Trends in prognosis and use of SGLT2i and GLP-1 RA in patients with diabetes and coronary artery disease

OBJECTIVE

To explore trends in prognosis and use of glucose-lowering drugs (GLD) in patients with diabetes and coronary artery disease (CAD).

RESEARCH DESIGN AND METHODS

All patients with diabetes and CAD undergoing a coronary angiography between 2010 and 2021 according to the Swedish Angiography and Angioplasty Registry were included. Information on GLD (dispended 6 months before or after coronary angiography) was collected from the Swedish Prescribed Drug Registry. Data on major cardiovascular events (MACE; mortality, myocardial infarction, stroke, heart failure) through December 2021 were obtained from national registries. Cox proportional survival analysis was used to assess outcomes where cardioprotective GLD (any of Sodium Glucose Lowering Transport 2 receptor inhibitors [SGLT2i] and Glucagon Like Peptide Receptor Agonists [GLP-1 RA]) served as a reference.

RESULTS

Among all patients (n = 38,671), 31% had stable CAD, and 69% suffered an acute myocardial infarction. Mean age was 69 years, 67% were male, and 81% were on GLD. The use of cardioprotective GLD increased rapidly in recent years (2016-2021; 7-47%) and was more common in younger patients (66 vs. 68 years) and men (72.9% vs. 67.1%) than other GLD. Furthermore, compared with other GLD, the use of cardioprotective GLD was more common in patients with a less frequent history of heart failure (5.0% vs. 6.8%), myocardial infarction (7.7% vs. 10.5%) and chronic kidney disease (3.7% vs. 5.2%). The adjusted hazard ratio (HR) (95% CI) for MACE was greater in patients on other GLD than in those on cardioprotective GLD (1.10; 1.03-1.17, p = 0.004). Trend analyses for the years 2010-2019 revealed improved one-year MACE in patients with diabetes and CAD (year 2019 vs. 2010; 0.90; 0.81-1.00, p = 0.045), while 1-year mortality was unchanged.

CONCLUSIONS

The prescription pattern of diabetes medication is changing quickly in patients with diabetes and CAD; however, there are worrying signals of inefficient use prioritizing cardioprotective GLD to younger and healthier individuals at lower cardiovascular risk. Despite this, there are improving trends in 1-year morbidity.

Emerging opportunities to target inflammation: myocardial infarction and type 2 diabetes

After myocardial infarction (MI), patients with type 2 diabetes have an increased rate of adverse outcomes, compared to patients without. Diabetes confers a 1.5-2-fold increase in early mortality and, importantly, this discrepancy has been consistent over recent decades, despite advances in treatment and overall survival. Certain assumptions have emerged to explain this increased risk, such as differences in infarct size or coronary artery disease severity. Here, we re-evaluate that evidence and show how contemporary analyses using state-of-the-art characterization tools suggest that the received wisdom tells an incomplete story. Simultaneously, epidemiological and mechanistic biological data suggest additional factors relating to processes of diabetes-related inflammation might play a prominent role. Inflammatory processes after MI mediate injury and repair and are thus a potential therapeutic target. Recent studies have shown how diabetes affects immune cell numbers and drives changes in the bone marrow, leading to pro-inflammatory gene expression and functional suppression of healing and repair. Here, we review and re-evaluate the evidence around adverse prognosis in patients with diabetes after MI, with emphasis on how targeting processes of inflammation presents unexplored, yet valuable opportunities to improve cardiovascular outcomes in this vulnerable patient group.

Comparing and contrasting risk factors for heart failure in patients with and without history of myocardial infarction: data from HOMAGE and the UK Biobank

AIMS

Myocardial infarction (MI) is among the commonest attributable risk factors for heart failure (HF). We compared clinical characteristics associated with the progression to HF in patients with or without a history of MI in the HOMAGE cohort and validated our results in UK Biobank.

METHODS AND RESULTS

During a follow-up of 5.2 (3.5-5.9) years, 177 (2.4%) patients with prior MI and 370 (1.92%) patients without prior MI experienced HF onset in the HOMAGE cohort (n = 26 478, history of MI: n = 7241). Older age, male sex and higher heart rate were significant risk factors of HF onset in patients with and without prior MI. Lower renal function was more strongly associated with HF onset in patients with prior MI. Higher body mass index (BMI), systolic blood pressure and blood glucose were significantly associated with HF onset only in patients without prior MI (all p for interactions <0.05). In the UK Biobank (n = 500 001, history of MI: n = 4555), higher BMI, glycated haemoglobin, diabetes and hypertension had a stronger association with HF onset in participants without prior MI compared to participants with MI (all p for interactions <0.05).

CONCLUSION

The importance of clinical risk factors associated with HF onset is dependent on whether the patient has had a prior MI. Diabetes and hypertension are associated with new-onset HF only in the absence of MI history. Patients may benefit from targeted risk management based on MI history.

Effects of empagliflozin on insulin initiation or intensification in patients with type 2 diabetes and cardiovascular disease: Findings from the EMPA-REG OUTCOME trial

AIM

To evaluate the effects of empagliflozin versus placebo on subsequent insulin initiation or dosing changes in a large cardiovascular outcomes trial.

MATERIALS AND METHODS

In EMPA-REG OUTCOME, 7020 patients with type 2 diabetes and cardiovascular disease received empagliflozin 10 mg, 25 mg, or placebo. Median follow-up was 3.1 years. After 12 weeks of treatment, changes in background antihyperglycaemic therapy were permitted. Among insulin-naïve patients, we assessed the effects of pooled empagliflozin arms versus placebo on time to initiation of insulin. Among insulin-treated patients, we assessed effects on time to an increase or decrease in insulin dose of more than 20%.

RESULTS

In 3633 (52%) participants not treated with insulin at baseline, empagliflozin reduced new use of insulin versus placebo by 60% (7.1% vs. 16.4%; adjusted HR 0.40 [95% CI 0.32-0.49]; P < .0001). In 3387 (48%) patients using insulin at baseline, empagliflozin reduced the need for a greater than 20% insulin dose increase by 58% (14.4% vs. 29.3%; adjusted HR 0.42 [95% CI 0.36-0.49]; P < .0001) and increased the proportion achieving sustained greater than 20% insulin dose reductions without subsequent increases in HbA1c compared with placebo (9.2% vs. 4.9%; adjusted HR 1.87 [95% CI: 1.39-2.51]; P < .0001). Sensitivity analyses confirmed consistent findings when insulin dose changes of more than 10% or more than 30% were considered.

CONCLUSIONS

In patients with type 2 diabetes and cardiovascular disease, empagliflozin markedly and durably delays insulin initiation and substantial increases in insulin dose, while facilitating sustained reductions in insulin requirements over time.

Impact of Insulin Treatment on the Effect of Eplerenone: Insights From the EMPHASIS-HF Trial

BACKGROUND

Patients with heart failure with reduced ejection fraction (HFrEF) and insulin-treated diabetes have a high risk of cardiovascular complications. Mineralocorticoid receptor antagonists may mitigate this risk. We aim to explore the effect of eplerenone on cardiovascular outcomes and all-cause mortality in HFrEF patients with diabetes, including those treated with insulin in the EMPHASIS-HF trial (Eplerenone in Patients with Systolic Heart Failure and Mild Symptoms).

METHODS

The primary outcome was the composite of heart failure hospitalization or cardiovascular death. Cox models with treatment-by-diabetes subgroup interaction terms were used.

RESULTS

The median follow-up was 21 (10-33) months. Of the 2737 patients included, 623 (23%) had non-insulin-treated diabetes, 236 (9%) had insulin-treated diabetes and 1878 did not have diabetes. Patients with insulin-treated diabetes were younger, more often women, with higher body mass index, waist circumference, more frequent ischemic heart failure cause, impaired kidney function, and longer diabetes duration. Compared with patients without diabetes, those with insulin-treated diabetes had a 2-fold higher risk of having a primary outcome event. The hazard ratio (95% CI) for the effect of eplerenone, compared with placebo, on the primary outcome was 0.31 (0.19-0.50) in insulin-treated diabetes, 0.69 (0.50-0.93) in non-insulin-treated diabetes, and 0.72 (0.58-0.88) in patients without diabetes; interaction P=0.007. The annualized number needed-to-treat-to-benefit with regards to the primary outcome was 3 (95% CI, 3-4) in patients with insulin-treated diabetes, 16 (13-19) in patients with diabetes not receiving insulin, and 26 (24-28) in patients without diabetes.

CONCLUSIONS

Patients with insulin-treated diabetes experienced a greater benefit from eplerenone than those with diabetes not treated with insulin and people without diabetes. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00232180.

Assessment of quality indicators for acute myocardial infarction management in 28 countries and use of composite quality indicators for benchmarking

Background:

The European Society of Cardiology established a set of quality indicators for the management of acute myocardial infarction. Our aim was to evaluate their degree of attainment, prognostic value and potential use for centre benchmarking in a large international cohort.

Methods:

Quality indicators were extracted from the long-tErm follow-uP of antithrombotic management patterns In acute CORonary syndrome patients (EPICOR) (555 hospitals, 20 countries in Europe and Latin America, 2010–2011) and EPICOR Asia (218 hospitals, eight countries, 2011–2012) registries, including non-ST-segment elevation acute myocardial infarction (n=6558) and ST-segment elevation acute myocardial infarction (n=11,559) hospital survivors. The association between implementation rates for each quality indicator and two-year adjusted mortality was evaluated using adjusted Cox models. Composite quality indicators were categorized for benchmarking assessment at different levels.

Results:

The degree of attainment of the 17 evaluated quality indicators ranged from 13% to 100%. Attainment of most individual quality indicators was associated with two-year survival. A higher compliance with composite quality indicators was associated with lower mortality at centre-, country- and region-level. Moreover, the higher the risk for two-year mortality, the lower the compliance with composite quality indicators.

Conclusions:

When EPICOR and EPICOR Asia were conducted, the European Society of Cardiology quality indicators would have been attained to a limited extent, suggesting wide room for improvement in the management of acute myocardial infarction patients. After adjustment for confounding, most quality indicators were associated with reduced two-year mortality and their prognostic value should receive further attention. The two composite quality indicators can be used as a tool for benchmarking either at centre-, country- or world region-level.

Diabetes, metformin and glucose lowering therapies after myocardial infarction: Insights from the SWEDEHEART registry

OBJECTIVE

To explore real-life use of glucose lowering drugs and prognosis after acute myocardial infarction (AMI) with a special focus on metformin.

METHODS

Patients (n = 70270) admitted for AMI 2012-2017 were stratified by diabetes status and glucose lowering treatment and followed for mortality and MACE+ (AMI, heart failure (HF), stroke, mortality) until end of 2017 (mean follow-up time 3.4 ± 1.4 years) through linkage with national registries and SWEDEHEART. Hazard ratios (HR) were calculated in adjusted Cox proportional hazard regression models.

RESULTS

Mean age was 68 ± 11 years and 70% were male. Of patients with diabetes (n = 16356; 23%), a majority had at least one glucose lowering drug (81%) of whom 51% had metformin (24% monotherapy), 43% insulin and a minority any SGLT2i/GLP-1 RA (5%). Adjusted HR for patients with versus without diabetes was 1.31 (95% CI 1.27-1.36) for MACE+ and 1.48 (1.41-1.56) for mortality. Adjusted HR for MACE+ for diabetes patients on metformin was 0.92 (0.85-0.997), p = 0.042 compared to diet treated diabetes.

CONCLUSION

Diabetes still implies a high complication risk after AMI. Metformin and insulin were the most common treatment used in almost half of the diabetes population. Furthermore, patients treated with metformin had a lower cardiovascular risk after AMI and needs to be confirmed in prospective controlled trials.

MEESSI-AHF risk score performance to predict multiple post-index event and post-discharge short-term outcomes

BACKGROUND

The multiple estimation of risk based on the emergency department Spanish score in patients with acute heart failure (MEESSI-AHF) is a risk score designed to predict 30-day mortality in acute heart failure patients admitted to the emergency department. Using a derivation cohort, we evaluated the performance of the MEESSI-AHF risk score to predict 11 different short-term outcomes.

METHODS

Patients with acute heart failure from 41 Spanish emergency departments (n=7755) were recruited consecutively in two time periods (2014 and 2016). Logistic regression models based on the MEESSI-AHF risk score were used to obtain c-statistics for 11 outcomes: three with follow-up from emergency department admission (inhospital, 7-day and 30-day mortality) and eight with follow-up from discharge (7-day mortality, emergency department revisit and their combination; and 30-day mortality, hospital admission, emergency department revisit and their two combinations with mortality).

RESULTS

The MEESSI-AHF risk score strongly predicted mortality outcomes with follow-up starting at emergency department admission (c-statistic 0.83 for 30-day mortality; 0.82 for inhospital death, P=0.121; and 0.85 for 7-day mortality, P=0.001). Overall, mortality outcomes with follow-up starting at hospital discharge predicted slightly less well (c-statistic 0.80 for 7-day mortality, P=0.011; and 0.75 for 30-day mortality, P<0.001). In contrast, the MEESSI-AHF score predicted poorly outcomes involving emergency department revisit or hospital admission alone or combined with mortality (c-statistics 0.54 to 0.62).

CONCLUSIONS

The MEESSI-AHF risk score strongly predicts mortality outcomes in acute heart failure patients admitted to the emergency department, but the model performs poorly for outcomes involving hospital admission or emergency department revisit. There is a need to optimise this risk score to predict non-fatal events more effectively.

Impact of previous coronary artery bypass grafting in patients presenting with an acute coronary syndrome: Current trends and clinical implications

BACKGROUND

Among patients presenting with an acute coronary syndrome, those with previous coronary artery bypass grafting are a particular subset.

AIMS

The purpose of this study was to investigate the prognostic impact of previous coronary artery bypass grafting in acute coronary syndrome patients and to identify the current trends in their clinical management.

METHODS

We performed a cohort analysis of patients prospectively enrolled in the Portuguese Registry of acute coronary syndrome between 2010-2019 with known previous coronary artery bypass grafting status. The co-primary endpoints were in-hospital and one-year mortality.

RESULTS

A total of 19,334 (962 coronary artery bypass grafting and 18,372 non-coronary artery bypass grafting) and 9402 (479 coronary artery bypass grafting and 8923 non-coronary artery bypass grafting) patients were included in the analyses of in-hospital and mid-term outcomes, respectively. Coronary artery bypass grafting patients were older and had a higher incidence of comorbidities. They were less likely to undergo invasive angiography (74.9 vs 84.6%, p<0.001), but were equally likely to receive dual antiplatelet therapy (91.0 vs 90.8%, p=0.823). In-hospital mortality was similar between groups (3.6 vs 3.4%, p=0.722). Unadjusted one-year mortality was higher in the coronary artery bypass grafting group (hazard ratio 1.48, 95% confidence interval 1.09-2.01, p=0.012), but similar in both groups after propensity-matching and multivariate analysis (hazard ratio 0.63, 95% confidence interval 0.37-1.09, p=0.098).

CONCLUSIONS

Among patients with acute coronary syndrome, a previous history of coronary artery bypass grafting was associated with a high burden of comorbidities and a high-risk profile but was not an independent predictor of adverse events. Treatment decisions should be made on a case-by-case basis, and should not be based on previous coronary artery bypass grafting status alone.

Heart failure with insulin degludec versus glargine U100 in patients with type 2 diabetes at high risk of cardiovascular disease: DEVOTE 14

Background

Heart failure (HF) is a common cardiovascular complication of type 2 diabetes (T2D). This secondary analysis investigated baseline factors and treatment differences associated with risk of hospitalization for HF (hHF), and the possible association between severe hypoglycemia and hHF.

Methods

DEVOTE was a treat-to-target, double-blind cardiovascular outcomes trial in patients (n = 7637) with T2D and high cardiovascular risk randomized to insulin degludec (degludec) or insulin glargine 100 units/mL (glargine U100). The main endpoint of this secondary analysis was time to first hHF (standardized MedDRA Query definition). Severe hypoglycemia was adjudicated (American Diabetes Association definition). The main endpoint and the temporal association between severe hypoglycemia and hHF were analyzed with a Cox proportional hazards regression model. Predictors of time to first hHF were identified using baseline variables.

Results

Overall, 372 (4.9%) patients experienced hHF (550 events). There was no significant difference in the risk of hHF between treatments (hazard ratio [HR] 0.88 [0.72;1.08]_{95% CI}, p = 0.227). Prior HF (HR 4.89 [3.90;6.14]_{95% CI}, p ≤ 0.0001) was the strongest predictor of future hHF events. The risk of hHF significantly increased after (HR 2.2), and within a week after (HR 11.1), experiencing a severe hypoglycemic episode compared with before an episode.

Conclusions

In patients with T2D and high cardiovascular risk there were no treatment differences in terms of hHF. Prior HF was the strongest predictor of future hHF events, and there was an association between severe hypoglycemia and subsequent hHF. Further research should evaluate whether the risk of hHF can be modified by treatments aimed at reducing hypoglycemia.

Trial Registration NCT01959529

Editor's Choice- Impact of identifying precipitating factors on 30-day mortality in acute heart failure patients

BACKGROUND

The aim of this study was to describe the prevalence and prognostic value of the most common triggering factors in acute heart failure.

METHODS

Patients with acute heart failure from 41 Spanish emergency departments were recruited consecutively in three time periods between 2011 and 2016. Precipitating factors were classified as: (a) unrecognized; (b) infection; (c) atrial fibrillation; (d) anaemia; (e) hypertension; (f) acute coronary syndrome; (g) non-adherence; and (h) two or more precipitant factors. Unadjusted and adjusted logistic regression models were used to assess the association between 30-day mortality and each precipitant factor. The risk of dying was further evaluated by week intervals over the 30-day follow-up to assess the period of higher vulnerability for each precipitant factor.

RESULTS

Approximately 69% of our 9999 patients presented with a triggering factor and 1002 died within the first 30 days (10.0%). The most prevalent factors were infection and atrial fibrillation. After adjusting for 11 known predictors, acute coronary syndrome was associated with higher 30-day mortality (odds ratio (OR) 1.87; 95% confidence interval (CI) 1.02-3.42), whereas atrial fibrillation (OR 0.75; 95% CI 0.56-0.94) and hypertension (OR 0.34; 95% CI 0.21-0.55) were significantly associated with better outcomes when compared to patients without precipitant. Patients with infection, anaemia and non-compliance were not at higher risk of dying within 30 days. These findings were consistent across gender and age groups. The 30-day mortality time pattern varied between and within precipitant factors.

CONCLUSIONS

Precipitant factors in acute heart failure patients are prevalent and have a prognostic value regardless of the patient's gender and age. They can be managed with specific treatments and can sometimes be prevented.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)

Risk assessment have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of – usually interactive and online available – tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Type 2 diabetes mellitus increases long-term mortality risk after isolated surgical aortic valve replacement

BACKGROUND

Diabetes mellitus (DM) adversely affects morbidity and mortality for major atherosclerosis-related cardiovascular diseases and is associated with increased risk for the development of aortic stenosis. Clinical data regarding the impact of DM on outcomes of patients undergoing aortic valve replacement (AVR) have revealed inconsistent results. The aim of the current study was to investigate and compare the impact of type 2 DM on short-, intermediate- and long-term mortality between DM and non-DM patients who undergo isolated AVR.

METHODS

We performed an observational study in a large tertiary medical center over a 14-year period (2004-2018), which included all patients who had undergone isolated AVR surgery for the first time. Of the 1053 study patients, 346 patients (33%) had type 2 DM (DM group) and were compared with non-DM (non-DM group) patients (67%). Short-term (in-hospital), intermediate (1- and 3-years), and late (5- and 10-years) mortality were evaluated. Mean follow-up of was 69 ± 43 months.

RESULTS

Short-term (in-hospital) mortality was similar between the DM compared with the non-DM group: 3.5% and 2.5% (p = 0.517). Intermediate-term mortality (1- and 3-year) was higher in the DM group compared with the non-DM group, but did not reach statistical significance: 8.1% vs. 5.7% (p = 0.169) and 12.1% vs. 8.3% (p = 0.064) respectively. Long-term (5- and 10-year) mortality was significantly higher in the DM group, compared to the non-DM group: 19.4% vs. 12.9% (p = 0.007) and 30.3% vs. 23.5% (p = 0.020) respectively. Among the 346 DM patients, 55 (16%) were treated with insulin and 291 (84%) with oral antiglycemic medication only. Overall in-hospital mortality among insulin-treated DM patients was 7.3% compared with 2.7% among non insulin-treated DM patients (p = 0.201). Long-term mortality was higher in the subgroup of insulin-treated DM patients compared with the subgroup of non-insulin treated DM patients with an overall mortality rate of 36.4% vs. 29.2% (p = 0.039). Furthermore, predictors for late mortality included DM (HR 1.39 CI 1.03-1.86, p = 0.031) and insulin treatment (HR 1.76 CI 1.05-2.94, p = 0.033), as demonstrated after adjustment for confounders by multivariable analysis.

CONCLUSIONS

Type 2 DM is an independent predictor for long-term mortality after isolated AVR surgery.