scholarly journals 564 Cardiac magnetic resonance myocardial feature tracking for optimized risk assessment after acute myocardial infarction in patients with type 2 diabetes

2020 ◽  
Vol 21 (Supplement_1) ◽  
Author(s):  
J T Kowallick ◽  
S J Backhaus ◽  
T Stiermaier ◽  
T Lange ◽  
J L Navarra ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Type 2 Diabetes ◽  
Risk Assessment ◽  
Acute Myocardial Infarction ◽  
Magnetic Resonance ◽  
Feature Tracking ◽  
Multivariable Analysis ◽  
Diabetic Patients ◽  
Patients With Diabetes

Abstract Objective Type 2 diabetes mellitus (T2DM) associates with worse cardiovascular outcome following acute myocardial infarction (AMI) as compared to non-diabetic patients. Since the mechanisms behind these observations are not fully understood we aimed to quantify the underlying pathophysiology on ventricular and atrial levels and study their prognostic implications using cardiovascular magnetic resonance (CMR) quantitative feature-tracking (FT) and tissue characterization. Research Design and Methods: A total of 1147 consecutive patients with AMI (n = 265 with diabetes; n = 882 without diabetes) undergoing cardiac magnetic resonance (CMR) imaging in median 3 days after AMI were included in this multicenter study. Left ventricular (LV) function and volumetry included LV ejection fraction (LV-EF), global longitudinal (GLS), radial (GRS) and circumferential strain (GCS) as well as left atrial (LA) strain and strain rate parameters of LA reservoir, conduit and booster pump function. LV damage assessment included infarct size (IS), edema and microvascular obstruction (MO). The clinical study endpoint was the rate of major adverse cardiovascular events (MACE) at 12 months. Results T2DM patients had impaired LA reservoir (19.8 vs. 21.2%, p < 0.01) and conduit strains 7.6 vs. 9.0%, p < 0.01) but no differences in ventricular function or myocardial damage. They were at higher risk of MACE than non-diabetic patients (10.2% vs. 5.8%, p < 0.01) with the majority of MACE occurring in patients with LVEF ≥ 35%. Whilst LVEF was an independent predictor of adverse events in non-diabetic patients (p = 0.04 on multivariable analysis), LV GLS as well as LA strain emerged as independent predictors of poor prognosis in patients with diabetes (p < 0.02 on multivariable analysis). Considering patients with diabetes and LVEF ≥35% (n = 237), GLS and LA reservoir strain below median were significantly associated with higher 12-month event rates. Conclusions In patients with diabetes, LA and LV longitudinal strain permit optimized risk assessment early after reperfused AMI with incremental prognostic value over and above LVEF.

scholarly journals Cardiac Magnetic Resonance Myocardial Feature Tracking for Optimized Risk Assessment after Acute Myocardial Infarction in Patients with Type 2 Diabetes

2020 ◽  
Author(s):  
Ada Admin ◽  
Sören J. Backhaus ◽  
Johannes T. Kowallick ◽  
Thomas Stiermaier ◽  
Torben Lange ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Type 2 Diabetes ◽  
Risk Assessment ◽  
Acute Myocardial Infarction ◽  
Magnetic Resonance ◽  
Left Ventricular ◽  
Major Adverse Cardiovascular Events ◽  
Diabetic Patients ◽  
Patients With Diabetes

Type 2 diabetes mellitus predicts outcome following acute myocardial infarction (AMI). Since underlying mechanics are incompletely understood, we investigated left ventricular (LV) and atrial (LA) pathophysiological changes and their prognostic implications using cardiovascular magnetic resonance (CMR). Consecutive patients (n=1147, n=265 diabetic; n=882 non-diabetic) underwent CMR 3 days after AMI. Analyses included LV ejection fraction (LVEF), global longitudinal, circumferential and radial strains (GLS, GCS and GRS), LA reservoir, conduit and booster pump strains, as well as infarct size, edema and microvascular obstruction. Predefined endpoints were major adverse cardiovascular events (MACE) within 12 months. Diabetic<b> </b>patients had impaired LA reservoir (19.8 vs. 21.2%, p<0.01) and conduit strains (7.6 vs. 9.0%, p<0.01) but not ventricular function or myocardial damage. They were at higher risk of MACE than non-diabetic patients (10.2% vs. 5.8%, p<0.01) with most MACE occurring in patients with LVEF≥35%. Whilst LVEF (p=0.045) and atrial reservoir strain (p=0.024) were independent predictors of MACE in non-diabetic patients, GLS was in diabetic patients (p=0.010). Considering patients with diabetes and LVEF≥35% (n=237), GLS and LA reservoir strain below median were significantly associated with MACE. In conclusion, in patients with diabetes, LA and LV longitudinal strain permit optimized risk assessment early after reperfused AMI with incremental prognostic value over and above LVEF.

scholarly journals Cardiac Magnetic Resonance Myocardial Feature Tracking for Optimized Risk Assessment after Acute Myocardial Infarction in Patients with Type 2 Diabetes

2020 ◽  
Author(s):  
Ada Admin ◽  
Sören J. Backhaus ◽  
Johannes T. Kowallick ◽  
Thomas Stiermaier ◽  
Torben Lange ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Type 2 Diabetes ◽  
Risk Assessment ◽  
Acute Myocardial Infarction ◽  
Magnetic Resonance ◽  
Left Ventricular ◽  
Major Adverse Cardiovascular Events ◽  
Diabetic Patients ◽  
Patients With Diabetes

Type 2 diabetes mellitus predicts outcome following acute myocardial infarction (AMI). Since underlying mechanics are incompletely understood, we investigated left ventricular (LV) and atrial (LA) pathophysiological changes and their prognostic implications using cardiovascular magnetic resonance (CMR). Consecutive patients (n=1147, n=265 diabetic; n=882 non-diabetic) underwent CMR 3 days after AMI. Analyses included LV ejection fraction (LVEF), global longitudinal, circumferential and radial strains (GLS, GCS and GRS), LA reservoir, conduit and booster pump strains, as well as infarct size, edema and microvascular obstruction. Predefined endpoints were major adverse cardiovascular events (MACE) within 12 months. Diabetic<b> </b>patients had impaired LA reservoir (19.8 vs. 21.2%, p<0.01) and conduit strains (7.6 vs. 9.0%, p<0.01) but not ventricular function or myocardial damage. They were at higher risk of MACE than non-diabetic patients (10.2% vs. 5.8%, p<0.01) with most MACE occurring in patients with LVEF≥35%. Whilst LVEF (p=0.045) and atrial reservoir strain (p=0.024) were independent predictors of MACE in non-diabetic patients, GLS was in diabetic patients (p=0.010). Considering patients with diabetes and LVEF≥35% (n=237), GLS and LA reservoir strain below median were significantly associated with MACE. In conclusion, in patients with diabetes, LA and LV longitudinal strain permit optimized risk assessment early after reperfused AMI with incremental prognostic value over and above LVEF.

scholarly journals Cardiac Magnetic Resonance Myocardial Feature Tracking for Optimized Risk Assessment After Acute Myocardial Infarction in Patients With Type 2 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (7) ◽  
pp. 1540-1548
Author(s):  
Sören J. Backhaus ◽  
Johannes T. Kowallick ◽  
Thomas Stiermaier ◽  
Torben Lange ◽  
Jenny-Lou Navarra ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Type 2 Diabetes ◽  
Risk Assessment ◽  
Acute Myocardial Infarction ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Feature Tracking

scholarly journals Risk stratification score for acute myocardial infarction and sudden cardiac death in type 2 diabetes mellitus

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
S Lee ◽  
J Zhou ◽  
CL Guo ◽  
WKK Wu ◽  
WT Wong ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Myocardial Infarction ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Cardiac Death ◽  
Adverse Outcomes ◽  
Risk Scores ◽  
Diabetic Patients ◽  
Type 2 Diabetic

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Acute myocardial infarction (AMI) and sudden cardiac death (SCD) are major cardiovascular adverse outcomes in patients with type 2 diabetic mellitus. Although there are many risk scores on composite outcomes of major cardiovascular adverse outcomes or cardiovascular mortality for diabetic patients, these existing scores did not account for the difference in pathogenesis and prognosis between acute coronary syndrome and lethal ventricular arrhythmias. Furthermore, recent studies reported that HbA1c and lipid levels, which were often accounted for in these risk scores, have J/U-shaped relationships with adverse outcomes. Purpose The present study aims to evaluate the application of incorporating non-linear J/U-shaped relationships between mean HbA1c and cholesterol levels into risk scores for predicting for AMI and non-AMI related SCD respectively, amongst type 2 diabetes mellitus patients. Methods This was a territory-wide cohort study of patients with type 2 diabetes mellitus above the age 40 and free from prior AMI and SCD, with or without prescriptions of anti-diabetic agents between January 1st, 2009 to December 31st, 2009 at government-funded hospitals and clinics in Hong Kong. Risk scores were developed for predicting incident AMI and non-AMI related SCD. The performance of conditional inference survival forest (CISF) model compared to that of random survival forests (RSF) model and multivariate Cox model. Results This study included 261308 patients (age = 66.0 ± 11.8 years old, male = 47.6%, follow-up duration = 3552 ± 1201 days, diabetes duration = 4.77 ± 2.29 years). Mean HbA1c and high-density lipoprotein-cholesterol (HDL-C) were significant predictors of AMI under multivariate Cox regression and were linearly associated with AMI. Mean HbA1c and total cholesterol were significant multivariate predictors with a J-shaped relationship with non-AMI related SCD. The AMI and SCD risk scores had an area-under-the-curve (AUC) of 0.666 (95% confidence interval (CI)= [0.662, 0.669]) and 0.677 (95% CI= [0.673, 0.682]), respectively. CISF significantly improves prediction performance of both outcomes compared to RSF and multivariate Cox models. Conclusions A holistic combination of demographic, clinical, and laboratory indices can be used for the risk stratification of type 2 diabetic patients against AMI and SCD.

scholarly journals Predictive value of stress hyperglycemia ratio for the occurrence of acute kidney injury in acute myocardial infarction patients with diabetes

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Side Gao ◽  
Qingbo Liu ◽  
Hui Chen ◽  
Mengyue Yu ◽  
Hongwei Li
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Acute Kidney Injury ◽  
Cardiogenic Shock ◽  
Predictive Value ◽  
Kidney Injury ◽  
Left Ventricular Ejection ◽  
Diabetic Patients ◽  
Stress Hyperglycemia ◽  
Patients With Diabetes

Abstract Background Acute hyperglycemia has been recognized as a robust predictor for occurrence of acute kidney injury (AKI) in nondiabetic patients with acute myocardial infarction (AMI), however, its discriminatory ability for AKI is unclear in diabetic patients after an AMI. Here, we investigated whether stress hyperglycemia ratio (SHR), a novel index with the combined evaluation of acute and chronic glycemic levels, may have a better predictive value of AKI as compared with admission glycemia alone in diabetic patients following AMI. Methods SHR was calculated with admission blood glucose (ABG) divided by the glycated hemoglobin-derived estimated average glucose. A total of 1215 diabetic patients with AMI were enrolled and divided according to SHR tertiles. Baseline characteristics and outcomes were compared. The primary endpoint was AKI and secondary endpoints included all-cause death and cardiogenic shock during hospitalization. The logistic regression analysis was performed to identify potential risk factors. Accuracy was defined with area under the curve (AUC) by a receiver-operating characteristic (ROC) curve analysis. Results In AMI patients with diabetes, the incidence of AKI (4.4%, 7.8%, 13.0%; p < 0.001), all-cause death (2.7%, 3.6%, 6.4%; p = 0.027) and cardiogenic shock (4.9%, 7.6%, 11.6%; p = 0.002) all increased with the rising tertile levels of SHR. After multivariate adjustment, elevated SHR was significantly associated with an increased risk of AKI (odds ratio 3.18, 95% confidence interval: 1.99–5.09, p < 0.001) while ABG was no longer a risk factor of AKI. The SHR was also strongly related to the AKI risk in subgroups of patients. At ROC analysis, SHR accurately predicted AKI in overall (AUC 0.64) and a risk model consisted of SHR, left ventricular ejection fraction, N-terminal B-type natriuretic peptide, and estimated glomerular filtration rate (eGFR) yielded a superior predictive value (AUC 0.83) for AKI. Conclusion The novel index SHR is a better predictor of AKI and in-hospital mortality and morbidity than admission glycemia in AMI patients with diabetes.

Prevalence of Toenail Onychomycosis in Patients with Type 2 Diabetes Mellitus and Evaluation of Risk Factors

2011 ◽  
Vol 101 (1) ◽  
pp. 49-54 ◽  
Author(s):  
Aynur Gulcan ◽  
Erim Gulcan ◽  
Sukru Oksuz ◽  
Idris Sahin ◽  
Demet Kaya
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Fasting Blood Glucose ◽  
Diabetic Patients ◽  
Essential Components ◽  
Patients With Diabetes ◽  
Epidemiologic Risk

Background: We sought to determine the frequency of toenail onychomycosis in diabetic patients, to identify the causative agents, and to evaluate the epidemiologic risk factors. Methods: Data regarding patients’ diabetic characteristics were recorded by the attending internal medicine clinician. Clinical examinations of patients’ toenails were performed by a dermatologist, and specimens were collected from the nails to establish the onycomycotic abnormality. All of the specimens were analyzed by direct microscopy and culture. Results: Of 321 patients with type 2 diabetes mellitus, clinical onychomycosis was diagnosed in 162; 41 of those diagnoses were confirmed mycologically. Of the isolated fungi, 23 were yeasts and 18 were dermatophytes. Significant correlations were found between the frequency of onychomycosis and retinopathy, neuropathy, obesity, family history, and duration of diabetes. However, no correlation was found with sex, age, educational level, occupation, area of residence, levels of hemoglobin A1c and fasting blood glucose, and nephropathy. The most frequently isolated agents from clinical specimens were yeasts. Conclusions: Long-term control of glycemia to prevent chronic complications and obesity and to promote education about the importance of foot and nail care should be essential components in preventing onychomycosis and its potential complications, such as secondary foot lesions, in patients with diabetes mellitus. (J Am Podiatr Med Assoc 101(1): 49–54, 2011)

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