[Management of cardiovascular diseases in patients with diabetes : ESC guidelines 2023]

Structured diabetes care routines in cardiac rehabilitation are associated with increased diabetes detection and improved treatment after myocardial infarction: a nationwide observational study

BACKGROUND

Despite the detrimental impact of abnormal glucose metabolism on cardiovascular prognosis after myocardial infarction (MI), diabetes is both underdiagnosed and undertreated. We investigated associations between structured diabetes care routines in cardiac rehabilitation (CR) and detection and treatment of diabetes at one-year post-MI.

METHODS

Center-level data was derived from the Perfect-CR survey, which evaluated work routines applied at Swedish CR centers (n = 76). Work routines involving diabetes care included: (1) routine assessment of fasting glucose and/or HbA1c, (2) routine use of oral glucose tolerance test (OGTT), (3) having regular case rounds with diabetologists, and (4) whether glucose-lowering medication was adjusted by CR physicians. Patient-level data was obtained from the national MI registry SWEDEHEART (n = 7601, 76% male, mean age 62.6 years) and included all post-MI patients irrespective of diabetes diagnosis. Using mixed-effects regression we estimated differences between patients exposed versus. not exposed to the four above-mentioned diabetes care routines. Outcomes were newly detected diabetes and the proportion of patients receiving oral glucose-lowering medication at one-year post-MI.

RESULTS

Routine assessment of fasting glucose/HbA1c was performed at 63.2% (n = 48) of the centers, while 38.2% (n = 29) reported using OGTT for detecting glucose abnormalities. Glucose-lowering medication adjusted by CR physicians (n = 13, 17.1%) or regular case rounds with diabetologists (n = 7, 9.2%) were less frequently reported. In total, 4.0% of all patients (n = 304) were diagnosed with diabetes during follow-up and 17.9% (n = 1361) were on oral glucose-lowering treatment one-year post-MI. Routine use of OGTT was associated with a higher rate of newly detected diabetes at one-year (risk ratio [95% confidence interval]: 1.62 [1.26, 1.98], p = 0.0007). At one-year a higher proportion of patients were receiving oral glucose-lowering medication at centers using OGTT (1.22 [1.07, 1.37], p = 0.0046) and where such medication was adjusted by CR physicians (1.31 [1.06, 1.56], p = 0.0155). Compared to having none of the structured diabetes care routines, the more routines implemented the higher the rate of newly detected diabetes (from 0 routines: 2.7% to 4 routines: 6.3%; p for trend = 0.0014).

CONCLUSIONS

Having structured routines for diabetes care implemented within CR can improve detection and treatment of diabetes post-MI. A cluster-randomized trial is warranted to ascertain causality.

Machine learning models for assessing risk factors affecting health care costs: 12-month exercise-based cardiac rehabilitation

Introduction

Exercise-based cardiac rehabilitation (ECR) has proven to be effective and cost-effective dominant treatment option in health care. However, the contribution of well-known risk factors for prognosis of coronary artery disease (CAD) to predict health care costs is not well recognized. Since machine learning (ML) applications are rapidly giving new opportunities to assist health care professionals' work, we used selected ML tools to assess the predictive value of defined risk factors for health care costs during 12-month ECR in patients with CAD.

Methods

The data for analysis was available from a total of 71 patients referred to Oulu University Hospital, Finland, due to an acute coronary syndrome (ACS) event (75% men, age 61 ± 12 years, BMI 27 ± 4 kg/m2, ejection fraction 62 ± 8, 89% have beta-blocker medication). Risk factors were assessed at the hospital immediately after the cardiac event, and health care costs for all reasons were collected from patient registers over a year. ECR was programmed in accordance with international guidelines. Risk analysis algorithms (cross-decomposition algorithms) were employed to rank risk factors based on variances in their effects. Regression analysis was used to determine the accounting value of risk factors by entering first the risk factor with the highest degree of explanation into the model. After that, the next most potent risk factor explaining costs was added to the model one by one (13 forecast models in total).

Results

The ECR group used health care services during the year at an average of 1,624 ± 2,139€ per patient. Diabetes exhibited the strongest correlation with health care expenses (r = 0.406), accounting for 16% of the total costs (p < 0.001). When the next two ranked markers (body mass index; r = 0.171 and systolic blood pressure; r = - 0.162, respectively) were added to the model, the predictive value was 18% for the costs (p = 0.004). The depression scale had the weakest independent explanation rate of all 13 risk factors (explanation value 0.1%, r = 0.029, p = 0.811).

Discussion

Presence of diabetes is the primary reason forecasting health care costs in 12-month ECR intervention among ACS patients. The ML tools may help decision-making when planning the optimal allocation of health care resources.

The double burden: type 1 diabetes and heart failure-a comprehensive review

Heart failure (HF) is increasing at an alarming rate, primary due to the rising in aging, obesity and diabetes. Notably, individuals with type 1 diabetes (T1D) face a significantly elevated risk of HF, leading to more hospitalizations and increased case fatality rates. Several risk factors contribute to HF in T1D, including poor glycemic control, female gender, smoking, hypertension, elevated BMI, and albuminuria. However, early and intensive glycemic control can mitigate the long-term risk of HF in individuals with T1D. The pathophysiology of diabetes-associated HF is complex and multifactorial, and the underlying mechanisms in T1D remain incompletely elucidated. In terms of treatment, much of the evidence comes from type 2 diabetes (T2D) populations, so applying it to T1D requires caution. Sodium-glucose cotransporter 2 inhibitors have shown benefits in HF outcomes, even in non-diabetic populations. However, most of the information about HF and the evidence from cardiovascular safety trials related to glucose lowering medications refer to T2D. Glycemic control is key, but the link between hypoglycemia and HF hospitalization risk requires further study. Glycemic variability, common in T1D, is an independent HF risk factor. Technological advances offer the potential to improve glycemic control, including glycemic variability, and may play a role in preventing HF. In summary, HF in T1D is a complex challenge with unique dimensions. This review focuses on HF in individuals with T1D, exploring its epidemiology, risk factors, pathophysiology, diagnosis and treatment, which is crucial for developing tailored prevention and management strategies for this population.

Effect of SGLT-2 inhibitor, dapagliflozin, on left ventricular remodeling in patients with type 2 diabetes and HFrEF

The current study evaluated the effect of SGLT-2 inhibitor, dapagliflozin, on left ventricular remodeling in patients with type 2 diabetes and HFrEF. 60 patients were randomized (1:1) to receive dapagliflozin 10 mg once daily, or placebo double blind for 1 year. Patients underwent transthoracic echocardiography and doppler evaluation prior to dapagliflozin initiation and at 1 year. At 1year, adjusted mean difference versus placebo in change from baseline in LVEF was 2.5% (95% CI: 1.00-4.06, P = 0.002). Adjusted mean difference versus placebo in change from baseline in LVED volume was - 6.0ml (95% CI: -8.07 --3.87, P<0.001). Adjusted mean difference versus placebo in change from baseline in LVES volume was - 8.1ml (95% CI: -11.07 --5.14, P<0.001). Similarly, adjusted mean difference versus placebo in change from baseline in LVED diameter was - 1.6 mm (95% CI: -2.67 --0.62, P = 0.002). Adjusted mean difference versus placebo in change from baseline in VTI was 0.20 cm (95% CI: 0.01-0.38, P = 0.036). Dapagliflozin was well tolerated. Dapagliflozin was associated with significant and clinically meaningful improvement in echocardiographic parameters versus placebo in patients with type 2 diabetes and HFrEF.Registration number and date: ChiCTR2300072707, 21/06/2023.

The Emerging Role of Prediabetes and Its Management: Focus on L-Arginine and a Survey in Clinical Practice

The worldwide impressive growth of metabolic disorders observed in the last decades, especially type 2 diabetes mellitus and obesity, has generated great interest in the potential benefits of early identification and management of patients at risk. In this view, prediabetes represents a high-risk condition for the development of type 2 diabetes mellitus and cardiovascular diseases, and an ideal target to intercept patients before they develop type 2 diabetes gaining a prominent role even in international guidelines. For prediabetic individuals, lifestyle modification is the cornerstone of diabetes prevention, with evidence of about 50% relative risk reduction. Accumulating data also show potential benefits from pharmacotherapy. In this context, the only available data pertain to metformin as a pharmaceutical drug and vitamin D and L-arginine as nutraceuticals. L-arginine appears to be a very interesting tool in the clinical management of patients with pre-diabetes. In this review we summarize the current knowledge on the role of L-arginine in prediabetes as a potentially useful preventive strategy against the progression to type 2 diabetes, with a particular focus on the underlying molecular mechanisms and the past and ongoing trials. In this article we also report the interesting data about the perception of the prediabetic condition and its therapeutic management in the clinical practice in Italy. An early identification and a prompt management of people with prediabetes appears to be of paramount importance to prevent the progression to diabetes and avoid its cardiovascular consequences.