Objective. To assess the prevalence of antenatal depressive disorder in different trimesters and to evaluate the relation of psychosocial risk factors to antenatal depressive disorder. Design. Cohort follow‐up. Setting. University Hospital, Kaunas, Lithuania. Sample. Two hundred and thirty pregnant women consecutively admitted. Methods. At 12–16 weeks, 22–26 weeks, and 32–36 weeks of pregnancy, participants were screened for depression using the World Health Organization's Composite International Diagnostic Interview Short Form (CIDI‐SF). Women who gave at least one positive answer to the CIDI‐SF depression‐screening question were evaluated for depressive disorder using the non‐patient version of the Structured Clinical Interview for DSM‐III‐R (SCID‐NP). Psychosocial stressors and two Big Five Personality dimensions, neuroticism and extraversion, were also evaluated. Main outcome measures. Prevalence of depressive disorder. Results. The prevalence of the antenatal depressive disorder at 12–16 weeks’ gestation was 6.1%, at 22–26 weeks 3.5%, and at 32–36 weeks 4.4%. In the first trimester, a greater prevalence of current depressive disorder was independently associated with unplanned and unwanted pregnancy, high neuroticism, low education, and a previous history of depression; in the second trimester with unplanned and unwanted pregnancy and high neuroticism; in the third trimester with unplanned and unwanted pregnancy, high neuroticism, and the occurrence of psychosocial stressors during the last year. Conclusions. The highest prevalence of depressive disorders was found in the first trimester, the lowest in mid‐pregnancy. Several determinants (unwanted and unplanned pregnancy, high neuroticism) were independent predictors of antenatal depressive disorders throughout whole pregnancy, while other determinants (low education, previous history of depression, the occurrence of psychosocial stressors at the end of pregnancy) were trimester specific.

Aims: To evaluate the prevalence of anxiety and depression in medical students and in humanities students. To assess the relationship between symptoms of anxiety, symptoms of depression and Big-Five personality dimensions and vulnerability to stress in medical students. Methods: Randomly selected 338 medical students and 73 humanities students were evaluated for symptoms of anxiety and depression using the Hospital Anxiety and Depression Scale (HADS), for Big-Five personality dimensions using the Ten-Item Personality Inventory (TIPI), and for vulnerability to stress using the Stress Vulnerability Scale (SVS). Results: Symptoms of anxiety and symptoms of depression were prevalent in medical students (43% and 14%, respectively) and in humanities students (52% and 12%, respectively). In medical students the score on the HADS anxiety subscale and the score on the HADS depression subscale correlated negatively with the score on the TIPI Emotional Stability scale (r = —0.39, p < 0.01 and r = —0.2, p < 0.01, respectively) and correlated positively with the score on the SVS (r = 0.38, p < 0.01 and r = 0.44, p < 0.01, respectively). Conclusions: Symptoms of anxiety and depression are prevalent in medical students and in humanities students. Severity of symptoms of anxiety and symptoms of depression in medical students is negatively related to emotional stability and positively related to stress vulnerability.

Deterioration of health related quality of life (HRQoL) is common in brain tumor patients. This study evaluated validity and reliability of the Medical Outcomes Study 36-Item Short Form (SF-36) in patients with brain tumors. Two hundred and seventy-seven patients admitted for brain tumor surgery were evaluated for HRQoL (SF-36 questionnaire); depressive symptoms (Beck Depression Inventory-II or BDI-II); and functional status (Barthel index or BI). Final histological diagnosis was obtained from pathology reports. Two-hundred and twenty-seven (completion rate of 82%) patients (69% women; mean age 55.8 ± 14.4 years) completed the SF-36 questionnaire. The most common brain tumor diagnosis was meningioma (40%), followed high-grade glioma (19%). Missing data rates were ≤4%. Internal consistency was adequate for all (Cronbach α ≥ .728) but Social Functioning (Cronbach α = .527) and General Health (Cronbach α = .693) subscales. Ceiling (≥36%) and floor (≥22%) effect rates were the greatest for the Role Limitations subscales. The SF-36 subscales pertaining physical health correlated the strongest with the BI score, while the SF-36 subscales pertaining emotional health correlated the strongest with the BDI-II score. Patients with mild-moderate depressive symptoms (BDI-II score ≥20) scored lower across all SF-36 subscales, and handicap patients (BI score <90) scored the lower across all, but Mental Health, subscales. The SF-36 is a valid and reliable instrument in brain tumor patients and therefore can be reliably applied for evaluation of HRQoL in neuro-oncology setting. Further studies exploring other psychometric properties of the SF-36 in brain tumor patients across disease progression stages are warranted.

This study aimed to evaluate how precise the Edinburgh Depression Scale (EDS) is in screening for major depressive disorder (MDD) during different periods of pregnancy. A random sample of 230 pregnant women was interviewed in the first, second, and third trimesters of pregnancy using the EDS and not-patient version of the Structured Clinical Interview for DSM-III-R (SCID-NP). We evaluated test-retest reliability of the EDS; area under the ROC curve (AUC), sensitivity, specificity, and positive predictive value (PPV) of the EDS against the SCID-NP diagnoses in the first, second, and third trimesters of pregnancy. Test–retest reliability of the EDS was 0.81 (p < 0.001). An optimal cutoff score of the EDS for screening current SCID-NP diagnosis of MDD was 12 and higher in the first trimester of pregnancy (AUC 0.94, sensitivity 92%, specificity 95%, and PPV 52%) and 11 and higher in the second and third trimesters of pregnancy (AUC 0.96 and 0.90, respectively; sensitivity 100% and 88%, respectively; specificity 92% and 92%, respectively; PPV 25% and 29%, respectively). The EPDS is a reliable instrument for repeated evaluations of depressive symptoms during pregnancy. It has a good sensitivity and specificity for detecting antenatal MDD with optimal cutoff of 11/12 or higher.

MR elastography allows non-invasive quantification of the shear modulus of tissue, i.e. tissue stiffness and viscosity, information that offers the potential to guide presurgical planning for brain tumor resection. Here, we review brain tumor MRE studies with particular attention to clinical applications. Studies that investigated MRE in patients with intracranial tumors, both malignant and benign as well as primary and metastatic, were queried from the Pubmed/Medline database in August 2018. Reported tumor and normal appearing white matter stiffness values were extracted and compared as a function of tumor histopathological diagnosis and MRE vibration frequencies. Because different studies used different elastography hardware, pulse sequences, reconstruction inversion algorithms, and different symmetry assumptions about the mechanical properties of tissue, effort was directed to ensure that similar quantities were used when making inter-study comparisons. In addition, because different methodologies and processing pipelines will necessarily bias the results, when pooling data from different studies, whenever possible, tumor values were compared with the same subject's contralateral normal appearing white matter to minimize any study-dependent bias. The literature search yielded 10 studies with a total of 184 primary and metastatic brain tumor patients. The group mean tumor stiffness, as measured with MRE, correlated with intra-operatively assessed stiffness of meningiomas and pituitary adenomas. Pooled data analysis showed significant overlap between shear modulus values across brain tumor types. When adjusting for the same patient normal appearing white matter shear modulus values, meningiomas were the stiffest tumor-type. MRE is increasingly being examined for potential in brain tumor imaging and might have value for surgical planning. However, significant overlap of shear modulus values between a number of different tumor types limits applicability of MRE for diagnostic purposes. Thus, further rigorous studies are needed to determine specific clinical applications of MRE for surgical planning, disease monitoring and molecular stratification of brain tumors.