Background—Preeclampsia is a pregnancy-specific disorder resulting in hypertension and multiorgan dysfunction. There is growing evidence that these effects persist after pregnancy. We aimed to systematically evaluate and quantify the evidence on the relationship between preeclampsia and the future risk of cardiovascular diseases. Methods and Results—We studied the future risk of heart failure, coronary heart disease, composite cardiovascular disease, death because of coronary heart or cardiovascular disease, stroke, and stroke death after preeclampsia. A systematic search of MEDLINE and EMBASE was performed to identify relevant studies. We used random-effects meta-analysis to determine the risk. Twenty-two studies were identified with >6.4 million women including >258 000 women with preeclampsia. Meta-analysis of studies that adjusted for potential confounders demonstrated that preeclampsia was independently associated with an increased risk of future heart failure (risk ratio [RR], 4.19; 95% confidence interval [CI], 2.09–8.38), coronary heart disease (RR, 2.50; 95% CI, 1.43–4.37), cardiovascular disease death (RR, 2.21; 95% CI, 1.83–2.66), and stroke (RR, 1.81; 95% CI, 1.29–2.55). Sensitivity analyses showed that preeclampsia continued to be associated with an increased risk of future coronary heart disease, heart failure, and stroke after adjusting for age (RR, 3.89; 95% CI, 1.83–8.26), body mass index (RR, 3.16; 95% CI, 1.41–7.07), and diabetes mellitus (RR, 4.19; 95% CI, 2.09–8.38). Conclusions—Preeclampsia is associated with a 4-fold increase in future incident heart failure and a 2-fold increased risk in coronary heart disease, stroke, and death because of coronary heart or cardiovascular disease. Our study highlights the importance of lifelong monitoring of cardiovascular risk factors in women with a history of preeclampsia.

Aims: The prediction of future trends in cardiovascular disease (CVD) mortality and their risk factors can assist policy-makers in healthcare planning. This study aims to project geospatial trends in CVDs and their underlying risk factors from 2025 to 2050. Methods and results: Using historical data on mortality and disability-adjusted life years (DALYs) from the Global Burden of Disease (GBD) 2019 study, encompassing the period of 1990 to 2019, Poisson regression was performed to model mortality and DALYs associated with CVD and its associated risk factors from 2025 to 2050. Subgroup analysis was based on GBD super-regions. Between 2025 and 2050, a 90.0% increase in cardiovascular prevalence, 73.4% increase in crude mortality, and 54.7% increase in crude DALYs are projected, with an expected 35.6 million cardiovascular deaths in 2050 (from 20.5 million in 2025). However, age-standardized cardiovascular prevalence will be relatively constant (−3.6%), with decreasing age-standardized mortality (−30.5%) and age-standardized DALYs (−29.6%). In 2050, ischaemic heart disease will remain the leading cause of cardiovascular deaths (20 million deaths) while high systolic blood pressure will be the main cardiovascular risk factor driving mortality (18.9 million deaths). Central Europe, Eastern Europe, and Central Asia super-region is set to incur the highest age-standardized cardiovascular mortality rate in 2050 (305 deaths per 100 000 population). Conclusion: In the coming decades, the relatively constant age-standardized prevalence of global CVD suggests that the net effect of summative preventative efforts will likely continue to be unchanged. The fall in age-standardized cardiovascular mortality reflects the improvement in medical care following diagnosis. However, future healthcare systems can expect a rapid rise in crude cardiovascular mortality, driven by the ageing global populace. The continued rise in CVD burden will largely be attributed to atherosclerotic diseases. Registration: Not applicable.

The coexistence of type 2 diabetes mellitus (T2DM) and heart failure (HF), either with reduced (HFrEF) or preserved ejection fraction (HFpEF), is frequent (30–40% of patients) and associated with a higher risk of HF hospitalization, all-cause and cardiovascular (CV) mortality. The most important causes of HF in T2DM are coronary artery disease, arterial hypertension and a direct detrimental effect of T2DM on the myocardium. T2DM is often unrecognized in HF patients, and vice versa, which emphasizes the importance of an active search for both disorders in the clinical practice. There are no specific limitations to HF treatment in T2DM. Subanalyses of trials addressing HF treatment in the general population have shown that all HF therapies are similarly effective regardless of T2DM. Concerning T2DM treatment in HF patients, most guidelines currently recommend metformin as the first-line choice. Sulphonylureas and insulin have been the traditional second- and third-line therapies although their safety in HF is equivocal. Neither glucagon-like preptide-1 (GLP-1) receptor agonists, nor dipeptidyl peptidase-4 (DPP4) inhibitors reduce the risk for HF hospitalization. Indeed, a DPP4 inhibitor, saxagliptin, has been associated with a higher risk of HF hospitalization. Thiazolidinediones (pioglitazone and rosiglitazone) are contraindicated in patients with (or at risk of) HF. In recent trials, sodium–glucose co-transporter-2 (SGLT2) inhibitors, empagliflozin and canagliflozin, have both shown a significant reduction in HF hospitalization in patients with established CV disease or at risk of CV disease. Several ongoing trials should provide an insight into the effectiveness of SGLT2 inhibitors in patients with HFrEF and HFpEF in the absence of T2DM.

OBJECTIVE Glycemic variability is emerging as a measure of glycemic control, which may be a reliable predictor of complications. This systematic review and meta-analysis evaluates the association between HbA_1c variability and micro- and macrovascular complications and mortality in type 1 and type 2 diabetes. RESEARCH DESIGN AND METHODS Medline and Embase were searched (2004–2015) for studies describing associations between HbA_1c variability and adverse outcomes in patients with type 1 and type 2 diabetes. Data extraction was performed independently by two reviewers. Random-effects meta-analysis was performed with stratification according to the measure of HbA_1c variability, method of analysis, and diabetes type. RESULTS Seven studies evaluated HbA_1c variability among patients with type 1 diabetes and showed an association of HbA_1c variability with renal disease (risk ratio 1.56 [95% CI 1.08–2.25], two studies), cardiovascular events (1.98 [1.39–2.82]), and retinopathy (2.11 [1.54–2.89]). Thirteen studies evaluated HbA_1c variability among patients with type 2 diabetes. Higher HbA_1c variability was associated with higher risk of renal disease (1.34 [1.15–1.57], two studies), macrovascular events (1.21 [1.06–1.38]), ulceration/gangrene (1.50 [1.06–2.12]), cardiovascular disease (1.27 [1.15–1.40]), and mortality (1.34 [1.18–1.53]). Most studies were retrospective with lack of adjustment for potential confounders, and inconsistency existed in the definition of HbA_1c variability. CONCLUSIONS HbA_1c variability was positively associated with micro- and macrovascular complications and mortality independently of the HbA_1c level and might play a future role in clinical risk assessment.

Background: There is growing evidence that sleep duration and quality may be associated with cardiovascular harm and mortality. Methods and Results: We conducted a systematic review, meta‐analysis, and spline analysis of prospective cohort studies that evaluate the association between sleep duration and quality and cardiovascular outcomes. We searched MEDLINE and EMBASE for these studies and extracted data from identified studies. We utilized linear and nonlinear dose‐response meta‐analysis models and used DerSimonian–Laird random‐effects meta‐analysis models of risk ratios, with inverse variance weighting, and the I ² statistic to quantify heterogeneity. Seventy‐four studies including 3 340 684 participants with 242 240 deaths among 2 564 029 participants who reported death events were reviewed. Findings were broadly similar across both linear and nonlinear dose‐response models in 30 studies with >1 000 000 participants, and we report results from the linear model. Self‐reported duration of sleep >8 hours was associated with a moderate increased risk of all‐cause mortality, with risk ratio , 1.14 (1.05–1.25) for 9 hours, risk ratio, 1.30 (1.19–1.42) for 10 hours, and risk ratio, 1.47 (1.33–1.64) for 11 hours. No significant difference was identified for periods of self‐reported sleep <7 hours, whereas similar patterns were observed for stroke and cardiovascular disease mortality. Subjective poor sleep quality was associated with coronary heart disease (risk ratio , 1.44; 95% confidence interval, 1.09–1.90), but no difference in mortality and other outcomes. Conclusions: Divergence from the recommended 7 to 8 hours of sleep is associated with a higher risk of mortality and cardiovascular events. Longer duration of sleep may be more associated with adverse outcomes compared with shorter sleep durations.