Background: Enrollment of large cohorts of syncope patients from administrative data is crucial for proper risk stratification but is limited by the enormous amount of time required for manual revision of medical records. Aim: To develop a Natural Language Processing (NLP) algorithm to automatically identify syncope from Emergency Department (ED) electronic medical records (EMRs). Methods: De-identified EMRs of all consecutive patients evaluated at Humanitas Research Hospital ED from 1 December 2013 to 31 March 2014 and from 1 December 2015 to 31 March 2016 were manually annotated to identify syncope. Records were combined in a single dataset and classified. The performance of combined multiple NLP feature selectors and classifiers was tested. Primary Outcomes: NLP algorithms’ accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F3 score. Results: 15,098 and 15,222 records from 2013 and 2015 datasets were analyzed. Syncope was present in 571 records. Normalized Gini Index feature selector combined with Support Vector Machines classifier obtained the best F3 value (84.0%), with 92.2% sensitivity and 47.4% positive predictive value. A 96% analysis time reduction was computed, compared with EMRs manual review. Conclusions: This artificial intelligence algorithm enabled the automatic identification of a large population of syncope patients using EMRs.

Today, it is possible to investigate the biological paths and mechanisms that link mental life to biological life. Emotions, feelings, desires, and cognitions influence biological systems. In recent decades, psychoneuroendocrinoimmunology research has highlighted the routes linking the psyche–brain–immune systems. Recently, epigenetics research has shown the molecular mechanisms by which stress and mental states modulate the information contained in the genome. This research shapes a new paradigm considering the human being as a whole, integrating biology and psychology. This will allow us to progress towards personalized precision medicine, deeply changing medical and psychological sciences and clinical practice. In this paper, we recognize leading research on both bidirectional relations between the psyche–brain–immunity and molecular consequences of psychological and mental states.

Meditation represents an effective and safe practice to lower distress and promote well-being. PsychoNeuroEndocrinoImmunology-based Meditation (PNEIMED) is a validated method that can reduce stress-related symptoms and salivary cortisol secretion. To date, few randomised controlled trials (RCTs) have assessed cortisol levels through salivary samples, collected both in the morning phase and during acute mental stress elicitation, in healthy young subjects following brief meditation training. The present study aims to investigate, in healthy young undergraduate students, the effects of a brief PNEIMED training course on HPA axis by measuring salivary cortisol levels. Forty students attending the Faculty of Psychology, without comorbidities and previous experience of meditation, were enrolled in the study. Twenty subjects were randomly assigned to 30 h of PNEIMED training (intervention group, IG), and twenty subjects were randomly assigned to 30 h of academic lessons (control group, CG). Salivary cortisol measures included basal morning (t0 = baseline time, collected 30 min after waking) and under stress-eliciting task values. Cortisol measurement under the stress-eliciting task was provided through the Subtraction Stress Task (SST) at scheduled time intervals (t1 = 5 min pre-SST, t2 = 10 min post-SST, t3 = 30 min = post-SST). Salivary cortisol was measured among all subjects (IG + CG) at the beginning (pre-test) and at the end (post-test, four days later) of the study. ANOVA between-group analysis of basal diurnal salivary cortisol showed a significant hormone deflection in the IG at the end of the PNEIMED course (post-test) when compared to the CG (IG post-test 5.64 ± 4.2 vs CG post-test 9.44 ± 4.9; F1,38 = 6.838; p = 0.013). RM-ANOVA within-group analysis for the IG also showed that time and condition effects were statistically significant, with Ftime = 5.438; p = 0.002 and Fcondition = 10.478; p = 0.004, respectively. The IG group presented a significant reduction in basal morning cortisol at the end of the PNEIMED course (post-test) compared to the salivary concentration at baseline (pre-test) (IG pre-test 9.42 ± 6.0 vs IG post-test 5.64 ± 4.2; F1,38 8,354; p = 0.009). RM-ANOVA for the control group showed only the main effect of time (F1,38 = 40.348; p < 0.001). Regarding cortisol measures under the SST-stress eliciting task, ANOVA between-groups analysis showed higher cortisol levels in the IG than in the CG before the PNEIMED course, with significant differences between groups at time t2 and time t3. After the PNEIMED course, the cortisol levels in the IG had decreased, although the differences between groups were not significant. Interestingly, ANOVA within-groups analysis showed that in the IG, the cortisol levels post-test (after the PNEIMED course) were lower than at pre-test (before the PNEIMED course), showing a significant difference of cortisol salivary concentration between conditions at t3 (F = 5.326; p = 0.032). In the control group, the post-hoc analyses for pairwise comparisons between conditions (pre-test vs post-test) did not show significant differences. Although the low number of subjects enrolled in the study does not allow for definitive conclusions to be drawn, the present findings confirmed the capability of the PNEIMED method to lower stress hormone secretion both at baseline and under acute mental stimulation in a group of young naïve practitioners and make a contribution to the existing literature by increasing the number of published RCTs about the topic.

Psychoneuroendocrineimmunology (PNEI) brings together knowledge acquired since the 1930s from endocrinology, immunology, neuroscience, and psychology. With PNEI, a model of research and interpretation of health and disease is emerging, which sees the human body as a structured and interconnected unit, where the psychological and biological systems are mutually coordinated. In the PNEI view, many factors could influence mental health, with the endocrine system involved in mediating the effects of environmental stress on mental health and inflammation in the onset and course of psychiatric disorders as a result of individual and collective conditions and behaviors. Among these, nutrition is one way by which the environment impacts physiology: indeed, many pieces of research showed that several elements (e.g., probiotics, fish oil, zinc) have a positive effect on mental disorders thus being potentially augmentation agents in treatment. Still, physical activity can moderate depressive symptoms, while prolonged stress increases the risk of psychopathology. Taken together, the PNEI-based approach may inform prevention and treatment strategies, also in the field of mental health care.