Frequency of migraine and the risk of cardiovascular disease for women : limited evidence of an association

Evaluation of: Kurth T, Schurks M, Logroscino G et al. Migraine frequency and risk of cardiovascular disease in women. Neurology 73, 581–588 (2009). There is substantial evidence that migraine with aura (MA) is associated with ischemic stroke and myocardial infarction in women. The mechanisms of this association are poorly understood. Analysis of data from the Women’s Health Study, from 27,798 women over 45 years of age who were initially free of cardiovascular disease, found that women with baseline MA at a frequency of less than monthly had increased risk of major cardiovascular disease (HR: 2.28; 95% CI: 1.70–3.07) relative to women without migraine, and those who reported MA with a frequency of more than weekly had more than four-times the risk of ischemic stroke (HR: 4.25; 95% CI: 1.36–13.29) compared with those without migraine. Low numbers of outcome events in each of the frequency categories and lack of information on migraine frequency during follow-up limit the interpretation of these findings, but they suggest that frequency of migraine may be a moderating factor in the link between MA and cardiovascular disease.

Overview of risk prediction models in cardiovascular disease research

Many risk prediction models have been developed for cardiovascular diseases in different countries during the past three decades. However, there has not been consistent agreement regarding how to appropriately assess a risk prediction model, especially when new markers are added to an established risk prediction model. Researchers often use the area under the receiver operating characteristic curve (ROC) to assess the discriminatory ability of a risk prediction model. However, recent studies suggest that this method has serious limitations and cannot be the sole approach to evaluate the usefulness of a new marker in clinical and epidemiological studies. To overcome the shortcomings of this traditional method, new assessment methods have been proposed. The aim of this article is to overview various risk prediction models for cardiovascular diseases, to describe the receiver operating characteristic curve method and discuss some new assessment methods proposed recently. Some of the methods were illustrated with figures from a cardiovascular disease study in Australia.

Laboratory and non-laboratory-based risk prevention models for secondary prevention of cardiovascular disease : the LIPID study

Aims : The aims of this study were to examine whether risk prediction models for recurrent cardiovascular disease (CVD) events have prognostic value, and to particularly examine the performance of those models based on non-laboratory data. We also aimed to construct a risk chart based on the risk factors that showed the strongest relationship with CVD.

Methods and results : Cox proportional hazards models were used to calculate a risk score for each recurrent event in a CVD patient who was enrolled in a very large randomized controlled clinical trial. Patients were then classified into groups according to quintiles of their risk score. These risk models were validated by calibration and discrimination analyses based on data from patients recruited in New Zealand for the same study. Non-laboratory-based risk factors, such as age, sex, body mass index, smoking status, angina grade, history of myocardial infarction, revascularization, stroke, diabetes or hypertension and treatment with pravastatin, were found to be significantly associated with the risk of developing a recurrent CVD event. Patients who were classified into the medium and high-risk groups had two-fold and four-fold the risk of developing a CVD event compared with those in the low-risk group, respectively. The risk prediction models also fitted New Zealand data well after recalibration.

Conclusion : A simpler non-laboratory-based risk prediction model performed equally as well as the more comprehensive laboratory-based risk prediction models. The risk chart based on the further simplified Score Model may provide a useful tool for clinical cardiologists to assess an individual patient's risk for recurrent CVD events.

Pharmacist assessment of adherence, risk and treatment in cardiovascular disease (PAART CVD)

Cardiovascular disease (CVD) accounts for 18% of disease burden in Australia, and 35% of deaths. Evidence- based management of CVD risk requires systematic consideration of individual risk factors and overall CVD risk, and a balanced approach to lifestyle modification, the optimal use of medicines, and medicines adherence.

This project examines a pHot model for primary prevention of CVD in community pharmacy aimed at improving quality of care. Pharmacists from ten pharmacies received training in CVD risk factor management and facilitating patient lifestyle modification.

They recruited 70 participants aged 50-74 years, taking medicines for blood pressure (BP) or cholesterol, and without diabetes or CVD, At baseline, research assistants conducted a clinical assessment of anthropometric and biomedical risk factors, and conducted interviews to examine health behaviours, medicines use and related issues. Data was analysed by a consultant pharmacist and summary reports produced, with recommendations and targets for risk reduction. These were addressed by patients and their community pharmacists over five monthly sessions. At follow up, the relative risk reduction for CVD onset over the next five years was 24%, contributed to by reductions in mean systolic BP (-7mmHg), diastolic PP (-5 mmHg), total:HDL cholesterol ratio (—0.2), waist circumference (—2cm in males, —0.7cm in females) and other risk factors.

Several key health behaviours improved, including diet quality and physical activity levels. Prevalence of non-adherence to cardiovascular medicines dropped by 1 6% to 22%.

The potential health benefits from this intervention need to be confirmed via larger, controlled clinical trials. Overall, this appears to be a feasible and potentially effective public health measure.

The neuronal noradrenaline transporter, anxiety and cardiovascular disease

Panic disorder can serve as a clinical model for testing whether mental stress can cause heart disease. Potential neural mechanisms of cardiac risk are the sympathetic activation during panic attacks, continuing release of adrenaline as a co-transmitter in the cardiac sympathetic nerves, and impairment of noradrenaline neuronal reuptake, augmenting sympathetic neural respnses.

The phenotype of impaired neuronal reuptake of noradrenaline: an epigenetic mechanism? We suspect that this phenotype, in sensitizing people to heart symptom development, is a cause of panic disorder, and by magnifying the sympathetic neural signal in the heart, underlies increased cardiac risk. No loss of function mutations of the coding region of the norepinephrine transporter (NET) are evident, but we do detect hypermethylation of CpG islands in the NET gene promoter region. Chromatin immunoprecipitation methodology demonstrates binding of the inhibitory transcription factor, MeCP2, to promoter region DNA in panic disorder patients.

Cardiovascular illnesses co-morbid with panic disorder. Panic disorder commonly coexists with essential hypertension and the postural tachycardia syndrome. In both of these cardiovascular disorders the impaired neuronal noradrenaline reuptake phenotype is also present and, as with panic disorder, is associated with NET gene promoter region DNA hypermethylation. An epigenetic ‘co-morbidity’ perhaps underlies the clinical concordance.

Brain neurotransmitters. Using internal jugular venous sampling, in the absence of a panic attack we find normal norepinephrine turnover, but based on measurements of the overflow of the serotonin metabolite, 5HIAA, a marked increase (six to sevenfold) in brain serotonin turnover in patients with panic disorder. This appears to represent the underlying neurotransmitter substrate for the disorder. Whether this brain serotonergic activation is a prime mover, or consequential on other primary causes of panic disorder, including cardiac sensitization by faulty neuronal noradrenaline reuptake leading to cardiac symptoms and the enhanced vigilance which accompanies them, is unclear at present.

The quality and outcomes framework reduces disparities in health outcomes for cardiovascular disease

Jamie Robinson, the Berkeley health economist, famously remarked in 2001 that ‘the three worst ways to pay doctors are salary, capitation and fee-for-service.’ Different financial incentives produce different clinical and service outcomes, sometimes perversely.1 In 2004, the UK government introduced pay for performance (P4P) for general practitioners, the Quality and Outcomes Framework (QOF). Its introduction was associated with the general trend in the National Health Service away from placing implicit trust in doctors and more active monitoring of their performance. One-quarter of GP pay can be earned from achieving scores on 147 indicators.2 These indicators were acceptable to doctors because the majority are evidence-based clinical outcome measures for 10 chronic diseases. Others relate to patient access and satisfaction, and practice organisation.