Antipsychotic medication, stress, gender, and age are factors that influence prolactin levels in patients with psychosis. The aim of the study was to investigate the level of prolactin response to antipsychotic treatment in acute patients, taking into account the total duration of psychosis. The study was conducted on 170 acute patients with schizophrenia spectrum disorders and bipolar disorder. Subjects were divided into three subgroups according to the duration of the psychosis (less than 5 years, between 5 and 10 years and more than 10 years of disorder duration). The initial prolactin response under antipsychotic treatment was measured, while the severity of the psychiatric symptoms was assessed with the BPRS (Brief Psychiatric Rating Scale). Hyperprolactinemia was found in 120 (70.6%) patients, amongst which 80 (66.7%) were females and 40 (33.3%) were males. The average increase in prolactinemia was 2.46 times the maximum value in women, and 1.59 times in men. Gender (β = 0.27, p<0.0001), type of antipsychotic medication according to potency of inducing hyperprolactinemia (β = -0.23, p<0.003), and the duration of psychosis over 10 years (β = -0.15, p = 0.04) significantly predicted prolactin levels, when age, diagnosis, antipsychotic category (conventional/atypical/combinations of antipsychotics), and BPRS total scores were controlled for. Prolactin levels in patients treated with antipsychotic medication appeared to depend on patients’ gender, on the type of antipsychotic medication according to potency of inducing hyperprolactinemia, and on the duration of the psychosis. An increase in prolactin levels was associated with female gender, while the use of prolactin sparing antipsychotics and a duration of psychosis over 10 years were associated with lower prolactin levels.

Patients with severe COVID-19 experience high-stress levels and thus are at risk for developing acute stress disorder (ASD) and/or post-traumatic stress disorder (PTSD). The present study aims to search for correlations between psychiatric response to stress and coping strategies among individuals with acute vs. remitted COVID-19. Ninety subjects with COVID-19 were included in the study, divided into two samples by disease category. Our focus was analysing the perceived stress intensity according to NSESSS and PCL-C-17 scales, and coping strategies with COPE-60. High NSESSS scores were found in 40% of acute patients, and 15.6% of remitted patients had high PCL-C-17 scores fulfilling the criteria for PTSD. We found a negative correlation between stress level and disease category. Acute patients used significantly more engagement and emotion-focused coping methods, but less disengagement types of coping than patients in the remitted phase. Remitted patients under high stress levels are prone to use disengagement and emotion-focused coping strategies. In conclusion, remitted COVID-19 patients experience lower levels of stress and use less emotion-focused strategies, except among those who developed PTSD post-COVID-19 infection, presenting with high-stress levels and using more disengagement and emotion-focused types of coping strategies.

This study assesses the empathy level, cognitive performance and emotion recognition skills of remitted patients with schizophrenia, schizoaffective disorder and bipolar disorder, and also explores the relationship between impairments in the mentioned domains. The study was performed on 77 subjects divided into two groups: PAT sample (N = 37) included remitted patients with either schizophrenia, schizoaffective or bipolar disorder who were compared with healthy control subjects from the HC sample (N = 40). Along with sociodemographic and clinical data, empathy levels (using EQ (Empathy Quotient) scale), the ability to recognize another person’s emotional state (using RMET (Reading the Mind in the Eyes Test)), and cognitive performance (using MoCA (Montreal Cognitive Assessment) Scale) were investigated. The intensity of the psychiatric symptoms was measured with BPRS-E (Brief Psychiatric Rating Scale—Expanded). The remitted patients had lower EQ (p = 0.02) and RMET (p < 0.0001) scores than the healthy subjects. In the PAT group, RMET scores were positively correlated with MoCA total scores. Both EQ and RMET scores were negatively correlated with BPRS-E total scores. Psychiatric disorder was a significant predictor for deficits in emotion recognition. There were no significant differences in RMET, EQ and MoCA scores between patients with respect to diagnosis, the type of antipsychotic or the associated medication. In both samples, females had higher empathy levels (p = 0.04) and better emotion recognition abilities (p = 0.04) than males. Patients with schizophrenia, schizoaffective or bipolar disorder, currently in remission, displayed lower empathy levels and poorer emotion recognition skills than healthy subjects. Poor emotion recognition skills were associated with symptom severity and impairments in global cognition.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection induces a significant inflammatory response that are amplified by persistent stress. The pathophysiology of mental illnesses is explored in terms of inflammatory processes. Thus, anxious, depressed, or psychotic episodes may occur as a result of metabolic and immunological imbalances, as a direct result of their effect on the central nervous system, or as a side effect of the COVID-19 medication protocols. As such, the primary objective of this research is to establish if the psychological profiles of COVID-19 patients change substantially according to illness severity. The secondary objective is to determine if particular biological inflammatory indicators are associated with anxiety, sadness, psychoticism, and paranoid ideation. A cross-sectional study was performed on 90 hospitalized patients admitted during a 3-month period in the COVID-19 unit. All patients received the COPE-60 and SCL-90R questionnaires. Clinical and paraclinical data were collected and the information was classified according to the severity of COVID-19.The hyper-acute inflammation encountered in patients with severe COVID-19 infection characterized 80.0% of patients using disengagement coping methods, significantly more than patients with mild or moderate SARS-CoV-2 infection severity (p-value = 0.012), respectively, 73.3% severe COVID-19 patients engaging in emotion-focused coping strategies based on the COPE-60 scale (p-value = 0.037). Additionally, it was determined that negative coping mechanisms (disengagement) and emotion-focused methods are independent risk factors for developing psychoticism symptoms following acute SARS-CoV-2 infection, based on the SCL-90 questionnaire (OR = 2.07; CI = 1.44–3.01), respectively (OR = 2.92; CI = 1.44–3.01). Elevated white blood cells and monocytes and inflammatory markers, such as fibrinogen, procalcitonin, IL-6, and D-dimers, were also identified as risk factors for psychoticism symptoms in multivariate analysis. It is particularly important to consider the constant mental-state evaluation in patients with severe COVID-19 that might benefit from early intervention before psychotic symptoms onset.

Background and Objectives: This retrospective study aimed to identify the main comorbidities found in gynecological patients hospitalized for endometrial lesions and to analyze the relationships between these comorbidities and each type of endometrial lesion. The Charlson comorbidity index (CCI) was calculated, thus assessing the patient’s probability of survival in relation to the underlying disease and the existing comorbidities. Materials and Methods: During 2015–2019, 594 cases hospitalized for vaginal bleeding outside of pregnancy were included in the research. For all cases, the frequency of comorbidities was calculated, applying the Cox proportional hazard model, considering the hospitalizations (from the following year after the first outpatient or hospital assessment) as a dependent variable; age and comorbidities were considered as independent variables. Results: Analysis of variance (ANOVA) for mean age of patients enrolled after diagnosis and multiple comparisons (via the Tukey post-hoc test) indicate significant differences (p < 0.05) between the average age for endometrial cancer (EC) and that for the typical endometrial hyperplasia or other diagnoses. The most common comorbidities were hypertension (62.28%), obesity (35.01%), and diabetes (22.89%), followed by cardiovascular disease. An intensely negative correlation (r = −0.715281634) was obtained between the percentage values of comorbidities present in EC and other endometrial lesions. The lowest chances of survival were calculated for 88 (14.81% of the total) patients over 50 years (the probability of survival in the next 10 years being between 0 and 21%). The chances of survival at 10 years are moderately negatively correlated with age (sample size = 594, r = −0.6706, p < 0.0001, 95% confidence interval (CI) for r having values from −0.7126 to −0.6238) and strongly negatively correlated with the CCI (r = −0.9359, p < 0.0001, 95% CI for r being in the range −0.9452 to −0.9251). Conclusions: Using CCI in endometrial lesions is necessary to compare the estimated risk of EC mortality with other medical conditions.

Purpose: Adaptation to chronic disease is an important factor for the quality of life of patients and their families. This research aimed to identify the psychosocial and clinical factors that determine significant differences and best predict the patients’ adaptation to chronic diseases. Understanding these factors enables the design of evidence-based preventive interventions that promote early adaptation. Patients and Methods: A quantitative, non-experimental comparative and predictive study design was conducted. Several clinical, demographic, and psychological factors were measured with an online questionnaire. This study was conducted on a convenience sample of 263 patients with chronic diseases: 63 (24%) had chronic kidney disease with dialysis dependency, 49 (18.6%) had solid neoplasms, 61 (23.2%) had hemopathies, 64 (24.3%) had HIV infection, and 26 (9.9%) had tuberculosis. Results: Adaptation to chronic disease varies based on the type of diagnosis, with lower adaptation seen in conditions that significantly impact daily life, involve comorbidities, and require frequent treatments, like chronic kidney disease. The most significant predictor of adaptation to the chronic disease is the female gender. Other predictive factors are medication adherence, social support, and self-efficacy in managing chronic disease. Patients without comorbidities and fewer medications are more prone to illness denial, alongside younger, urban, employed, and higher-educated patients, potentially neglecting treatment. Patients with comorbidities and the older patients require greater emotional support, with psychological counseling and support groups being beneficial. Conclusion: Current data underlines the need for an individualized approach to chronic disease management, which should consider demographic and psychological factors in addition to clinical ones. It is important to design early interventions for the development of adaptation to chronic disease, which could include individual and family counseling and education programs for medication administration, treatment at home, adherence to a healthy lifestyle, and inclusion of the patient and his family in social support groups.