A systematic review and meta-analysis of new-onset atrial fibrillation in the context of COVID-19 infection.

New-onset atrial fibrillation (NOAF) in COVID-19 raises significant clinical and public health issues. This systematic review and meta-analysis aims to compile and analyze the current literature on NOAF in COVID-19 and give a more comprehensive understanding of the prevalence and outcomes of NOAF in COVID-19. A comprehensive literature search was carried out using several databases. The random effect model using inverse variance method and DerSimonian and Laird estimator of Tua2 was used to calculate the pooled prevalence and associated 95% confidence interval (CI). Results for outcome analysis were presented as odds ratios (ORs) with 95% CI and pooled using the Mantel-Haenszel random-effects model. The pooled prevalence of NOAF in COVID-19 was 7.8% (95% CI: 6.54%-9.32%),a pooled estimate from 30 articles (81 929 COVID-19 patients). Furthermore, our analysis reported that COVID-19 patients with NOAF had a higher risk of developing severe disease compared with COVID-19 patients without a history of atrial fibrillation (OR = 4.78, 95% CI: 3.75-6.09) and COVID-19 patients with a history of pre-existing atrial fibrillation (OR = 2.75, 95% CI: 2.10-3.59). Similarly, our analysis also indicated that COVID-19 patients with NOAF had a higher risk of all-cause mortality compared with, COVID-19 patients without a history of atrial fibrillation (OR = 3.83, 95% CI: 2.99-4.92) and COVID-19 patients with a history of pre-existing atrial fibrillation (OR = 2.32, 95% CI: 1.35-3.96). The meta-analysis did not reveal any significant publication bias. The results indicate a strong correlation between NOAF and a higher risk of severe illness and mortality. These results emphasize the importance of careful surveillance, early detection, and customized NOAF management strategies to improve clinical outcomes for COVID-19 patients.

Unveiling the Dual Threat: Myocarditis in the Spectrum of Dengue Fever.

This meta-analysis aims to systematically review and analyze available studies on the association between myocarditis and dengue viral fever. A comprehensive literature search was carried out using several databases. Mantel-Haenszel odds ratios and associated 95% confidence intervals were produced to report the overall effect size using random effect models. Besides, random effects models were used to calculate the overall pooled prevalence. Data from 26 articles (6622 dengue patients) showed that pooled estimate of myocarditis in dengue fever was 12.4% (95% CI, 8.41-17.08). Higher prevalence was seen in reports from Asia (15.2%) compared to that from Latin America (3.6%). Besides, the pooled prevalence of severity and mortality was 34% (95% CI, 20.49-49.04) and 26.44% (95% CI, 18.07-35.78) respectively. Significantly higher prevalence rates of severe disease in the pediatric population (52.4%) and studies with a higher percentage of females (52.1%) were also observed. However, higher mortality rates were seen in the adult population (34.8%) compared with the pediatric age group. Further, myocarditis in dengue patients was associated with increased risk of severity (RR = 2.44, 95% CI 1.007-5.93, P = 0.048) and mortality (RR = 19.41, 95% CI 7.19-52.38, P < 0.001) compared with dengue patients without myocarditis. No significant publication bias was evident in the meta-analysis. The findings highlight the clinical significance of early identification and management of myocarditis in patients with dengue fever.

The Bangor Gambling Task: Computerized replication and reappraisal of an emotion-based decision task.

Emotion-based decision making (EBDM) is the capacity to make decisions based on prior emotional consequences of actions. Several neuropsychological tasks, using different gambling paradigms and with different levels of complexity, have been designed to assess EBDM. The Bangor Gambling Task (BGT) was created as a brief and simple card gambling-task to assess EBDM. BGT contains a single-card deck and requires participants to decide whether to gamble or not, which can result in wins or losses. Unknown to the participant, the winning probabilities decrease throughout the task (from 0.75 in the first block to 0.25 in the fifth block), requiring participants to reduce their gambling probability to avoid long-term losses. A few studies have offered evidence regarding the BGT convergent validity. However, there are no computerized versions of BGT available, thus slowing the process of gathering information to explore the EBDM mechanisms behind the task, its validity, and clinical usefulness. In this article, we present a computerized version of the BGT using the Matlab environment and make all our code available. We explore BGT's replicability and analyze its probabilistic structure, providing trial-level and block-level analyses. Eighty-one participants performed the computerized version, which followed the same structure as the original version. It took participants 8.5 ± 3.3 minutes to complete the task, which is faster than the paper version. Replicating previous studies, participants diminished their gambling probability throughout the task, learning to inhibit the initially rewarded gambling behavior. This change in gambling probability could be considered a proxy for EBDM. Our analyses suggest that the last blocks are especially sensitive to capturing deficits in EBDM, and we propose some modifications to BGT's original version to enhance the initial exploratory and learning phase. Our results show that the BGT constitutes a quick and simple task to evaluate EBDM capacities.