Predictors of quality of life, functional status, depression and fatigue in early arthritis: comparison between clinically suspect arthralgia, unclassified arthritis and rheumatoid arthritis.

BACKGROUND: Rheumatoid arthritis (RA) is often preceded by symptomatic phases during which classification criteria are not fulfilled. The health burden of these "at-risk" stages is not well described. This study assessed health-related quality of life (HRQoL), function, fatigue and depression in newly presenting patients with clinically suspect arthralgia (CSA), unclassified arthritis (UA) or RA. METHODS: Cross-sectional analysis of baseline Patient-Reported Outcome Measures (PROMs) was conducted in patients from the Birmingham Early Arthritis Cohort. HRQoL, function, depression and fatigue at presentation were assessed using EQ-5D, HAQ-DI, PHQ-9 and FACIT-F. PROMs were compared across CSA, UA and RA and with population averages from the HSE with descriptive statistics. Multivariate linear regression assessed associations between PROMs and clinical and sociodemographic variables. RESULTS: Of 838 patients included in the analysis, 484 had RA, 200 had CSA and 154 had UA. Patients with RA reported worse outcomes for all PROMs than those with CSA or UA. However, "mean EQ-5D utilities were 0.65 (95%CI: 0.61 to 0.69) in CSA, 0.61 (0.56 to 0.66) in UA and 0.47 (0.44 to 0.50) in RA, which was lower than in general and older (≥ 65 years) background populations." In patients with CSA or UA, HRQoL was comparable to chronic conditions such as heart failure, severe COPD or mild angina. Higher BMI and older age (≥ 60 years) predicted worse depression (PHQ-9: -2.47 (-3.85 to -1.09), P < 0.001) and fatigue (FACIT-F: 5.05 (2.37 to 7.73), P < 0.001). Women were more likely to report worse function (HAQ-DI: 0.13 (0.03 to 0.21), P = 0.01) and fatigue (FACIT-F: -3.64 (-5.59 to -1.70), P < 0.001), and residents of more deprived areas experienced decreased function (HAQ-DI: 0.23 (0.10 to 0.36), P = 0.001), greater depression (PHQ-9: 1.89 (0.59 to 3.18), P = 0.004) and fatigue (FACIT-F: -2.60 (-5.11 to 0.09), P = 0.04). After adjustments for confounding factors, diagnostic category was not associated with PROMs, but disease activity and polypharmacy were associated with poorer performance across all PROMs. CONCLUSIONS: Patient-reported outcomes were associated with disease activity and sociodemographic characteristics. Patients presenting with RA reported a higher health burden than those with CSA or UA, however HRQoL in the pre-RA groups was significantly lower than population averages.

Psychometric validation of the 15-item Patient Health Questionnaire - Anxiety and Depression Scale (PHQ-ADS) to assess psychological distress in breast cancer survivors.

OBJECTIVE: Psychological distress persists amongst breast cancer survivors, so reliable assessment of symptoms is essential. The Patient Health Questionnaire Anxiety and Depression Scale (PHQ-ADS) is a composite measure of depression and anxiety and has been used to measure distress. This study aimed to evaluate the psychometric properties of the PHQ-ADS within breast cancer survivors. METHOD: Breast cancer survivors (N = 280) were recruited online and followed up at 12-months. Depression (PHQ-8) and anxiety (GAD-7) items formed the composite PHQ-ADS score. Additional measures included: distress thermometer (convergent validity), fear of cancer recurrence and COVID distress (discriminant validity), and self-compassion (predictive validity). Confirmatory factor analysis (CFA) using weighted least squares mean and variance adjusted estimation was undertaken. RESULTS: One, two, and bifactor models underlying the PHQ-ADS were evaluated. The bifactor model had the most appropriate model fit overall. Omega hierarchical for the general distress factor was 0.914, accounting for 82% of explained variance. This suggests the PHQ-ADS is sufficiently unidimensional to warrant use of a total composite score. The PHQ-ADS demonstrated strong convergent and moderate discriminant validity. Self-compassion was an independent predictor of distress at 12-months. CONCLUSIONS: The PHQ-ADS is a valid measure for psychological distress in breast cancer survivors prescribed hormone therapy.

Validation of the Distress Thermometer as a Screening Tool for Psychosocial Distress and Resilience in Parkinson's Disease.

BACKGROUND: Parkinson's disease (PD) is associated with psychosocial distress that affects patients' quality of life. The distress thermometer (DT) is an 11-point visual analogue scale that is used as a screening tool for the assessment of psychosocial distress, originally developed for oncological diseases. OBJECTIVES: To validate the DT for PD and to explore contributing factors. METHODS: The DT scale was administered to 105 people with Parkinson's Disease (PwPD). Along with it, we assessed motor symptoms (Unified Parkinson's Disease Rating Scale part III [UPDRS III], Hoehn and Yahr-stage [H&Y]), non-motor symptoms (Non-motor Symptom Questionnaire [NMSQ]), anxiety and depression (Hospital Anxiety and Depression Scale [HADS], Fear of Progression-Questionnaire Short Form [FOP-Q-SF], Generalized Anxiety Disorder Scale-7 [GAD-7], 9-question Patient Health Questionnaire [PHQ-9]), the feeling of hope (Herth Hope Index [HHI]) and quality of life (Schedule for the Evaluation of Individual Quality of Life [SEIQoL]). RESULTS: With a cut-off of 4, the DT identified PwPD with distress with a sensitivity of 97% and a specificity of 38%. With this cut-off, the DT will yield false negative results in 1 out of 100 cases. Factor analyses and a random forest regression of the dataset revealed that distress can be predicted by two factors, which we termed "anxiety" and "depression/resilience/motor symptoms". CONCLUSION: The DT is an ultra-short and reliable screening tool for distress in PwPD. DT values below 4 rule out distress with a high degree of certainty. Anxiety and depression are important factors in distress but are counterbalanced by the individuals' psychological resilience.

Examining the validity and reliability of the Arabic translated version of the depression and somatic symptoms scale (A-DSSS) among the Lebanese adults.

The prevalence of depression is high worldwide, and somatic symptoms are known to be one of the most debilitating aspects of depression. However, clinicians often face challenges in accurately assessing this comorbidity. To address this issue, the Depression and Somatic Symptoms Scale (DSSS) was developed as a self-administered scale that can diagnose both depression and somatic symptoms. The objective of this study is to evaluate the validity and reliability of the Arabic-translated version of the DSSS (A-DSSS) in a sample of Lebanese adults, as well as to explore its associated factors. A cross-sectional study was conducted over a period of one month, from February to March 2023, and involved a sample of 422 participants who were aged 18 years or older. Participants completed a questionnaire that included various measures, including demographic characteristics, alcohol and smoking habits, physical activity history, as well as two scales: the Patient Health Questionnaire-9 (PHQ9) scale and the A-DSSS scale. The A-DSSS showed high internal consistency (Cronbach's alpha = 0.936), strong test-retest reliability (ICC of 0.988 with CI 0.976-0.994; p < 0.001), and a three-factor structure consistent with previous research. Convergent validity was supported by a significant correlation with the PHQ-9. Stepwise linear regression revealed that engaging in physical activity and increasing calorie consumption (as measured by MET-min/week score) were associated with a significant decrease in the A-DSSS total score and subscales. However, a significant increase in the A-DSSS total score was seen in the female gender in comparison for male gender. The A-DSSS revealed good psychometric properties and may be a useful tool for assessing depression and somatic symptoms in this population. The study also identified potential factors associated with depression and somatic symptoms, such as physical activity, calorie consumption, and gender, which may have implications in addressing depression and somatic symptoms for future interventions and clinical practice.

Identification of depression in patients with acute coronary syndrome using multiple serum biomarkers.

BACKGROUND: Biomarkers for depression in patients with acute coronary syndrome (ACS) have not been identified. METHODS: This study evaluated multiple serum biomarkers for depressive disorders after ACS. Thirteen serum biomarkers associated with seven functional systems, along with sociodemographic/clinical characteristics, were evaluated in 969 patients within 2 weeks after ACS onset (acute phase). In total, 711 patients were evaluated for depressive disorder using DSM-IV criteria 1 year later (chronic phase). Logistic regression was used for the analysis. RESULTS: Depressive disorders were observed in 378 patients (39.0%) in the acute phase of ACS and 183 patients (25.7%) in the chronic phase. The weighted scores of five serum biomarkers (high-sensitivity C-reactive protein, interleukin-6, homocysteine, troponin I, and creatine kinase-MB) were significantly associated with depressive disorder diagnosis in the acute phase, and the weighted scores of three other biomarkers (tumor necrosis factor-alpha, interleukin-1 beta, and homocysteine) were significantly associated with depressive disorders in the chronic phase, in a dose-dependent manner after adjusting for relevant covariates (all P-values <0.001). CONCLUSIONS: The combination of several serum biomarkers exhibited robust associations with depressive disorders in both the acute and chronic phases of ACS.

Dietary Factors and the Risk of Depression among Women with Polycystic Ovary Syndrome.

This study aimed to assess the association between dietary factors and depression in a group of polycystic ovary syndrome (PCOS) women and to evaluate potential interactions and the mediating role of BMI in this relationship. One hundred and sixteen women with PCOS were asked to complete the Dietary Habits and Nutrition Beliefs Questionnaire and the manual for developing of nutritional data (KomPAN questionnaire) and the Beck Depression Inventory. The population was divided into two groups: (1) not at risk of depression (ND), n = 61, and (2) at risk of depression (RD), n = 55. Significantly higher BMI values were observed in the RD group than in the ND group. In the RD group, the intake of vegetables and legumes was lower than in the LD group, but the consumption of sweet beverages and energy drinks was higher. Consumption of vegetables and legumes at least twice per day is known to be associated with a 62% lower probability of the risk of depression in PCOS women. Furthermore, women with overweight and obesity have a 5.82 times greater chance of depression than women with normal body weight. Our findings show that there is a significant association between certain dietary factors, BMI, and symptoms of depression in PCOS women.

A longitudinal study of symptom cluster latent profiles in ovarian cancer patients undergoing chemotherapy.

BACKGROUND: This study aimed to identify distinct patterns within the symptom cluster of fatigue, pain, and sleep disturbance among ovarian cancer patients receiving chemotherapy, to determine the factors predicting these patterns and their impact on quality of life. METHODS: The longitudinal study collected data from 151 ovarian cancer patients at three time points: before chemotherapy (T0), after the first chemotherapy cycle (T1), and following the completion of four cycles of chemotherapy (T2). Latent profile analysis and latent transition analysis were used to identify symptom patterns and evaluate changes in symptom patterns. A bias-adjusted three-step approach was utilized to examine predictor variables and distal outcomes associated with latent class membership. RESULTS: Three symptom patterns emerged: "All Low," "Moderate" (T0)/"Low pain and high sleep disturbance" (T1 and T2), and "All High." Patients with lower educational attainment and higher levels of anxiety and depression were found to be at an elevated risk of belonging to the "All High" class. All quality-of-life domains showed significant differences among the three subgroups, following an "All Low" > "All High" pattern (p < 0.05). Membership in three classes remained relatively stable over time, with probabilities of 0.749 staying within their groups from T0 to T2. CONCLUSIONS: This study underscores the existence of a diverse and heterogeneous experience within the symptom cluster of fatigue, pain, and sleep disturbance among ovarian cancer patients. Importantly, these patterns were stable throughout chemotherapy. Recognizing and understanding these patterns can inform the development of targeted interventions to alleviate the burden of symptom clusters in this population.

Sleep quality, quality of life, fatigue, and mental health in COVID-19 post-pandemic Türkiye: a cross-sectional study.

Aim: This study explores the predictors and associated risk factors of sleep quality, quality of life, fatigue, and mental health among the Turkish population during the COVID-19 post-pandemic period. Materials and methods: A cross-sectional survey using multi-stage, stratified random sampling was employed. In total, 3,200 persons were approached. Of these, 2,624 (82%) completed the questionnaire package consisting of socio-demographic information, Pittsburgh Sleep Quality Index (PSQI), the WHO Quality of Life Brief Version (WHOQOL-BREF), Fatigue Assessment Scale (FAS), Patients Health Questionnaire (PHQ-15), GAD-7 anxiety scale, and the 21-item Depression, Anxiety, Stress Scale (DASS-21). Results: Significant differences between genders were found regarding socio-demographic characteristics (p < 0.01). Using PHQ-15 for depressive disorders, significant differences were found between normal and high severity scores (≥ 10), regarding age group (p < 0.001), gender (p = 0.049), educational level (p < 0.001), occupational status (p = 0.019), cigarette smoking (p = 0.002), waterpipe-narghile smoking (p = 0.039), and co-morbidity (p = 0.003). The WHOQOL-BREF indicated strong correlations between public health, physical health, psychological status, social relationships, environmental conditions, and sleep disorders (p < 0.01). Furthermore, comparisons of the prevalence of mental health symptoms and sleeping with PHQ-15 scores ≥ 10 (p = 0.039), fatigue (p = 0.012), depression (p = 0.009), anxiety (p = 0.032), stress (p = 0.045), and GAD-7 (p < 0.001), were significantly higher among the mental health condition according to sleeping disorder status. Multiple regression analysis revealed that DASS21 stress (p < 0.001), DASS21 depression (p < 0.001), DASS21 anxiety (p = 0.002), physical health (WHOQOL-BREF) (p = 0.007), patient health depression-PHQ-15 (p = 0.011), psychological health (WHOQOL-BREF) (p = 0.012), fatigue (p = 0.017), and environmental factors (WHOQOL-BREF) (p = 0.041) were the main predictor risk factors associated with sleep when adjusted for gender and age. Conclusion: The current study has shown that sleep quality was associated with the mental health symptoms of depression, anxiety, stress, and fatigue. In addition, insufficient sleep duration and unsatisfactory sleep quality seemed to affect physical and mental health functioning.

What Is Perinatal Depression?

This JAMA Patient Page describes perinatal depression screening and diagnosis and available treatment options.

Effect of Esketamine on perioperative anxiety and depression in women with systemic tumors based on big data medical background.

OBJECTIVE: Perioperative anxiety and depression syndrome (PADS) is a common clinical concern among women with systemic tumors. Esketamine has been considered for its potential to alleviate anxiety and depressive symptoms. However, its specific application and effectiveness in PADS among women with systemic tumors remain unclear. This study aimed to analyze the utility of Machine Learning (ML) algorithms based on electroencephalogram (EEG) signals in evaluating perioperative anxiety and depression in women with systemic tumors treated with Esketamine, utilizing a large-scale medical data background. PATIENTS AND METHODS: A single-center, randomized, placebo-controlled (SC-RPC) trial design was adopted. A total of 112 female patients with systemic tumors and PADS who received Esketamine treatment were included as study participants. A moderate dose (0.7 mg/kg) of Esketamine was administered through intravenous infusion over a duration of 60 minutes. EEG signals were collected from all patients, and the EEG signal features of individuals with depression were compared to those without depression. In this study, a Support Vector Machine (SVM)-K-Nearest Neighbour (KNN) hybrid classifier was constructed based on SVM and KNN algorithms. Using the EEG signals, the classifier was utilized to assess the anxiety and depression status of the patients. The predictive performance of the classifier was evaluated using accuracy, sensitivity, and specificity measures. RESULTS: The C2 correntropy feature of the delta rhythm in the left-brain EEG signal was significantly higher in individuals with depression compared to those without depression (p<0.05). Moreover, the C2 correntropy feature of the Alpha, Beta, and Gamma rhythms in the left-brain EEG signal was significantly lower in individuals with depression compared to those without depression (p<0.05). In the right brain EEG signal, the C2 correntropy feature of the delta rhythm was significantly higher in individuals with depression (p<0.05), while the C2 correntropy feature of the alpha and gamma rhythms was significantly lower in individuals with depression compared to those without depression (p<0.05). Additionally, the C1 correntropy feature of the Gamma rhythm in the right brain EEG signal was significantly higher in individuals with depression compared to those without depression (p<0.05). The SVM classifier achieved accuracy, sensitivity, and specificity of 98.23%, 98.10%, and 98.56%, respectively, in recognizing the left-brain EEG signals, with a correlation coefficient of 0.95. In recognizing the right brain EEG signals, the SVM classifier achieved accuracy, sensitivity, and specificity of 98.74%, 98.43%, and 99.03%, respectively, with a correlation coefficient of 0.96. The improved SVM-KNN approach yielded an accuracy, recall, precision, F-score, area over the curve (AOC), and Receiver Operation Characteristics (ROC) of 0.829, 0.811, 0.791, 0.853, 0.787, and 0.877, respectively, in predicting anxiety. For predicting depression, the accuracy, recall, precision, F-score, AOC, and ROC were 0.869, 0.842, 0.831, 0.893, 0.827, and 0.917, respectively. CONCLUSIONS: Significant differences were observed in the brain EEG signals between individuals with depression and those without depression. The improved SVM-KNN algorithm developed in this study demonstrates good predictive capability for anxiety and depression.

Establishing the sensitivity and specificity of the gynaecological cancer distress screen.

OBJECTIVE: Nuanced distress screening tools can help cancer care services manage specific cancer groups' concerns more efficiently. This study examines the sensitivity and specificity of a tool specifically for women with gynaecological cancers (called the Gynaecological Cancer Distress Screen or DT-Gyn). METHODS: This paper presents cross-sectional data from individuals recently treated for gynaecological cancer recruited through Australian cancer care services, partner organisations, and support/advocacy services. Receiver operating characteristics analyses were used to evaluate the diagnostic accuracy of the DT-Gyn against criterion measures for anxiety (GAD-7), depression (patient health questionnaire), and distress (IES-R and K10). RESULTS: Overall, 373 individuals aged 19-91 provided complete data for the study. Using the recognised distress thermometer (DT) cut-off of 4, 47% of participants were classified as distressed, while a cut-off of 5 suggested that 40% had clinically relevant distress. The DT-Gyn showed good discriminant ability across all measures (IES-R: area under the curve (AUC) = 0.86, 95% CI = 0.82-0.90; GAD-7: AUC = 0.89, 95% CI = 0.85-0.93; K10: AUC = 0.88, 95% CI = 0.85-0.92; PHQ-9: AUC = 0.85, 95% CI = 0.81-0.89) and the Youden Index suggested an optimum DT cut-point of 5. CONCLUSIONS: This study established the psychometric properties of the DT-Gyn, a tool designed to identify and manage the common sources of distress in women with gynaecological cancers. We suggest a DT cut point ≥5 is optimal in detecting 'clinically relevant' distress, anxiety, and depression in this population.

Anxiety evaluated by the Hospital Anxiety and Depression Scale as a predictor of postoperative nausea and vomiting: a pilot study.

The incidence of postoperative nausea and vomiting (PONV) remains high, and improving the accuracy of PONV prediction remains challenging. The primary aim of this study is to examine the impact of anxiety scores evaluated using the Hospital Anxiety and Depression Scale (HADS) on the PONV prediction model. We hypothesized that anxiety and depression, quantified using the HADS, could improve the accuracy of the PONV predictive model. This pilot study evaluated 100 patients. The HADS was conducted by a self-evaluation method before thoracoscopic surgery for lung tumors, and the anesthesia method was standardized. The criterion was whether the nurse in charge of the patient who complained of PONV assessed that drug administration was necessary. As the main analysis, the odds ratio of the HADS score for predicting PONV was evaluated using multivariable logistic regression models. Further, the receiver operating characteristic (ROC) curves of the model with the HADS score added to the variables of without-anxiety predictors and the model with the variables of without-anxiety predictors only were compared. The anxiety score was significantly higher in the PONV group than in the no PONV group (P = 0.021). For predictive accuracy, the model that included age, sex, smoking history, history of PONV, and anxiety score had a higher area under the ROC curve than did the model excluding the anxiety score (P = 0.021). In conclusion, the findings indicate that the HADS is worth investigating as a predictor of PONV.

A Randomized Trial of Two Remote Health Care Delivery Models on the Uptake of Genetic Testing and Impact on Patient-Reported Psychological Outcomes in Families With Pancreatic Cancer: The Genetic Education, Risk Assessment, and Testing (GENERATE) Study.

BACKGROUND & AIMS: Genetic testing uptake for cancer susceptibility in family members of patients with cancer is suboptimal. Among relatives of patients with pancreatic ductal adenocarcinoma (PDAC), The GENetic Education, Risk Assessment, and TEsting (GENERATE) study evaluated 2 online genetic education/testing delivery models and their impact on patient-reported psychological outcomes. METHODS: Eligible participants had ≥1 first-degree relative with PDAC, or ≥1 first-/second-degree relative with PDAC with a known pathogenic germline variant in 1 of 13 PDAC predisposition genes. Participants were randomized by family, between May 8, 2019, and June 1, 2021. Arm 1 participants underwent a remote interactive telemedicine session and online genetic education. Arm 2 participants were offered online genetic education only. All participants were offered germline testing. The primary outcome was genetic testing uptake, compared by permutation tests and mixed-effects logistic regression models. We hypothesized that Arm 1 participants would have a higher genetic testing uptake than Arm 2. Validated surveys were administered to assess patient-reported anxiety, depression, and cancer worry at baseline and 3 months postintervention. RESULTS: A total of 424 families were randomized, including 601 participants (n = 296 Arm 1; n = 305 Arm 2), 90% of whom completed genetic testing (Arm 1 [87%]; Arm 2 [93%], P = .014). Arm 1 participants were significantly less likely to complete genetic testing compared with Arm 2 participants (adjusted ratio [Arm1/Arm2] 0.90, 95% confidence interval 0.78-0.98). Among participants who completed patient-reported psychological outcomes questionnaires (Arm 1 [n = 194]; Arm 2 [n = 206]), the intervention did not affect mean anxiety, depression, or cancer worry scores. CONCLUSIONS: Remote genetic education and testing can be a successful and complementary option for delivering genetics care. (Clinicaltrials.gov, number NCT03762590).

Racial Disparities in Diagnosis and Treatment of Depression Associated with Androgen Deprivation Therapy for Prostate Cancer.

OBJECTIVE: To analyze potential racial disparities in the diagnosis and management of depression associated with androgen deprivation therapy. METHODS: TriNetX health record network was queried for prostate cancer patients treated with androgen deprivation therapy from 2003-2023. Differences in rates of depression diagnosis and treatment were compared between White and Black patients. Means, odds ratios, and t tests were calculated in univariate analysis with 95% confidence intervals (CI). RESULTS: Data were queried from 93 health care organizations to yield 78,313 prostate cancer patients treated with androgen deprivation therapy. Patients on androgen deprivation therapy had 60% greater odds of developing depression vs other patients [9% vs 6%; odds ratio (OR) 1.6; 95% CI (1.5-1.7); P <.0001]. Of those with depression secondary to androgen deprivation therapy, only 35% were treated with antidepressants. After starting androgen deprivation therapy, White patients had 30% greater odds of being diagnosed with depression, compared to Black patients [10% vs 8%; OR 1.3; 95% CI (1.2-1.4); P <.001]. White patients also had higher odds of being treated with a first line antidepressant than Black patients [56% vs 48%; OR 1.4, 95% CI (1.2-1.6), P <.001]. CONCLUSION: This analysis confirms a significant association between androgen deprivation therapy and the development of clinical depression, and highlights its medical undertreatment. Importantly, our findings also indicate significant racial disparities in the identification and treatment of depression. Routine screening initiatives that account for social determinants of health may alleviate this disparity. Limitations of this study include retrospective design and lack of data describing severity of depression, which might correlate with need for medication.

Depression in patients with hematologic malignancies: The current landscape and future directions.

Patients with hematologic malignancies experience high rates of depression. These patients are vulnerable to depression throughout the disease trajectory, from diagnosis to survivorship, and at the end of life. In addition to the distressing nature of depression, it has substantial downstream effects including poor quality of life, increased risk of treatment complications, and worse survival. Therefore, systematic screening for depression and integration of robust psychological interventions for affected patients is crucial. Although depression has been historically studied mostly in patients with solid malignancies, research focusing on patients with hematologic malignancies is growing. In this article, we describe what is known about depression in patients with hematologic malignancies, including its assessment, prevalence, risk factors, and implications. We also describe interventions to ameliorate depression in this population. Future research is needed to test effective and scalable interventions to reduce the burden of depression among patients with blood cancers.

Can Muscular Parameters Predict Symptoms of Anxiety and Depression?

Major depressive disorder and anxiety disorders are among the major public health issues. Therefore, identifying predictors of symptoms of depression and anxiety holds fundamental importance to avoid the aggravation of these conditions. Muscle strength and function (e.g., handgrip strength and timed-stands test) are widely recognized predictors of health outcomes; however, their association with symptoms of depression and anxiety is still not completely understood. This study investigated the associations between handgrip strength and timed-stands test scores with symptoms of depression and anxiety. In addition, we examined whether individuals exhibiting greater strength levels demonstrate reduced symptoms of anxiety and depression compared to those with lower levels of strength. This is a community-based, cross-sectional study. Participants were recruited through social media and underwent a semi-structured interview to record sociodemographic characteristics, comorbidities, use of tobacco and medication, and symptoms of anxiety (Beck's Anxiety Inventory [BAI]) and depression (Beck's Depressive Inventory [BDI]). Subsequently, anthropometric characteristics, handgrip strength, and functionality (i.e., timed-stands test) were assessed. In all, 216 individuals were evaluated. The adjusted regression model showed an inverse association between handgrip strength and anxiety (ß = -0.22; 95% CI [-0.38, -0.07]; R2 = 0.07, p = .005) and depression symptoms (ß = -0.25; 95% CI [-0.42, -0.07]; R2 = 0.05, p = .006). Similarly, timed-stands test scores were associated with anxiety (ß = -0.33; 95% CI [-0.54, -0.13]; R2 = 0.09, p = .002) and depression (ß = -0.32; 95% CI [-0.56, -0.09]; R2 = 0.06, p = .008). Furthermore, the low-strength group showed higher values on the BAI (9.5 vs. 5.9 arbitrary units; p = .0008) and BDI than the high-strength group (10.8 vs. 7.9 arbitrary units; p = .0214). When individuals were stratified by the timed-stands test, the low timed-stands group demonstrated higher values on the BAI (9.9 vs. 5.5 arbitrary units; p = .0030) and BDI than the high timed-stands group (11.2 vs. 7.5 arbitrary units; p < .0001). The results highlight muscular parameters as significant predictors associated with anxiety and depression symptoms.

Post-traumatic Stress and Depressive Symptoms in Women With Ovarian Cancer 3-6 Months After Diagnosis.

BACKGROUND/AIM: The potentially traumatic role of severe life-threatening medical conditions is still debated in psychiatry and not yet recognized, particularly among post-traumatic stress disorders. However, increasing evidence suggests the psychopathological impact of severe medical conditions related to their poor prognosis, high lethality, treatments heaviness and invasiveness. Ovarian cancer (OC) is one of the malignancies with the highest mortality and the aim of this study was to investigate post-traumatic stress and depressive symptoms in women 3 to 6 months after diagnosis. PATIENTS AND METHODS: A sample of 83 women diagnosed with OC at different stages (from AI to IV) was recruited and assessed by means of the: Structural Clinical Interview for Mental Disorders according to DSM-5 (SCID-5), Trauma and Loss Spectrum Self-Report (TALS-SR), Impact Event Scale-Revised (IES-R), Hamilton Rating Scale for Depression (HAM-D), Mood Spectrum-Self Report (MOOD-SR), Work and Social Adjustment Scale (WSAS). RESULTS: Full data on the psychiatric assessments were available for 45 patients: 13 (28.9%) patients reported a diagnosis of PTSD. Patients with PTSD reported statistically significant higher depressive symptoms and more severe impact on work and social functioning compared to those without PTSD. CONCLUSION: Our results highlight the need to carefully assess the potentially traumatic burden of a diagnosis of OC and its association with depressive symptoms for their impact on patients' global functioning, in order to provide appropriate preventive and therapeutic interventions.