Neonatal brain injury or neonatal encephalopathy (NE) is a significant morbidity and mortality factor in preterm and full-term newborns. NE has an incidence in the range of 2.5 to 3.5 per 1000 live births carrying a considerable burden for neurological outcomes such as epilepsy, cerebral palsy, cognitive impairments, and hydrocephaly. Many scoring systems based on different risk factor combinations in regression models have been proposed to predict abnormal outcomes. Birthweight, gestational age, Apgar scores, pH, ultrasound and MRI biomarkers, seizures onset, EEG pattern, and seizure duration were the most referred predictors in the literature. Our study proposes a decision-tree approach based on clinical risk factors for abnormal outcomes in newborns with the neurological syndrome to assist in neonatal encephalopathy prognosis as a complementary tool to the acknowledged scoring systems. We retrospectively studied 188 newborns with associated encephalopathy and seizures in the perinatal period. Etiology and abnormal outcomes were assessed through correlations with the risk factors. We computed mean, median, odds ratios values for birth weight, gestational age, 1-min Apgar Score, 5-min Apgar score, seizures onset, and seizures duration monitoring, applying standard statistical methods first. Subsequently, CART (classification and regression trees) and cluster analysis were employed, further adjusting the medians. Out of 188 cases, 84 were associated to abnormal outcomes. The hierarchy on etiology frequencies was dominated by cerebrovascular impairments, metabolic anomalies, and infections. Both preterms and full-terms at risk were bundled in specific categories defined as high-risk 75–100%, intermediate risk 52.9%, and low risk 0–25% after CART algorithm implementation. Cluster analysis illustrated the median values, profiling at a glance the preterm model in high-risk groups and a full-term model in the inter-mediate-risk category. Our study illustrates that, in addition to standard statistics methodologies, decision-tree approaches could provide a first-step tool for the prognosis of the abnormal outcome in newborns with encephalopathy.

Learning disabilities (LDs) have an estimated prevalence between 5% and 9% in the pediatric population and are associated with difficulties in reading, arithmetic, and writing. Previous electroencephalography (EEG) research has reported a lag in alpha-band development in specific LD phenotypes, which seems to offer a possible explanation for differences in EEG maturation. In this study, 40 adolescents aged 10–15 years with LDs underwent 10 sessions of Live Z-Score Training Neurofeedback (LZT-NF) Training to improve their cognition and behavior. Based on the individual alpha peak frequency (i-APF) values from the spectrogram, a group with normal i-APF (ni-APF) and a group with low i-APF (li-APF) were compared in a pre-and-post-LZT-NF intervention. There were no statistical differences in age, gender, or the distribution of LDs between the groups. The li-APF group showed a higher theta absolute power in P4 (p = 0.016) at baseline and higher Hi-Beta absolute power in F3 (p = 0.007) post-treatment compared with the ni-APF group. In both groups, extreme waves (absolute Z-score of ≥1.5) were more likely to move toward the normative values, with better results in the ni-APF group. Conversely, the waves within the normal range at baseline were more likely to move out of the range after treatment in the li-APF group. Our results provide evidence of a viable biomarker for identifying optimal responders for the LZT-NF technique based on the i-APF metric reflecting the patient’s neurophysiological individuality.

Statins are included in the category of high-frequency prescription drugs, and their use is on an upward trend worldwide. In 2012, the FDA issued a warning about possible cognitive adverse drug reactions (ADRs) related to statins, some of which are listed in the Summary of Product Characteristics, but there are still concerns about their potential risk of psychiatric events. The aim of this research was to investigate spontaneous reports containing psychiatric ADRs associated with statins by analyzing the EudraVigilance (EV) database. From January 2004 to July 2021, a total of 8965 ADRs were reported for the Systems Organ Class (SOC) “psychiatric disorders”, of which 88.64% were registered for atorvastatin (3659), simvastatin (2326) and rosuvastatin (1962). Out of a total of 7947 individual case safety reports (ICSRs) of the 3 statins mentioned above, in 36.3% (2885) of them, statins were considered the only suspected drug, and in 42% (3338), no other co-administered drugs were mentioned. Moreover, insomnia has been reported in 19.3% (1536) of cases, being the most frequent adverse reaction. A disproportionality analysis of psychiatric ADRs was performed. The Reporting Odds Ratio (ROR) and 95% confidence interval (95% CI) were calculated for simvastatin, atorvastatin and rosuvastatin compared with antiplatelets and antihypertensive drugs. The reporting probability for most ADRs of these statins compared to antiplatelets was higher. The reporting probability for insomnia, nightmares and depression produced by statins compared to antihypertensive drugs was also higher. The results of this analysis augment the existing data about a possible correlation between the administration of statins and the occurrence of psychiatric side effects.

The past few decades have shown a worrisome increase in the prevalence of obesity and its related illnesses. This increasing burden has a noteworthy impact on overall worldwide mortality and morbidity, with significant economic implications as well. The same trend is apparent regarding pediatric obesity. This is a particularly concerning aspect when considering the well-established link between cardiovascular disease and obesity, and the fact that childhood obesity frequently leads to adult obesity. Moreover, most obese adults have a history of excess weight starting in childhood. In addition, given the cumulative character of both time and severity of exposure to obesity as a risk factor for associated diseases, the repercussions of obesity prevalence and related morbidity could be exponential in time. The purpose of this review is to outline key aspects regarding the current knowledge on childhood and adolescent obesity as a cardiometabolic risk factor, as well as the most common etiological pathways involved in the development of weight excess and associated cardiovascular and metabolic diseases.

In HF patients with AF, despite a similar peak (Equation is included in full-text article.)O2 compared with patients with HF and SR, (Equation is included in full-text article.)O2 AT is higher because of a higher HR and a greater HR increase during exercise. One postulated mechanism would be a greater cardiac output increase at the beginning of exercise in HF patients with AF. The delayed AT generates uncertainty about the meaning of a (Equation is included in full-text article.)O2 value at AT in HF patients with AF, because a higher AT is usually associated with better performance and a better prognosis.