Alleviation of symptom severity for major depressive disorder (MDD) is known to be associated with a lagged improvement of functioning. Pharmacotherapy guidelines support algorithms for MDD treatment. However, it is currently unclear whether concordance with guidelines influences functional recovery. A guideline concordance algorithm (GCA-8) was used to measure this pathway in a naturalistic clinical setting.

Data from 1403 adults (67% female, 84% non-Hispanic/Latino White, mean age of 43 years) with nonpsychotic MDD from the Penn State Psychiatry Clinical Assessment and Rating Evaluation System registry (visits from 02/01/2015 to 04/13/2021) were evaluated. Multivariable linear regression measured associations between GCA-8 and World Health Organization Disability Assessment Schedule 2.0 (WHODAS) scores. Mediation by MDD symptom severity using the Patient Health Questionnaire depression module (PHQ-9) was also evaluated.

This study found a statistically significant improvement in WHODAS scores (functioning) between baseline and final measures (−2 points, P < .001) within one year. A one standard deviation increase in the GCA-8 score was associated with a 0.48-point reduction in mean disability score (total effect; P = .02) with significant mediation by the change in MDD symptom severity (coefficient = −0.51, P < .001) and a nonsignificant natural direct effect of the GCA-8 independent of PHQ-9 change (coefficient = −0.02, P = .92).

Higher pharmacotherapy guideline concordance is associated with better functioning for MDD patients; this association likely occurs through improvement in MDD symptom severity rather than directly.

In Egypt, palliative care for geriatric patients is understudied, necessitating exploration for service optimization. Amidst rising chronic illnesses and aging, understanding perspectives of geriatric patients and families is crucial for targeted improvements. This study aims to explore geriatric patients’ and their families’ perspectives on palliative care in Egypt, seeking opportunities to optimize service delivery for the elderly.

Employing a cross-sectional design with 110 geriatric patients and an equal number of family caregivers from the Damietta Oncology Institute and the pain treatment clinics for cancer patients at Zagazig University Hospital, the study focuses on a specialized pain clinic. Validated tools (Palliative Care Outcome Scale, Family Satisfaction with End-of-Life Care [FAMCARE] Scale, Edmonton Symptom Assessment System [ESAS], Caregiver Strain Index [CSI]) assess quality of life, family satisfaction, symptom severity, and caregiver strain.

Geriatric patients (mean age: 65.0 ± 8.1 years; 45.5% male, 55.5% female) have diverse diagnoses (e.g., breast cancer 22%). Palliative care outcomes reveal challenges: low emotional well-being (2.6 ± 0.0) and alarming overall quality of life (1.8 ± 0.0). Family dissatisfaction (FAMCARE) is pervasive (total mean score 2.6 ± 0.5). Symptom severity (ESAS) is high, and caregiver strain (CSI) is notable (8.5 ± 2.2).

The findings underscore the significance of the challenges faced by geriatric patients and caregivers in palliative care. Patients confront considerable symptom burdens and emotional distress, while caregivers experience notable strain. Urgently needed are targeted interventions designed to enhance patient well-being, alleviate caregiver burden, and elevate satisfaction. The critical importance of implementing these interventions promptly is highlighted, as they are instrumental in improving the overall care experience for geriatric patients and their caregivers. Moreover, the results underscore the imperative of developing comprehensive support mechanisms to address the intricate dimensions of palliative care, ultimately contributing to a more compassionate and effective care continuum.

Enlarged pituitary gland volume could be a marker of psychotic disorders. However, previous studies report conflicting results. To better understand the role of the pituitary gland in psychosis, we examined a large transdiagnostic sample of individuals with psychotic disorders.

The study included 751 participants (174 with schizophrenia, 114 with schizoaffective disorder, 167 with psychotic bipolar disorder, and 296 healthy controls) across six sites in the Bipolar-Schizophrenia Network on Intermediate Phenotypes consortium. Structural magnetic resonance images were obtained, and pituitary gland volumes were measured using the MAGeT brain algorithm. Linear mixed models examined between-group differences with controls and among patient subgroups based on diagnosis, as well as how pituitary volumes were associated with symptom severity, cognitive function, antipsychotic dose, and illness duration.

Mean pituitary gland volume did not significantly differ between patients and controls. No significant effect of diagnosis was observed. Larger pituitary gland volume was associated with greater symptom severity (F = 13.61, p = 0.0002), lower cognitive function (F = 4.76, p = 0.03), and higher antipsychotic dose (F = 5.20, p = 0.02). Illness duration was not significantly associated with pituitary gland volume. When all variables were considered, only symptom severity significantly predicted pituitary gland volume (F = 7.54, p = 0.006).

Although pituitary volumes were not increased in psychotic disorders, larger size may be a marker associated with more severe symptoms in the progression of psychosis. This finding helps clarify previous inconsistent reports and highlights the need for further research into pituitary gland-related factors in individuals with psychosis.

The study is aimed to identify brain functional connectomes predictive of depressed and elevated mood symptomatology in individuals with bipolar disorder (BD) using the machine learning approach Connectome-based Predictive Modeling (CPM).

Functional magnetic resonance imaging data were obtained from 81 adults with BD while they performed an emotion processing task. CPM with 5000 permutations of leave-one-out cross-validation was applied to identify functional connectomes predictive of depressed and elevated mood symptom scores on the Hamilton Depression and Young Mania rating scales. The predictive ability of the identified connectomes was tested in an independent sample of 43 adults with BD.

CPM predicted the severity of depressed [concordance between actual and predicted values (r = 0.23, pperm (permutation test) = 0.031) and elevated (r = 0.27, pperm = 0.01) mood. Functional connectivity of left dorsolateral prefrontal cortex and supplementary motor area nodes, with inter- and intra-hemispheric connections to other anterior and posterior cortical, limbic, motor, and cerebellar regions, predicted depressed mood severity. Connectivity of left fusiform and right visual association area nodes with inter- and intra-hemispheric connections to the motor, insular, limbic, and posterior cortices predicted elevated mood severity. These networks were predictive of mood symptomatology in the independent sample (r ⩾ 0.45, p = 0.002).

This study identified distributed functional connectomes predictive of depressed and elevated mood severity in BD. Connectomes subserving emotional, cognitive, and psychomotor control predicted depressed mood severity, while those subserving emotional and social perceptual functions predicted elevated mood severity. Identification of these connectome networks may help inform the development of targeted treatments for mood symptoms.

Abnormalities in emotion recognition (ER) are frequently reported in depression, with lowered recognition accuracy in patients with major depressive disorder (MDD) when compared to healthy individuals. Mindfulness was found to directly impact the severity of depressive symptoms, by negative cognition and dysfunctional reaction recognition.

The aims of this study were to compare ER and mindfulness levels between MDD patients and healthy controls (HC), as well as to examine whether ER and mindfulness are related to symptom severity in MDD patients.

68 patients with MDD and 93 HC participated in the study. A sociodemographic form, Reading the Mind in the Eyes Test (RMET), Five Facet Mindfulness Questionnaire-Short Form (FFMQ-S) and the Montgomery Asperg Depression Scale (MADRS) were administered. Group comparison in ER and mindfulness was assessed using the Multivariate analysis of covariance (MANCOVA). Bivariate correlations and multiple linear regression analyses were performed to assess the associations between depression severity, ER and mindfulness in the patient group.

Better ER and higher levels of mindfulness were found in HCs relative to the MDD group. A positive association between depression severity and the non-reactivity facet of mindfulness was found, indicating that in the MDD group non-reactivity was a significant predictor for depression severity. On the other hand, ER was not significant in predicting symptom severity.

Non-reactivity, unlike other dimensions of mindfulness, seems to increase with the severity of depressive symptoms among MDD patients. To particularly focus on this subdimension in mindfulness techniques may yield better outcomes in alleviation of depressive symptoms.

No significant relationships.

Almost all depression measures have been developed without discussing how to best conceptualize and assess the severity of depression. It is therefore not surprising that measures differ in both how items are rated and item content. The question that we address in the present report from the Rhode Island Methods to Improve Diagnostic Assessment and Services (MIDAS) project is whether a measure of depression severity should include symptoms that are frequent in depressed patients but are defining features of other disorders (eg, anxiety, irritability)

Patients were evaluated with a semi-structured interview and severity ratings were made of each symptom of major depressive disorder (MDD) as well as anxiety, irritability, and somatization. Patients were also rated on the Clinical Global Index of severity (CGI).

Three of the 5 nondepressive symptoms (psychic anxiety, somatic anxiety, and subjective anger) were significantly correlated with the CGI. The correlation between the sum of all 5 nondepressive symptoms and the CGI was significantly lower than the correlation between the sum of the depressive symptom severity ratings (0.12 vs 0.52, z = 11.0, p < .001). The partial correlation between the CGI and the nondepressive symptom severity ratings (after controlling for the total depressive symptom ratings) was nonsignificant.

After accounting for the severity of depressive symptoms, the severity of the nondepressive symptoms was not associated with global ratings of depressive severity. These findings raise questions regarding the appropriateness of including ratings of anxiety, irritability, and somatization on a measure that purportedly assesses the severity of depression.

Many studies have reported hippocampal volume reductions associated with posttraumatic stress disorder (PTSD), while others have not. Here we provide an updated meta-analysis of such reductions associated with PTSD and evaluate the association between symptom severity and hippocampal volume.

A total of 37 studies met the criteria for inclusion in the meta-analysis. Mean effect sizes (Hedges’ g) and 95% confidence intervals (CI95%) were computed for each study and then averaged to obtain an overall mean effect size across studies. Meta-regression was employed to examine the relationship between PTSD symptom severity and hippocampal volume.

Results showed that PTSD is associated with significant bilateral reduction of the hippocampus (left hippocampus effect size=–0.400, p<0.001, 5.24% reduction; right hippocampus effect size=–0.462, p<0.001, 5.23% reduction). Symptom severity, as measured by the Clinician-Administered PTSD Scale (CAPS), was significantly associated with decreased left, but not right, hippocampal volume.

PTSD was associated with significant bilateral volume reduction of the hippocampus. Increased symptom severity was significantly associated with reduced left hippocampal volume. This finding is consistent with the hypothesis that PTSD is more neurotoxic to the left hippocampus than to the right. However, whether the association between PTSD and lower hippocampal volume reflects a consequence of or a predisposition to PTSD remains unclear. More prospective studies are needed in this area.