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Abstract
Objectives This study was conducted to establish the association between glycated haemoglobin (HbA1c) and left ventricular diastolic dysfunction (LVDD) in non-hypertensive patients with newly diagnosed type 2 diabetes mellitus (DM) and determine the cut-off value of HbA1c for detecting LVDD.
Design Cross-sectional study.
Setting This study was conducted in General Medicine Department in collaboration with the Cardiology Department at All India Institute of Medical Sciences, Patna.
Participants The study population comprised patients with newly diagnosed type 2 DM within the past 3 months, aged between 18 years and 80 years, who were not hypertensive and without any systemic diseases and who presented to the General Medicine Department.
Primary and secondary outcome measures The presence of LVDD was the primary outcome measure.
Results Among the total of 60 participants, it was observed that age (adjusted odds ratio (AOR): 1.169, 95% CI: 1.066 to 1.283) and HbA1c (AOR: 2.625, 95% CI: 1.264 to 5.450) were found to be independent predictors for the presence of LVDD. Receiver operating characteristic analysis identified a cut-off value of HbA1c at 9.5% (80 mmol/mol) for detecting LVDD, with a specificity of 96.43%, a sensitivity of 37.5% and a positive predictive value (PPV) of 91.62%.
Conclusions This study demonstrated that age and HbA1c levels are independent predictors of LVDD in patients with newly diagnosed type 2 DM without hypertension. A cut-off value of 9.5% for HbA1c was identified with a high specificity and PPV for predicting LVDD in patients with newly diagnosed type 2 diabetes. This underscores the importance of conducting echocardiography in patients with newly diagnosed asymptomatic type 2 diabetes with HbA1c 9.5% or more to assess LVDD, allowing for prompt interventions if necessary and to decelerate the progression towards heart failure.
- Echocardiography
- Heart failure
- DIABETES & ENDOCRINOLOGY
Data availability statement
Data are available upon reasonable request. The datasets generated during the study are available from the corresponding author upon reasonable request.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Strengths and limitations of this study
Comprehensive echocardiographic assessments were conducted for all the study participants.
Patients with a history of hypertension, which is a known confounding factor for LVDD, were excluded from the study.
The sample size of the study was relatively small.
The study did not include a control group of non-diabetic patients.
As it is a single-centre study, the results may not necessarily be generalisable to the entire region.
Introduction
Diabetes mellitus (DM) is a rapidly growing epidemic, affecting over 463 million people worldwide, with India having a significant portion of the population affected. It is a major contributor to mortality, particularly due to cardiovascular complications such as coronary artery disease and heart failure.1
Diabetic cardiomyopathy, a cause of heart failure, is a separate entity from atherosclerotic coronary artery disease, and early diagnosis and treatment are crucial in halting disease progression. Various factors such as glycaemic control, dyslipidaemia and hypertension play a role in diabetic cardiomyopathy, but recent studies have focused on chronic inflammation and changes in the extracellular matrix.2
The mechanisms attributed to diabetic cardiomyopathy involve endothelial dysfunction, platelet activation and aberrant coagulation cascade, which lead to the production of reactive oxygen species. These processes are associated with chronic inflammation and extracellular changes caused by advanced glycation end products.3 4 Studies have shown a high prevalence of subclinical diastolic dysfunction among diabetic patients, with evidence suggesting that myocardial damage impacts diastolic performance prior to systolic function.5
Left ventricular diastolic dysfunction (LVDD) is the first stage of diabetic cardiomyopathy and has a significant impact on early diagnosis and treatment.6 The relationship between glycaemic control and LVDD is still debated, and finding an association between glycated haemoglobin (HbA1c) and LVDD would be beneficial. Although studies finding an association between HbA1c and LVDD have taken into account long-standing cases of DM, which have established a relation with diastolic dysfunction,7 it is likely that diabetes affects the diastolic function of the heart even before the onset of overt complications resulting from diabetes. This underscores the necessity to evaluate newly diagnosed cases of DM.
If HbA1c is found to be predictive of LVDD in patients with newly diagnosed type 2 diabetes, it could be used as a routine screening tool for identifying high-risk individuals where echocardiography is not feasible or available for newly diagnosed diabetic patients and diagnosed (HFpEF) as earliest as possible and providing early treatment. The aim of this research is to assess the association between HbA1c and LVDD (if any) in non-hypertensive patients with newly diagnosed type 2 diabetes, with secondary objectives including determining the cut-off value of HbA1c for LVDD.
Materials and methods
Study design
This study employed an observational cross-sectional design.
Study setting
The study was conducted at the Outpatient Department (OPD) and Inpatient Department (IPD) of the General Medicine Department collaborating with the Cardiology Department at All India Institute of Medical Sciences (AIIMS), Patna.
Study duration
The study was conducted from January 2022 to January 2023.
Study participants
The study included all patients with newly diagnosed type 2 DM attending the OPD and IPD of the General Medicine Department at AIIMS, Patna, who met the inclusion and exclusion criteria.
Inclusion criteria
Individuals newly diagnosed with type 2 DM within the past 3 months based on American Diabetic Association (ADA) guidelines,8 including fasting blood sugar (FBS), 2-hour plasma glucose (2-hour PG) after an oral glucose tolerance test, HbA1C levels, random blood glucose (RBS) and medical history
Non-hypertensive individuals (blood pressure <140/90 mm Hg according to the eighth Joint National Committee),9 without a history of hypertension or antihypertensive medication
Age group: 18–80 years
Exclusion criteria
Individuals who did not provide consent
Known cases of diseases such as ischaemic heart disease, coronary artery disease, cardiomyopathy, valvular heart disease, chronic pulmonary illness, chronic kidney disease (estimated glomerular filtration rate <60 mL/min/m2), chronic liver disease, severe anaemia (haemoglobin <7 mg/dL) and thyroid dysfunction, as identified through a detailed history, clinical examination and available investigations
Number of groups
Group with LVDD: LVDD was classified into three grades based on specific echocardiographic criteria outlined in the American Society of Echocardiography and the European Association of Cardiovascular Imaging 2016 guidelines for LVDD evaluation.10 Grade 1 LVDD was assumed to be an E/A ratio of ≤0.8 and an E velocity of ≤50 cm/s. Additional assessments were done if the E/A ratio was ≤0.8 but E velocity was >50 cm/s, or if the E/A ratio was >0.8 but <2. The evaluation involved three parameters: (1) average E/e' >14, (2) tricuspid regurgitation (TR) velocity >2.8 m/s and (3) left atrial volume index >34 mL/m². If two or all three of these parameters were negative, it was taken as Grade 1 LVDD, assuming normal left atrial pressure (LAP). If two or all three parameters were positive, it was taken as Grade 2 LVDD, indicating raised LAP. Finally, if the E/A ratio was ≥2 and there was evidence of raised LAP, it was taken as Grade 3 LVDD. Patients with any of these grades of LVDD were taken into this group.
Group without LVDD.
Sample size calculation
The sample size for the study was calculated using the online tool ‘easyROC’ for a single diagnostic test. The assumptions included a significance level of 5%, a study power of 80% and an assumed discriminatory power of HbA1c to differentiate between the presence and absence of LVDD as 0.7 (area under the curve (AUC)). Furthermore, an allocation ratio of LVDD present to LVDD absent cases was set at 1:1. Thus, a minimum sample size of 24 cases with LVDD present and a minimum of 24 cases with LVDD absent was calculated, totalling at least 48 patients.
Sampling technique
Purposive sampling was employed.
Study procedure
The study enrolled patients from the General Medicine Department’s OPD and IPD, and the diagnosis of type 2 diabetes was established based on ADA criteria, utilising parameters such as FBS, 2-hour PG, HbA1C or RBS values. Prior to any data collection, informed consent was diligently obtained from each participant. Data collection employed a prestructured questionnaire, encompassing baseline information like age, gender, medical history, clinical examination findings including height and weight (for body mass index (BMI) and body surface area calculation) and pertinent investigations such as FBS, 2-hour PG and HbA1c. Furthermore, the study documented details concerning the use of oral hypoglycaemic drugs or insulin within the past 3 months (if any). Transthoracic echocardiography was then performed to identify LVDD. All the cases were diagnosed during the first OPD visit, followed by echocardiography tests categorising them as either LVDD or non-LVDD on the same day as the diagnosis of type 2 DM.
Study tool
Transthoracic echocardiography using M-mode, pulsed wave Doppler study and tissue Doppler imaging were performed on a PHILIPS EPIQ 7C model.
Data collection
Data were collected using a structured questionnaire through face-to-face interviews, clinical examination and lab reports.
During the echocardiography, after ruling out heart failure with reduced ejection fraction (left ventricular ejection fraction (LVEF) <40%) and heart failure with mildly reduced ejection fraction (LVEF 40%–49%), patients were screened further with E wave, E/A ratio, average E/e’ and maximum TR velocity, and lastly, LVDD was examined. If patients had LVDD, then the grade of LVDD was determined.
Statistical analysis
Data analysis was conducted using Microsoft Excel, Jamovi and SPSS V.26. Categorical variables were expressed in percentages and proportions, while continuous variables were expressed in mean (SD) based on the normality of the data. A univariate binary logistic regression analysis was performed to look for predictors of LVDD, and the variables with p<0.2 were considered for the multivariate analysis model. We used ‘Enter Method’ in SPSS to build the models, and the model fit was assessed by the Hosmer-Lemeshow goodness of fit test, and the model variability was given by Nagelkerke’s R2. A p<0.05 was considered significant. To find out the probable cut-off value of HbA1c, FBS and 2-hour PG for predicting LVDD in normotensive patients with newly diagnosed type 2 diabetes, receiver operating characteristic (ROC) analysis was performed, and the Youden index was calculated.
Patient and public involvement
Patients and/or the public were not involved in the study design, conduct or reporting of this research. We intend to disseminate the key findings of this study to the general public through the local media and open-access publication.
Results
The demographic details and laboratory investigations of individuals with LVDD and those without LVDD are presented in table 1. In the LVDD group, HbA1c, FBS and 2-hour PG values were significantly higher, at 9.5% (2.72) (80.6 mmol/mol (29.33)), 174 mg/dL (35.8) and 246 mg/dL (44.6), respectively, compared with the non-LVDD group, where the values were 7.8% (0.96) (107.1 mmol/mol (10.35)), 148 mg/dL (13.6) and 210 mg/dL (16.70), respectively with p=0.002, p<0.001 and p<0.001, respectively. Non-LVDD individuals had an average BMI of 22.9 kg/m2 (3.79) and an LVEF of 55.0% (7.0), while individuals with LVDD exhibited an average BMI of 22.9 kg/m2 (3.38) and an LVEF of 55.0% (8.0) with p=0.419 and p=0.440, respectively.
Demographic details and laboratory investigations of the study participants (n=60)
Individuals with LVDD had notably lower E wave and E/A ratio values, measuring 75.6 cm/s (21.7) and 1.0 (0.54), respectively, compared with the non-LVDD group, which had values of 88.5 cm/s (19.0) and 1.3 (0.28), respectively. Furthermore, the LVDD group had a significantly higher maximum TR velocity of 2 m/s (0.63) compared with that of the non-LVDD group with 1.6 m/s (0.49) (p=0.016). Additionally, individuals with LVDD showed a higher average E/e’ ratio of 10.2 (4.36), in contrast to the non-LVDD group with 8.5 (2.06), but the difference was not statistically significant (p=0.059).
The results of the univariate and multivariate binary logistic regression analyses are presented in table 2. It was observed that age (crude odds ratio (COR), 1.097; 95% CI, 1.041 to 1.157), HbA1c (COR, 1.840; 95% CI, 1.164 to 2.907), FBS (COR, 1.045; 95% CI, 1.016 to 1.075) and 2-hour PG (COR, 1.049; 95% CI, 1.019 to 1.080) were significant predictors of LVDD. These variables were subsequently considered for the multivariate analysis.
Various risk factors associated with the presence of left ventricular diastolic dysfunction (LVDD)
Only age (adjusted odds ratio (AOR), 1.169; 95% CI, 1.066 to 1.283) and HbA1c (AOR, 2.625; 95% CI, 1.264 to 5.450) were found to be independent predictors for the presence of LVDD.
ROC analysis was conducted to evaluate the predictive abilities of HbA1c, FBS and 2-hour PG, for LVDD in patients with newly diagnosed type 2 DM. HbA1c had an AUC of 0.713, FBS had an AUC of 0.75 and 2-hour PG had an AUC of 0.789, all with statistically significant p values (<0.05). Cut-off values were determined using the maximum Youden index, and the corresponding sensitivities and specificities were calculated. HbA1c at a cut-off of 9.5% (80 mmol/mol) exhibited a sensitivity of 37.5% and specificity of 96.43%, with a positive predictive value (PPV) of 91.62%. FBS at a cut-off of 161 mg/dL had a sensitivity of 68.75%, specificity of 85.71% and PPV of 83.36%. 2-hour PG at a cut-off of 224 mg/dL showed a sensitivity of 75%, specificity of 85.71% and PPV of 84.53% for predicting LVDD (figure 1).
Receiver operating characteristic curves for prediction of left ventricular diastolic dysfunction.
Discussion
This study was undertaken to establish an association between HbA1c levels and the presence of LVDD in non-hypertensive patients with newly diagnosed type 2 DM. Among the total of 60 participants, it was observed that age and HbA1c were independent predictors of LVDD in patients, with AORs of 1.169 and 2.625, respectively. ROC analysis, with transthoracic echocardiography taken as the gold standard, identified a cut-off value of HbA1c at 9.5% (80 mmol/mol) for detecting LVDD, with a specificity of 96.43%, sensitivity of 37.5% and PPV of 91.62%.
DM is one of the leading causes of morbidity in the world with an ever-growing prevalence. According to data from WHO, from 2000 to 2019, there was a 3% rise in age-adjusted mortality rates associated with DM. In lower-middle-income nations, the mortality rate related to diabetes surged by 13%.11 It can affect almost every organ and organ system, notably the heart, kidneys, eyes and peripheral nerves.
DM and cardiovascular disease (CVD) are closely interconnected, and CVD stands as the primary contributor to both mortality and morbidity among individuals with diabetes.12 As such, one of the primary goals in managing DM should be to reduce cardiovascular risk. Nonetheless, it is a challenge due to the complex and multifaceted relationship that links DM to CVD.13
DM and heart failure share an intricate, bidirectional relationship, with diabetes now recognised as an independent risk factor for heart failure.14 A distinct clinical condition called diabetic cardiomyopathy, characterised by myocardial dysfunction in diabetic patients that cannot be attributed to hypertension, coronary artery disease or other cardiac ailments, has been identified.15 In contrast to individuals who do not have diabetes, the risk of developing heart failure is 1.2–1.7 times higher in those having impaired glucose tolerance, and it rises to 2 times in men and 5 times in women with diabetes.16 17
DM often silently affects heart functionand thus goes undiagnosed until symptoms are evident, leading to underdiagnosis of early-stage heart failure due to limited knowledge and diagnostic options.14 This necessitates the search for newer diagnostic approaches and protocols for detecting heart failure early in such patients.
Left ventricular dysfunction, which ultimately leads to heart failure, refers to a state in which the heart’s left ventricle experiences structural or functional abnormalities, leading to decreased cardiac output and increased intracardiac pressures, either at rest or under stress.18 Multiple mechanisms have been postulated for the development of LVDD in DM, and the process starts with left atrial enlargement. Intricate molecular and cellular processes attributed to metabolic and neurohumoral imbalances, oxidative stress, inflammation as well as both microvascular and macrovascular angiopathy have been implicated in causing myocardial fibrosis, hypertrophy, apoptosis and dysfunction leading to the development of LVDD in diabetic patients.14 Multiple studies have estimated the prevalence of asymptomatic LVDD in diabetic patients, and the reported range varies from 47% to as high as 75%, highlighting the need for better detection.19 20
Although quite a few studies have reported a significant association between HbA1c levels and LVDD,21–23 many of these studies were conducted in patients with established DM and hypertension, which are confounding factors for LVDD.7 14 24 Thus, only normotensive patients without any history of antihypertensive medication intake were included in this study.
In type 2 DM, microvascular and macrovascular complications may silently commence several years before clinical or biochemical diagnosis. Thus, our focus was on patients with newly diagnosed type 2 DM to identify LVDD at the earliest stage, utilising the HbA1c value obtained at the first point of medical attention. Since HbA1c reflects the glycaemic status of the past 2–3 months, we specifically included cases of newly diagnosed diabetes within the last 3 months.
Similar to previous studies, HbA1c was identified as an independent risk factor of LVDD in patients with newly diagnosed type 2 diabetes with odds of LVDD nearly increasing by 2.6 times with each 1% rise in HbA1c levels. This points to the hidden burden of cardiac dysfunction in seemingly asymptomatic diabetic patients and highlights the need for conducting echocardiography in such patients for early detection. The high specificity and PPV of HbA1c (at a cut-off value of 9.5% (80 mmol/mol)) observed in this study underscore its potential utility as a surrogate marker for predicting LVDD in patients having type 2 diabetes even at the time of diagnosis. Furthermore, during diagnosis or routine monitoring of patients with diabetes, if the HbA1c level is ≥9.5% (80 mmol/mol), clinicians could consider recommending a screening echocardiography to look for LVDD.
A similar study conducted by Senoz et al in Turkey among 116 participants aged 18–65 years,25 also discovered a significant association between HbA1c and LVDD. However, their identified cut-off value was 7.35% (57 mmol/mol), with sensitivity and specificity at 80%, which is notably lower than the cut-off value of 9.5% (80 mmol/mol) identified in this study. This disparity could be due to the difference in the sample sizes in the study or due to the inherent differences between the study participants in terms of age group and geographical location. Further large-scale, multicentric studies are needed to establish a more generalisable cut-off.
While FBS and 2-hour PG showed higher sensitivity in predicting LVDD, they may not be as reliable as HbA1c. This is because blood glucose levels can fluctuate significantly throughout the day due to various factors. HbA1c, on the other hand, reflects the average blood glucose levels over a 2–3-month period, providing a better indication of the cumulative impact of hyperglycaemia on the myocardium. FBS and 2-hour PG only represent glucose levels at a single point in time, which may not capture the chronic effects of hyperglycaemia on the myocardium as effectively as HbA1c.
Strengths and weaknesses
The strengths of this study include the use of comprehensive echocardiographic assessment and the exclusion of patients with hypertension and other CVDs that may affect left ventricular diastolic function. The limitations of this study include the relatively small sample size, the lack of a control group of non-diabetic patients and the use of non-random (purposive) sampling technique, which could be the reason for the observed discrepancy in age between the two groups. Further studies on this topic should aim to mitigate the confounding effect of age to suggest more accurate, age-adjusted cut-off values of HbA1c.
Conclusion and recommendations
This study demonstrated that age and HbA1c levels are independent predictors of LVDD in patients with newly diagnosed type 2 diabetes without hypertension. A cut-off value of 9.5% (80 mmol/mol) for HbA1c in predicting LVDD at the time of diagnosis of type 2 DM, with a high specificity and PPV, was identified. This underscores the importance of conducting echocardiography in patients with newly diagnosed type 2 diabetes with HbA1c of 9.5% (80 mmol/mol) or more to assess LVDD at the earliest, allowing for prompt interventions if necessary and to decelerate the progression towards HFpEF and other complications.
Supplemental material
Data availability statement
Data are available upon reasonable request. The datasets generated during the study are available from the corresponding author upon reasonable request.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants and the ethical approval was obtained from the institutional Ethics Committee of All India Institute of Medical Sciences, Patna (Ref. No. AIIMS/Pat/IEC/PGTh/Jan21/13). Participants gave informed consent to participate in the study before taking part.
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Contributors Conceptualisation: RP, SS, SA, NK, SA. Data curation: RP, SA, RB, VSO. Data analysis: SA, RB, VSO. Methodology: RP, SS, SA, NK, RB, VSO. Supervision: SS, SA, NK, SA. Writing (original draft): RB and VSO. Writing (review and editing): RP, SS, SA, NK, SA, RB, VSO. RP and SS take responsibility for the overall content as guarantors.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.