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Background and Aims: Body adiposity is known to affect mortality risk in patients with coronary artery disease (CAD). We examined associations of body mass index (BMI) and waist circumference (WC) with long term mortality in Dutch CAD patients, and potential and effect modification of these associations by lifestyle and health determinants., Methods: 10,370 CAD patients (mean age ∼65 y; 20% female; >80% on cardiovascular drugs) from the prospective Alpha Omega Cohort and Utrecht Cardiovascular Cohort-Secondary Manifestations of ARTerial disease study were included. Cox models were used to estimate categorical and continuous associations (using restricted cubic splines) of measured BMI and WC with all-cause and cardiovascular mortality risk, adjusting for age, sex, smoking, alcohol, physical activity and educational level. Analyses were repeated in subgroups of lifestyle factors (smoking, physical activity, diet quality), education and health determinants (diabetes, self-rated health)., Results: During ∼10 years of follow-up (91,947 person-years), 3,553 deaths occurred, including 1,620 from cardiovascular disease. U-shaped relationships were found for BMI and mortality risk, with the lowest risk for overweight patients (BMI ∼27 kg/m2). For obesity (BMI ≥30), the HR for all-cause mortality was 1.31 (95% CI: 1.11, 1.41) in male patients and 1.10 (95% CI: 0.92, 1.30) in female patients, compared to BMI 25-30 kg/m2. WC was also non-linearly associated with mortality, and HRs were 1.18 (95%CI:1.06, 1.30) in males and 1.31 (95%CI:1.05, 1.64) in females for the highest vs. middle category of WC. Results for cardiovascular mortality were mostly in line with the results for all-cause mortality. U-shaped associations were found in most subgroups, associations were moderately modified by physical activity, smoking and educational level., Conclusions: CAD patients with obesity and a large WC were at increased risk of long-term CVD and all-cause mortality, while mildly overweight patients had the lowest risk. These associations were consistent across subgroups of patients with different lifestyles and health status., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Cruijsen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Most evidence on the relationship between sodium and potassium intake and cardiovascular disease originated from general population studies. This study aimed to evaluate the relation between estimated 24-hour sodium and potassium urinary excretion and the risk of recurrent vascular events and mortality in patients with vascular disease., Methods: 7561 patients with vascular disease enrolled in the UCC-SMART cohort (1996-2015) were included. Twenty-four hour sodium and potassium urinary excretion were estimated (Kawasaki formulae) from morning urine samples. Cox proportional hazard models with restricted cubic splines were used to evaluate the relation between estimated urinary salt excretion and major adverse cardiovascular events (MACE; including myocardial infarction, stroke, cardiovascular mortality) and all-cause mortality., Results: After a median follow-up of 7.4 years (interquartile range: 4.1-11.0), the relations between estimated 24-hour sodium urinary excretion and outcomes were J-shaped with nadirs of 4.59 gram/day for recurrent MACE and 4.97 gram/day for all-cause mortality. The relation between sodium-to-potassium excretion ratio and outcomes were also J-shaped with nadirs of 2.71 for recurrent MACE and 2.60 for all-cause mortality. Higher potassium urinary excretion was related to an increased risk of both recurrent MACE (HR 1.25 per gram potassium excretion per day; 95%CI 1.13-1.39) and all cause-mortality (HR 1.13 per gram potassium excretion per day; 95%CI 1.03-1.25)., Conclusions: In patients with established vascular disease, lower and higher sodium intake were associated with higher risk of recurrent MACE and all-cause mortality. Higher estimated 24-hour potassium urinary excretion was associated with a higher risk of recurrent MACE and all-cause mortality., Competing Interests: The authors have declared that no competing interests exist.

Objectives: The ankle brachial index (ABI) can be used to diagnose peripheral arterial disease (PAD). The clinical relevance of the ABI, especially in patients with known clinically manifest cardiovascular disease (CVD), is unknown. The authors set out to investigate the relationship between a screen-detected ABI and the risk for future cardiovascular morbidity and mortality in patients with clinically manifest CVD., Design, Materials and Methods: Patients with clinically manifest CVD were selected from the UCC-SMART cohort (n = 8360) and divided into four groups: normal ABI (0.91-1.39), screen-detected low ABI ≤ 0.9, screen-detected high ABI ≥ 1.4, and patients with known PAD irrespective of their ABI. Adjusted Cox Proportional Hazard Ratios (HRs) for Major Adverse Cardiovascular Events (MACE), Major Adverse Limb Events (MALE), and all-cause mortality were calculated. In addition, stratified analyses for women and men and for the presence of diabetes were performed., Results: During a median follow-up of 8.3 years (IQR 7.7) 1646 MACE, 601 MALE and 1958 all-cause mortalities were observed. Compared with normal ABI patients, patients with a screen-detected low ABI and patients with manifest PAD had a higher risk of MACE, MALE, and all-cause mortality with HRs of 1.9 (95% CI 1.6-2.2) for MACE, 7.6 (95% CI 5.7-10.1) for MALE, 1.7 (95% CI 1.5-2.0) for mortality and 1.3 (95% CI 1.2-1.5) for MACE, 13.8 (95% CI 11.1-17.1) for MALE, 1.7 (95% CI 1.5-1.9) for mortality, respectively. Screen-detected high ABI did not increase the risk of either MACE or MALE, however, was associated with lower risk of all-cause mortality with a HR of 0.6 (95% CI 0.5-0.9). Stratified analyses for women & men and for diabetes status were comparable for all three outcomes., Conclusions: In patients with manifest CVD but without PAD, a screen-detected low ABI is a powerful risk indicator for cardiovascular events, limb events, and all-cause mortality., Competing Interests: The authors have declared that no competing interests exist.

Aims: To compare the effectiveness of allopurinol with no treatment or placebo for the prevention of cardiovascular events in hyperuricemic patients., Methods and Results: Pubmed, Web of Science and Cochrane library were searched from inception until July 2020. Randomized controlled trials (RCT) and observational studies in hyperuricemic patients without significant renal disease and treated with allopurinol, versus placebo or no treatment were included. Outcome measures were cardiovascular mortality, myocardial infarction, stroke, or a combined endpoint (CM/MI/S). For RCT's a random effects meta-analysis was performed. For observational studies a narrative synthesis was performed. Of the original 1995 references we ultimately included 26 RCT's and 21 observational studies. We found a significantly reduced risk of combined endpoint (Risk Ratio 0.65 [95% CI] [0.46 to 0.91]; p = 0.012) and myocardial infarction (RR 0.47 [0.27 to 0.80]; p = 0.01) in the allopurinol group compared to controls. We found no significant effect of allopurinol on stroke or cardiovascular mortality. Of the 15 observational studies with sufficient quality, allopurinol was associated with reduced cardiovascular mortality in 1 out of 3 studies that reported this outcome, myocardial infarction in 6 out of 8, stroke in 4 out of 7, and combined end-point in 2 out of 2. Cardiovascular benefit was only observed when allopurinol therapy was prolonged for more than 6 months and when an appropriate allopurinol dose was administered (300 mg or more/day) or sufficient reduction of serum urate concentration was achieved (<0.36 mmol/l)., Conclusions: Data from RCT's and observational studies indicate that allopurinol treatment reduces cardiovascular risk in patients with hyperuricemia. However, the quality of evidence from RCTs is low to moderate. To establish whether allopurinol lowers the risk of cardiovascular events a well-designed and adequately powered randomized, placebo-controlled trial is needed in high-risk patients with hyperuricemia., Systematic Review Registration: PROSPERO registration CRD42018089744., Competing Interests: Dr. Cornel reports grants from ZonMw (LoDoCo 2 trial), personal fees from Amgen (advisory board), personal fees from Servier (advisory board), personal fees from Astra Zeneca (advisory board), outside the submitted work; All other authors declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background and Aims: The predictive value of traditional risk factors for vascular events in patients with manifest vascular disease is limited, underscoring the need for novel biomarkers to improve risk stratification. Since hematological parameters are routinely assessed in clinical practice, they are readily available candidates., Methods: We used data from 3,922 vascular patients, who participated in the Second Manifestations of ARTerial Disease (SMART) study. We first investigated associations between recurrent vascular events and 22 hematological parameters, obtained from the Utrecht Patient Oriented Database (UPOD), and then assessed whether parameters associated with outcome improved risk prediction., Results: After adjustment for all SMART risk score (SRS) variables, lymphocyte %, neutrophil count, neutrophil % and red cell distribution width (RDW) were significantly associated with vascular events. When individually added to the SRS, lymphocyte % improved prediction of recurrent vascular events with a continuous net reclassification improvement (cNRI) of 17.4% [95% CI: 2.1, 32.1%] and an increase in c-statistic of 0.011 [0.000, 0.022]. The combination of lymphocyte % and neutrophil count resulted in a cNRI of 22.2% [3.2, 33.4%] and improved c-statistic by 0.011 [95% CI: 0.000, 0.022]. Lymphocyte % and RDW yielded a cNRI of 18.7% [3.3, 31.9%] and improved c-statistic by 0.016 [0.004, 0.028]. However, the addition of hematological parameters only modestly increased risk estimates for patients with an event during follow-up., Conclusions: Several hematological parameters were independently associated with recurrent vascular events. Lymphocyte % alone and in combination with other parameters enhanced discrimination and reclassification. However, the incremental value for patients with a recurrent event was limited., Competing Interests: The authors have declared that no competing interests exist.

With the increased use of data not originally recorded for research, such as routine care data (or 'big data'), measurement error is bound to become an increasingly relevant problem in medical research. A common view among medical researchers on the influence of random measurement error (i.e. classical measurement error) is that its presence leads to some degree of systematic underestimation of studied exposure-outcome relations (i.e. attenuation of the effect estimate). For the common situation where the analysis involves at least one exposure and one confounder, we demonstrate that the direction of effect of random measurement error on the estimated exposure-outcome relations can be difficult to anticipate. Using three example studies on cardiovascular risk factors, we illustrate that random measurement error in the exposure and/or confounder can lead to underestimation as well as overestimation of exposure-outcome relations. We therefore advise medical researchers to refrain from making claims about the direction of effect of measurement error in their manuscripts, unless the appropriate inferential tools are used to study or alleviate the impact of measurement error from the analysis.