Initiation and continuation of pharmacological therapies in patients hospitalized for heart failure in Japan.

Currently, the utilization patterns of medications for heart failure (HF) after worsening HF events remain unelucidated in Japan. Here, we conducted a retrospective cohort study evaluating the changes in HF drug utilization patterns in 6 months before and after hospitalizations for HF. The adherence to newly initiated HF medications was evaluated based on the proportion of days covered (PDC) and persistence as continuous treatment episodes among new users. The study included 9091 patients hospitalized for HF between January 2016 and September 2019, including 2735 (30.1%) patients who were newly prescribed at least one HF medication after hospitalization. Despite increases in the use of foundational HF therapy (beta-blockers, angiotensin-converting-enzyme inhibitors/angiotensin receptor blockers, or mineralocorticoid receptor antagonists), 35.6% and 7.6% of patients were treated with the HF foundational monotherapy or diuretics alone after hospitalization, respectively. The mean PDC of newly initiated HF medications ranged from 0.57 for thiazide diuretics to 0.77 for sodium-glucose cotransporter-2 inhibitors. Continuous use of HF medications during the first year after initiation was observed in 30-60% of patients. The mean PDC and one-year continuous HF medication use were consistently lower in patients aged ≥ 75 years and in patients with a history of HF hospitalization for all HF medication classes except for tolvaptan and digoxin. Despite the guideline recommendations of HF pharmacotherapy, both treatment and adherence were suboptimal after HF hospitalization, especially in vulnerable populations such as older patients and those with prior HF hospitalizations.

A Case for Synthetic Data in Regulatory Decision-Making in Europe.

Regulators are faced with many challenges surrounding health data usage, including privacy, fragmentation, validity, and generalizability, especially in the European Union, for which synthetic data may provide innovative solutions. Synthetic data, defined as data artificially generated rather than captured in the real world, are increasingly being used for healthcare research purposes as a proxy to real-world data (RWD). Currently, there are barriers particularly challenging in Europe, where sharing patient's data is strictly regulated, costly, and time-consuming, causing delays in evidence generation and regulatory approvals. Recent initiatives are encouraging the use of synthetic data in regulatory decision making and health technology assessment to overcome these challenges, but synthetic data have still to overcome realistic obstacles before their adoption by researchers and regulators in Europe. Thus, the emerging use of RWD and synthetic data by pharmaceutical and medical device industries calls regulatory bodies to provide a framework for proper evidence generation and informed regulatory decision making. As the provision of data becomes more ubiquitous in scientific research, so will innovations in artificial intelligence, machine learning, and generation of synthetic data, making the exploration and intricacies of this topic all the more important and timely. In this review, we discuss the potential merits and challenges of synthetic data in the context of decision making in the European regulatory environment. We explore the current uses of synthetic data and ongoing initiatives, the value of synthetic data for regulatory purposes, and realistic barriers to the adoption of synthetic data in healthcare.

Prevalence of current mental disorders before and during the second wave of COVID-19 pandemic: An analysis of repeated nationwide cross-sectional surveys.

OBJECTIVES: To assess the prevalence of mental disorders during the second wave of COVID-19 pandemic in comparison with both, baseline and the first wave of the pandemic, and to identify disproportionally affected non-clinical subgroups. MATERIAL AND METHODS: We used data from three nationally representative cross-sectional studies and compared the prevalence of current mood and anxiety disorders, and alcohol-use disorders at baseline (November 2017, n = 3306), immediately after the first peak (May 2020, n = 3021), and during the second peak (November 2020, n = 3000) of COVID-19 in Czechia. We used the Mini International Neuropsychiatric Interview (M.I.N.I.) as a screening instrument, and calculated weighted prevalence (%) with 95% weighted confidence intervals (95% CIs). Additionally, we examined the prevalence of these disorders across different non-clinical population sub-groups during the second wave of the pandemic. RESULTS: The proportion of individuals experiencing at least one mental disorder was highest during the second wave of the pandemic (32.94%, 95% CI = 31.14%; 34.77%), when compared to both the baseline in November 2017 (20.02%, 95% CI = 18.64%; 21.39%), and the first wave in May 2020 (29.63%, 95% CI = 27.9%; 31.37%). Younger adults, students, those having lost a job or on forced leave, and those with only elementary education displayed disproportionally high prevalence of mental disorders. CONCLUSIONS: Our findings suggest that population mental health has not returned to pre-COVID-19 levels. It seems that mental health of some population subgroups, such as young adults or those worse off economically, might have been affected disproportionately by the COVID-19 situation, and future studies identifying high-risk groups are warranted.