycemic episode with either a blood glucose level of <50 mg/dL or symptoms that promptly resolved with the administration of oral carbohydrate, intravenous glucose, or subcutaneous or intramuscular glucagon (5, 17). For the main analysis, we defined severe hypoglycemia as any hypoglycemic episode meeting the above criteria and requiring medical assistance (care at a hospital, an emergency room, or from medical personnel). In sensitivity analyses, we used a second definition of severe hypoglycemia as any symptomatic, severe hypoglycemic episode necessitating any assistance (either medical care or assistance from another individual) (5, 17).

Identification of Incident QTc Interval Prolongation

The study participants were followed from the 24-month visit throughout the end of the planned 7-year follow-up period. In ACCORD, a resting 12-lead ECG was obtained from each participant at the baseline as well as biennial and exit follow-up visits (15). ECGs were obtained by certified electrocardiographers via a standardized protocol using a MAC 1200 electrocardiograph (Marquette Medical Systems, GE, Milwaukee, WI) at a sampling frequency of 500 Hz. The ECGs were electronically transferred to the central core laboratory at the Epidemiological Cardiology Research Center (Wake Forest School of Medicine, Winston-Salem, NC) for processing and coding. ECGs were visually reviewed for quality and automatically processed using the GE Marquette Medical Systems 12-SL program (version 2001). Incident QTc prolongation was ascertained from ECGs performed at the biennial and exit study visits.

For the main analysis, we used the Framingham formula for HR correction to calculate the QTc interval as follows: QTc_Framingham= QT + 154*(1 – 60/HR) (18). In additional analyses, we used 3 alternative HR correction methods to calculate the QTc interval including the Fridericia’s (QTc_Fridericia= QT/[60/HR]^1/3) (19), Hodges’ (QTc_Hodges= QT + 1.75*[HR – 60]) (20), and Bazett’s (QTc_Bazett= QT*[HR/60]^1/2) correction formulae (21).

We defined QTc prolongation as a QTc >460 ms in women or >450 ms in men as recommended by the American Heart Association, American College of Cardiology, and Heart Rhythm Society (22).

Covariates

We selected covariates a priori based on their potential association with hypoglycemia and QTc prolongation. The covariates, which were obtained at study enrollment, included age, sex, race/ethnicity, treatment arm, cigarette smoking, alcohol intake, duration of diabetes, history of established CVD (defined as prior myocardial infarction, coronary revascularization, carotid or peripheral revascularization, angina, stroke, or heart failure). Cardiac autonomic neuropathy (CAN) was assessed based on the following heart rate variability measures derived from baseline ECGs: standard deviation of all normal-to-normal R-R intervals (SDNN) and root mean square of successive differences between normal-to-normal R-R intervals (rMSSD). CAN was defined as SDNN and rMSSD both being below the fifth percentile of a healthy US population distribution (SDNN < 8.2 ms and rMSSD < 8.0 ms) (23). We included CAN as a covariate due to prior reports of an association between CAN, hypoglycemia, and QTc prolongation (24). Additionally, we selected the following variables collected during the hypoglycemia assessment period: average systolic BP (collected over 12 visits), average body mass index (BMI: average of BMI values from baseline, 12-month and 24-month visits), average HbA_1C (calculated from visits that occurred at baseline, 4, 8, 12, 16, 20, and 24 months), average ratio of total/high-density lipoprotein (HDL) cholesterol (mean of the baseline, 4, 8, 12, and 24-month visits), average estimated glomerular filtration rate (eGFR: calculated from the baseline, 4, 8, 12, 16, 20, and 24-month follow-up visits), use and classes of antihypertensive medications, and use of insulin or sulfonylurea. Total, HDL-, and low-density lipoprotein (LDL) cholesterol levels were measured at the ACCORD central laboratory using standard biochemical methods (15). Serum creatinine was measured via enzymatic methods on a Roche Double Modular P Analytics automated analyzer and eGFR calculated using the abbreviated Modification of Diet in Renal Disease (MDRD) equation (25).

Statistical Analyses

We compared the characteristics of study participants by severe hypoglycemia status using the t-test or Kruskal–Wallis test as appropriate for continuous variables; and the χ ² test for categorical variables. We used multivariable Poisson regression with robust variance estimation to generate risk ratios (RRs) and 95% CI relating severe hypoglycemia to incident QTc prolongation. We performed similar analyses relating the number of severe hypoglycemic episodes (categorized as 0, 1, or ≥2 episodes) to QTc prolongation.

The regression models were constructed in a sequential fashion. Model 1 adjusted for age, sex, race/ethnicity, and treatment arm; model 2 included variables in model 1 with additional adjustment for current smoking, alcohol intake, average BMI, average total/HDL cholesterol ratio, average hemoglobin A_1C, diabetes duration, average systolic BP, use of BP-lowering medication, average eGFR, and use of insulin or sulfonylurea; model 3 included model 2 variables plus history of CVD and use of beta blockers. Model 4 included model 3 variables with further adjustment for CAN. We conducted tests for statistical interaction of hypoglycemia with age, sex, treatment arm, race, and average HbA_1C.

A 2-sided P > .05 was considered statistically significant for all analyses including the interaction tests. All analyses were performed using STATA 14.2 (Stata, Inc, College Station, TX).

Results

Baseline Characteristics by Severe Hypoglycemia Status

The characteristics of study participants by severe hypoglycemia status are displayed in Table 1. The study sample consisted of 8277 participants (mean age: 62.6 [SD 6.5] years, 38.7% women, 62.8% White), of whom 3.9% (n = 324) had ≥1 severe hypoglycemia episode. Participants with severe hypoglycemia were older, more likely to be women, Black, and enrolled in the intensive glycemic management arm. Furthermore, they had longer diabetes duration, lower total/HDL cholesterol ratio and eGFR. They were also more frequently on antihypertensive medications (including beta blockers), and insulin than those without severe hypoglycemia episodes.

Incidence of QTc Prolongation by Severe Hypoglycemia Status

During a median follow-up of 5.0 years (interquartile range 5-5), 517 participants developed incident QTc prolongation (481/7953 among participants without severe hypoglycemia [6.1%]; and 36/324 among those with severe hypoglycemia [11.1%]).

After multivariable adjustment, severe hypoglycemia was associated with elevated risk of incident QTc prolongation (RR 1.66, 95% CI 1.16-2.38, P = .005, model 3, Table 2). An additional adjustment for CAN did not affect the magnitude or significance of the association, with a RR of 1.66 (95% CI 1.16-2.38, P = .005, model 4, Table 2).

The analyses using alternative QTc formulae yielded similar results with RRs of 1.59 (95% CI 1.13-2.23), 1.64 (95% CI 1.19-2.26), and 1.64 (95% CI 1.20-2.24) for the Fridericia, Hodges, and Bazett correction formulas, respectively (model 4, Table 2).

Incident QTc Prolongation by Number of Severe Hypoglycemia Status

We assessed the risks of QTc prolongation according to the number of severe hypoglycemia episodes. Compared with participants without severe hypoglycemia, the RRs for QTc prolongation were 1.57 (95% CI 1.04-2.39) and 2.01 (95% CI 1.07-3.78) for those with 1 and ≥2 severe hypoglycemic episodes, respectively (model 4, Table S1 (16)).

Additional Analyses

We tested for statistical interaction by age, sex, treatment arm, race, and average HbA_1C using the maximally adjusted regression model. No effect modification was found by sex, treatment arm, race, and average HbA_1C. We found a statistical interaction by age (P_Interaction= .008). Accordingly, we conducted subgroup analyses by age (using the median of 61.9 years as the cutoff). In subgroup analyses by age (Table 3), a significant association persisted between severe hypoglycemia and increased risk of QTc prolongation among younger participants (age <61.9 years; RR 2.63 [95% CI 1.49-4.64]) but not among older participants (age ≥61.9 years; RR 1.37 [95% CI 0.87-2.17]). This pattern was consistent using the Framingham, Fridericia, and Bazett correction formulas, but not the Hodges formula (1.57 [95% CI 0.87-2.83], and 1.69 [95% CI 1.15-2.47] for younger and older participants respectively).

When severe hypoglycemia was assessed using an alternative definition of severe hypoglycemia as severe hypoglycemic episode requiring any assistance, severe hypoglycemia remained associated with a higher risk of QTc prolongation, with the greatest risk observed among participants younger than 61.9 years (Tables S2, S3, and S4 (16)).

No significant association was observed between QTc prolongation and other parameters such as diabetes duration, total/HDL cholesterol ratio or mean eGFR (Table S5 (16)).

Discussion

We evaluated the associations of severe hypoglycemia with incident QTc prolongation in a large cohort of adults with type 2 diabetes. We observed that severe hypoglycemia was independently associated with a greater risk of incident QTc prolongation. Moreover, we observed that this association was more profound among younger participants. Our findings were consistent across several definitions of severe hypoglycemia and QT interval correction formulae. Our results suggest that severe hypoglycemic episodes (including repeated episodes) are possibly related to deleterious changes in cardiac repolarization (possibly cumulative) leading to QTc prolongation.

Our study is one of the few to report on the prospective association between severe hypoglycemia and incident QTc prolongation using a large sample of adults with type 2 diabetes. Thus far, investigations on hypoglycemia and QTc prolongation have mainly focused on individuals with type 1 diabetes. An epidemiological study evaluating the relation of severe hypoglycemia with QTc prolongation focused on individuals with type 1 diabetes, and also found a positive association between severe hypoglycemia and QTc prolongation in this population; this study was however limited by its cross-sectional design (26). In a prospective evaluation of the same cohort of patients with type 1 diabetes, severe hypoglycemia during follow-up was significantly associated with a greater incidence of QTc prolongation, although this association became nonsignificant after additional adjustment for diabetic neuropathy (27). Our report complements prior experimental or small-scale clinical studies by providing data from a large prospective study that support the putative role of severe hypoglycemia in the development of QTc prolongation, a precursor to lethal ventricular tachyarrhythmias (9, 10), in people with type 2 diabetes.

Experimental studies have suggested a number of potential pathways underlying hypoglycemia-induced QTc prolongation. A first mechanism is the interaction of low blood glucose level with the human ether-ago-go-related gene (HERG) potassium channel, the rapidly activating delayed rectifier potassium channel, which is essential in cardiac repolarization (28). Hypoglycemia interferes with its function by reducing HERG current density, leading to prolongation of the action potential and thus the QT interval (29). A second mechanism relates to the sympathoadrenal response in response to severe hypoglycemia which involves increased alpha and beta sympathetic activity, as well as higher plasma levels of epinephrine and norepinephrine, potentially leading to QTc prolongation (30). A third mechanism involves the role of hypokalemia. Indeed, hypoglycemia is often linked to excess insulin, which drives potassium uptake from the bloodstream (31), leading to hypokalemia, which can have a profound effect of myocardial cells and may cause cardiac arrhythmias including prolonged QTc (32). Finally, intracellular calcium oscillations leading to fluctuations in the membrane potential, which when exceeding the threshold for membrane depolarization, may result in a nondriven action potential. Hypoglycemia may also cause calcium overload further increasing the risk of QTc prolongation (33, 34).

Our findings have potential clinical implications for people with type 2 diabetes. Hypoglycemia may lead to fatal cardiac arrhythmias (1, 6, 7). Our study points to the potential utility of a systematic assessment of QTc interval from a 12-lead ECG in the setting of an episode of severe hypoglycemia, which has the potential for preventing fatal arrhythmias and thus death (6-8). On the other hand, among individuals with type 2 diabetes and at high risk of hypoglycemia (eg, with hypoglycemia unawareness), a prior history of QTc prolongation could constitute a criterion for continuous glucose monitor utilization, as this could potentially prevent death (12, 35). Indeed, the utilization of continuous glucose monitoring devices has been shown to reduce the occurrence of hypoglycemia episodes (36).

Our findings should be interpreted in the context of a few limitations. First, although ECGs were recorded at prespecified visits, continuous electrocardiographic monitoring was not available. It is therefore possible that we did not capture self-limited episodes of QTc prolongation occurring in between study visits, such as those occurring during certain hypoglycemic episodes. We also cannot exclude a possible bidirectionality of the association between severe hypoglycemia and QTc prolongation. Second, ACCORD did not include the use of continuous glucose–monitoring devices, thus it is possible that this study did not capture all hypoglycemic events, especially nocturnal hypoglycemia episodes, which are thought to be related to prolonged cardiac repolarization (37). This might have resulted in nondifferential misclassification of the exposure and outcome potentially leading to a bias towards the null. Third, this study was observational, hence there is a possibility of residual confounding. Finally, we did not have information available on clinically important outcomes such as deaths directly attributable to severe hypoglycemia and/or QTc prolongation.

Despite these limitations, the strengths of this study include the analysis of a large sample of adults with type 2 diabetes, the use of 2 very specific definitions of hypoglycemia, the standardized adjudication of QTc prolongation using centralized ECG core analysis, as well as the robust adjustment for relevant confounders including the extent and intensity of glycemia control, diabetes duration, the use of beta blockers, insulin and sulfonylureas, the presence of CAN and the exclusion of individuals on medication that could affect the QT interval.

In conclusion, in a large cohort of adults with type 2 diabetes, we observed that severe hypoglycemia was associated with a greater risk of incident QTc interval prolongation, independently of other risk factors including CAN. Moreover, the risk of QTc prolongation was greatest among younger participants (age <61.9 years).

Abbreviations

Abbreviations
 
• BMI

  body mass index

 
• BP

  blood pressure

 
• CVD

  cardiovascular disease

 
• ECG

  electrocardiogram

 
• eGFR

  estimated glomerular filtration rate

 
• HbA_1C

  hemoglobin A_1C

 
• HDL

  high-density lipoprotein

 
• HR

  heart rate

 
• LDL

  low-density lipoprotein

 
• MDRD

  Modification of Diet in Renal Disease

 
• rMSSD

  root mean square of successive differences between normal-to-normal R-R intervals

 
• RR

  risk ratio

 
• SDNN

  standard deviation of all normal-to-normal R-Rs intervals

 
• SH

  severe hypoglycemia

 
• T2DM

  type 2 diabetes

 
• QT

  corrected QT

Acknowledgment

The authors wish to thank the staff and participants of the ACCORD study for their valuable contributions.

The data used for the analyses are publicly available through the NHLBI Biorepository (BioLINCC).

Financial Support

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Dr. Echouffo-Tcheugui was supported by a National Heart, Lung, and Blood Institute grant K23 HL153774.

Author Contributions

A.D.K. performed the statistical analyses, interpreted the results, participated in the discussion, wrote the first draft of the manuscript, revised the manuscript and approved the final version. M.F.Y., S.E., and G.C.F. interpreted the results, participated in the discussion, revised the manuscript, and approved the final version. J.B.E. conceived the idea for the study, designed the study, performed the statistical analyses, interpreted the results, participated in the discussion, revised the manuscript, and approved the final version. J.B.E. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Disclosure Summary

Dr. Fonarow reports consulting for Abbott, Amgen, AstraZeneca, Bayer, Janssen, Medtronic, Merck, and Novartis. The other authors have no other potential conflicts of interest relevant to this article were reported. The Action to Control Cardiovascular Risk in Diabetes (ACCORD) has been funded by Federal funds from the National Heart Lung and Blood Institute (NHLBI). This manuscript was prepared using ACCORD Research Material obtained from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center, and does not necessarily reflect the opinions or views of the ACCORD or the NHLBI or ACCORD.

Data Availability

Some or all datasets generated during and/or analyzed during the current study are available upon request from the National Heart Lung and Blood Institute (NHLBI) Biologic Specimen and Data Repository Information Coordinating Center.

References