Clinical atherosclerotic cardiovascular disease (ASCVD) patients are judged to be very-high-risk if they had a history of multiple major ASCVD events, or one major ASCVD event with multiple high-risk conditions. Very-high-risk ASCVD patients are under high risk of adverse clinical events and need more attention in the management of secondary prevention. This real-world study aimed at estimating the prevalence of very-high-risk ASCVD and investigating the occurrence of adverse clinical events and associated risk factors among patients with very-high-risk ASCVD in China.

Data were obtained from the Urban Employee Basic Medical Insurance database in Tianjin, China. Very-high-risk ASCVD patients were identified from 2014 to 2015 through the history of ASCVD events and evidence of high-risk conditions, and followed for 24 months. Adverse clinical events were measured by major adverse cardiovascular events (MACE), a composite endpoint of stroke, myocardial infarction (MI) and death. A Cox regression model was used to identify risk factors of MACE, adjusting for potential confounders.

The percentage of clinical ASCVD patients identified as very-high-risk was 35.2 (N = 41,181), while 34,740 patients with continuous enrollment were included (mean age: 67.1 years; 42.5% female). The percentage of patients who had MACE in the 24-month follow-up period was 27.7, with stroke (22.3%) as the most prevalent event followed by death (6.9%) and MI (1.3%). Male gender, older age, and having MI or ischemic stroke (versus unstable angina) as the index major ASCVD event were risk predictors of MACE.

More than one-third of patients with clinical ASCVD are under very-high-risk in China, and among them 27.7 percent experience MACE during a 24-month follow-up period. Male patients, older patients, and patients who had MI or ischemic stroke are under higher risk of experiencing MACE. Future studies are warranted for comparing the differences in characteristics, pattern of drug use, occurrence of adverse clinical events and medical burden between very-high-risk ASCVD patients and ASCVD patients not at very-high-risk.

Internet gaming disorder (IGD) is a type of behavioural addictions. One of the key features of addiction is the excessive exposure to addictive objectives (e.g. drugs) reduces the sensitivity of the brain reward system to daily rewards (e.g. money). This is thought to be mediated via the signals expressed as dopaminergic reward prediction error (RPE). Emerging evidence highlights blunted RPE signals in drug addictions. However, no study has examined whether IGD also involves alterations in RPE signals that are observed in other types of addictions.

To fill this gap, we used functional magnetic resonance imaging data from 45 IGD and 42 healthy controls (HCs) during a reward-related prediction-error task and utilised a psychophysiological interaction (PPI) analysis to characterise the underlying neural correlates of RPE and related functional connectivity.

Relative to HCs, IGD individuals showed impaired reinforcement learning, blunted RPE signals in multiple regions of the brain reward system, including the right caudate, left orbitofrontal cortex (OFC), and right dorsolateral prefrontal cortex (DLPFC). Moreover, the PPI analysis revealed a pattern of hyperconnectivity between the right caudate, right putamen, bilateral DLPFC, and right dorsal anterior cingulate cortex (dACC) in the IGD group. Finally, linear regression suggested that the connection between the right DLPFC and right dACC could significantly predict the variation of RPE signals in the left OFC.

These results highlight disrupted RPE signalling and hyperconnectivity between regions of the brain reward system in IGD. Reinforcement learning deficits may be crucial underlying characteristics of IGD pathophysiology.