Risk of cancer after ST-segment-elevation myocardial infarction.

Analyses from administrative databases have suggested an increased cancer incidence among individuals who experienced a myocardial infarction, especially within the first 6 months. It remains unclear to what extent this represents an underlying biological link, or can be explained by detection of pre-symptomatic cancers and shared risk factors. Cancer incidence among 1809 consecutive patients surviving hospitalization for thrombotic ST-segment-elevation myocardial infarction (STEMI; mean age 62.6 years; 26% women; 115 incident cancers) was compared to the cancer incidence among 10,052 individuals of the general population (Rotterdam Study; mean age 63.1 years; 57% women; 677 incident cancers). Pathology-confirmed cancer diagnoses were obtained through identical linkage of both cohorts with the Netherlands Cancer Registry. Cox models were used to obtain hazards ratios (HRs) adjusted for factors associated with both atherosclerosis and cancer. Over 5-year follow-up, there was no significant difference in the incidence of cancer between STEMI patients and the general population (HR 0.96, 95% CI 0.78-1.19). In the first 3 months after STEMI, cancer incidence was markedly higher among STEMI patients compared to the general population (HR 2.45, 95% CI 1.13-5.30), which gradually dissolved during follow-up (P-for-trend 0.004). Among STEMI patients, higher C-reactive protein, higher platelet counts, and lower hemoglobin were associated with cancer incidence during the first year after STEMI (HRs 2.93 for C-reactive protein > 10 mg/dL, 2.10 for platelet count > 300*109, and 3.92 for hemoglobin < 7.5 mmol/L). Although rare, thrombotic STEMI might be a paraneoplastic manifestation of yet to be diagnosed cancer, and is hallmarked by a pro-inflammatory status and anemia.Trial registration Registered into the Netherlands National Trial Register and WHO International Clinical Trials Registry Platform under shared catalogue number NTR6831.

Prevalence and determinants of healthcare avoidance during the COVID-19 pandemic: A population-based cross-sectional study.

BACKGROUND: During the Coronavirus Disease 2019 (COVID-19) pandemic, the number of consultations and diagnoses in primary care and referrals to specialist care declined substantially compared to prepandemic levels. Beyond deferral of elective non-COVID-19 care by healthcare providers, it is unclear to what extent healthcare avoidance by community-dwelling individuals contributed to this decline in routine healthcare utilisation. Moreover, it is uncertain which specific symptoms were left unheeded by patients and which determinants predispose to healthcare avoidance in the general population. In this cross-sectional study, we assessed prevalence of healthcare avoidance during the pandemic from a patient perspective, including symptoms that were left unheeded, as well as determinants of healthcare avoidance. METHODS AND FINDINGS: On April 20, 2020, a paper COVID-19 survey addressing healthcare utilisation, socioeconomic factors, mental and physical health, medication use, and COVID-19-specific symptoms was sent out to 8,732 participants from the population-based Rotterdam Study (response rate 73%). All questionnaires were returned before July 10, 2020. By hand, prevalence of healthcare avoidance was subsequently verified through free text analysis of medical records of general practitioners. Odds ratios (ORs) for avoidance were determined using logistic regression models, adjusted for age, sex, and history of chronic diseases. We found that 1,142 of 5,656 included participants (20.2%) reported having avoided healthcare. Of those, 414 participants (36.3%) reported symptoms that potentially warranted urgent evaluation, including limb weakness (13.6%), palpitations (10.8%), and chest pain (10.2%). Determinants related to avoidance were older age (adjusted OR 1.14 [95% confidence interval (CI) 1.08 to 1.21]), female sex (1.58 [1.38 to 1.82]), low educational level (primary education versus higher vocational/university 1.21 [1.01 to 1.46), poor self-appreciated health (per level decrease 2.00 [1.80 to 2.22]), unemployment (versus employed 2.29 [1.54 to 3.39]), smoking (1.34 [1.08 to 1.65]), concern about contracting COVID-19 (per level increase 1.28 [1.19 to 1.38]) and symptoms of depression (per point increase 1.13 [1.11 to 1.14]) and anxiety (per point increase 1.16 [1.14 to 1.18]). Study limitations included uncertainty about (perceived) severity of the reported symptoms and potentially limited generalisability given the ethnically homogeneous study population. CONCLUSIONS: In this population-based cross-sectional study, 1 in 5 individuals avoided healthcare during lockdown in the COVID-19 pandemic, often for potentially urgent symptoms. Healthcare avoidance was strongly associated with female sex, fragile self-appreciated health, and high levels of depression and anxiety. These results emphasise the need for targeted public education urging these vulnerable patients to timely seek medical care for their symptoms to mitigate major health consequences.

Lifetime risk and multimorbidity of non-communicable diseases and disease-free life expectancy in the general population: A population-based cohort study.

BACKGROUND: Non-communicable diseases (NCDs) are leading causes of premature disability and death worldwide. However, the lifetime risk of developing any NCD is unknown, as are the effects of shared common risk factors on this risk. METHODS AND FINDINGS: Between July 6, 1989, and January 1, 2012, we followed participants from the prospective Rotterdam Study aged 45 years and older who were free from NCDs at baseline for incident stroke, heart disease, diabetes, chronic respiratory disease, cancer, and neurodegenerative disease. We quantified occurrence/co-occurrence and remaining lifetime risk of any NCD in a competing risk framework. We additionally studied the lifetime risk of any NCD, age at onset, and overall life expectancy for strata of 3 shared risk factors at baseline: smoking, hypertension, and overweight. During 75,354 person-years of follow-up from a total of 9,061 participants (mean age 63.9 years, 60.1% women), 814 participants were diagnosed with stroke, 1,571 with heart disease, 625 with diabetes, 1,004 with chronic respiratory disease, 1,538 with cancer, and 1,065 with neurodegenerative disease. NCDs tended to co-occur substantially, with 1,563 participants (33.7% of those who developed any NCD) diagnosed with multiple diseases during follow-up. The lifetime risk of any NCD from the age of 45 years onwards was 94.0% (95% CI 92.9%-95.1%) for men and 92.8% (95% CI 91.8%-93.8%) for women. These risks remained high (>90.0%) even for those without the 3 risk factors of smoking, hypertension, and overweight. Absence of smoking, hypertension, and overweight was associated with a 9.0-year delay (95% CI 6.3-11.6) in the age at onset of any NCD. Furthermore, the overall life expectancy for participants without these risk factors was 6.0 years (95% CI 5.2-6.8) longer than for those with all 3 risk factors. Participants aged 45 years and older without the 3 risk factors of smoking, hypertension, and overweight at baseline spent 21.6% of their remaining lifetime with 1 or more NCDs, compared to 31.8% of their remaining life for participants with all of these risk factors at baseline. This difference corresponds to a 2-year compression of morbidity of NCDs. Limitations of this study include potential residual confounding, unmeasured changes in risk factor profiles during follow-up, and potentially limited generalisability to different healthcare settings and populations not of European descent. CONCLUSIONS: Our study suggests that in this western European community, 9 out of 10 individuals aged 45 years and older develop an NCD during their remaining lifetime. Among those individuals who develop an NCD, at least a third are subsequently diagnosed with multiple NCDs. Absence of 3 common shared risk factors is associated with compression of morbidity of NCDs. These findings underscore the importance of avoidance of these common shared risk factors to reduce the premature morbidity and mortality attributable to NCDs.

Leveraging the coronary calcium scan beyond the coronary calcium score.

Non-contrast cardiac computed tomography in order to obtain the coronary artery calcium score has become an established diagnostic procedure in the clinical setting, and is commonly employed in clinical and population-based research. This state-of-the-art review paper highlights the potential gain in information that can be obtained from the non-contrast coronary calcium scans without any necessary modifications to the scan protocol. This includes markers of cardio-metabolic health, such as the amount of epicardial fat and liver fat, but also markers of general health including bone density and lung density. Finally, this paper addresses the importance of incidental findings and of radiation exposure accompanying imaging with non-contrast cardiac computed tomography. Despite the fact that coronary calcium scan protocols have been optimized for the visualization of coronary calcification in terms image quality and radiation exposure, it is important for radiologists, cardiologists and medical specialists in the field of preventive medicine to acknowledge that numerous additional markers of cardio-metabolic health and general health can be readily identified on a coronary calcium scan. KEY POINTS: • The coronary artery calcium score substantially increased the use of cardiac CT. • Cardio-metabolic and general health markers may be derived without changes to the scan protocol. • Those include epicardial fat, aortic valve calcifications, liver fat, bone density, and lung density. • Clinicians must be aware of this potential additional yield from non-contrast cardiac CT.

Carotid Intima-Media Thickness and Arterial Stiffness and the Risk of Atrial Fibrillation: The Atherosclerosis Risk in Communities (ARIC) Study, Multi-Ethnic Study of Atherosclerosis (MESA), and the Rotterdam Study.

BACKGROUND: We evaluated the association of carotid intima-media thickness (cIMT), carotid plaque, carotid distensibility coefficient (DC), and aortic pulse wave velocity (PWV) with incident atrial fibrillation (AF) and their role in improving AF risk prediction beyond the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF risk score. METHODS AND RESULTS: We analyzed data from 3 population-based cohort studies: Atherosclerosis Risk in Communities (ARIC) Study (n=13 907); Multi-Ethnic Study of Atherosclerosis (MESA; n=6640), and the Rotterdam Study (RS; n=5220). We evaluated the association of arterial indices with incident AF and computed the C-statistic, category-based net reclassification improvement (NRI), and relative integrated discrimination improvement (IDI) of incorporating arterial indices into the CHARGE-AF risk score (age, race, height weight, systolic and diastolic blood pressure, antihypertensive medication use, smoking, diabetes, previous myocardial infarction, and previous heart failure). Higher cIMT (meta-analyzed hazard ratio [95% CI] per 1-SD increment, 1.12 [1.08-1.16]) and presence of carotid plaque (1.30 [1.19-1.42]) were associated with higher AF incidence after adjustment for CHARGE-AF risk-score variables. Lower DC and higher PWV were associated with higher AF incidence only after adjustment for the CHARGE-AF risk-score variables excepting height, weight, and systolic and diastolic blood pressure. Addition of cIMT or carotid plaque marginally improved CHARGE-AF score prediction as assessed by the relative IDI (estimates, 0.025-0.051), but not when assessed with the C-statistic and NRI. CONCLUSIONS: Higher cIMT, presence of carotid plaque, and greater arterial stiffness are associated with higher AF incidence, indicating that atherosclerosis and arterial stiffness play a role in AF etiopathogenesis. However, arterial indices only modestly improve AF risk prediction.

Association Between Mind-Body Practice and Cardiometabolic Risk Factors: The Rotterdam Study.

OBJECTIVES: The increased popularity of mind-body practices highlights the need to explore their potential effects. We determined the cross-sectional association between mind-body practices and cardiometabolic risk factors. METHODS: We used data from 2579 participants free of cardiovascular disease from the Rotterdam Study (2009-2013). A structured home-based interview was used to evaluate engagement in mind-body practices including meditation, yoga, self-prayer, breathing exercises, or other forms of mind-body practice. We regressed engagement in mind-body practices on cardiometabolic risk factors (body mass index, blood pressure, and fasting blood levels of cholesterol, triglycerides, and glucose) and presence of metabolic syndrome. All analyses were adjusted for age, sex, educational level, smoking, alcohol consumption, (in)activities in daily living, grief, and depressive symptoms. RESULTS: Fifteen percent of the participants engaged in a form of mind-body practice. Those who did mind-body practices had significantly lower body mass index (ß = -0.84 kg/m, 95% confidence interval [CI] = -1.30 to -0.38, p < .001), log-transformed triglyceride levels (ß = -0.02, 95% CI = -0.04 to -0.001, p = .037), and log-transformed fasting glucose levels (ß = -0.01, 95% CI = -0.02 to -0.004, p = .004). Metabolic syndrome was less common among individuals who engaged in mind-body practices (odds ratio = 0.71, 95% CI = 0.54-0.95, p = .019). CONCLUSIONS: Individuals who do mind-body practices have a favorable cardiometabolic risk profile compared with those who do not. However, the cross-sectional design of this study does not allow for causal inference and prospective, and intervention studies are needed to elucidate the association between mind-body practices and cardiometabolic processes.

Evaluation of newer risk markers for coronary heart disease risk classification: a cohort study.

BACKGROUND: Whether newer risk markers for coronary heart disease (CHD) improve CHD risk prediction remains unclear. OBJECTIVE: To assess whether newer risk markers for CHD risk prediction and stratification improve Framingham risk score (FRS) predictions. DESIGN: Prospective population-based study. SETTING: The Rotterdam Study, Rotterdam, the Netherlands. PARTICIPANTS: 5933 asymptomatic, community-dwelling participants (mean age, 69.1 years [SD, 8.5]). MEASUREMENTS: Traditional CHD risk factors used in the FRS (age, sex, systolic blood pressure, treatment of hypertension, total and high-density lipoprotein cholesterol levels, smoking, and diabetes) and newer CHD risk factors (N-terminal fragment of prohormone B-type natriuretic peptide levels, von Willebrand factor antigen levels, fibrinogen levels, chronic kidney disease, leukocyte count, C-reactive protein levels, homocysteine levels, uric acid levels, coronary artery calcium [CAC] scores, carotid intima-media thickness, peripheral arterial disease, and pulse wave velocity). RESULTS: Adding CAC scores to the FRS improved the accuracy of risk predictions (c-statistic increase, 0.05 [95% CI, 0.02 to 0.06]; net reclassification index, 19.3% overall [39.3% in those at intermediate risk, by FRS]). Levels of N-terminal fragment of prohormone B-type natriuretic peptide also improved risk predictions but to a lesser extent (c-statistic increase, 0.02 [CI, 0.01 to 0.04]; net reclassification index, 7.6% overall [33.0% in those at intermediate risk, by FRS]). Improvements in predictions with other newer markers were marginal. LIMITATION: The findings may not be generalizable to younger or nonwhite populations. CONCLUSION: Among 12 CHD risk markers, improvements in FRS predictions were most statistically and clinically significant with the addition of CAC scores. Further investigation is needed to assess whether risk refinements using CAC scores lead to a meaningful change in clinical outcome. Whether to use CAC score screening as a more routine test for risk prediction requires full consideration of the financial and clinical costs of performing versus not performing the test for both persons and health systems. PRIMARY FUNDING SOURCE: Netherlands Organization for Health Research and Development (ZonMw).