Kernsmed7181

Suicide is the tenth leading cause of death in the United States. Several studies have leveraged electronic health record (EHR) data to predict suicide risk in veteran and military samples; however, few studies have investigated suicide risk factors in a large-scale community health population.

Clinical data was queried for 9,811 patients from the Penn Medicine Health System who had completed a Patient Health Questionnaire-9 (PHQ-9) documented in the EHR between January 2017 and June 2019. Patient demographics, PHQ-9 scores, and psychiatric comorbidities were extracted from the EHR. Univariate and multivariable logistic regressions were applied to determine significant risk factors associated with suicide ideation responses from the PHQ-9.

One-quarter (25.8%% of patients endorsed suicide ideation. Univariate analysis found 22 risk factors of suicide ideation. Multivariable logistic regression found significant positive associations (Odds Ratio, (95% Confidence Interval)) with the following younger ages less than 18 years 2.1, (1.69, 2.60) and 19-24 years 1.55, (1.29, 1.87)), single marital status (1.22, (1.08, 1.38)), African American (1.22, (1.08, 1.38)), non-commercial insurance (1.16, (1.03, 1.31)), multiple comorbidities (1 comorbidity (1.65, (1.32, 2.07); 2 comorbidities (2.07, (1.61, 2.64)), 3+ comorbidities (2.49, (1.87, 3.33))), bipolar disorders (Type I 1.38, (1.14, 1.67) and Type II 1.94, (1.52, 2.49)), depressive disorders (1.70, (1.49, 1.94)), obsessive compulsive disorder (OCD) (1.43, (1.08, 1.90)), and stress disorders (1.53, (1.33, 1.76)).

Community EHR information can be used to predict suicidal ideation. This information can be used to design tools for identifying patients at risk for suicide in real-time.

Community EHR information can be used to predict suicidal ideation. This information can be used to design tools for identifying patients at risk for suicide in real-time.

Medical diseases and depression frequently co-occur, but it remains uncertain whether specific medical diseases or the disease load, affect the clinical course of depression.

We identified all adults (≥18 years) at their first hospital-based diagnosis of unipolar depression in Denmark between 1996 and 2015. All medical hospital contacts since 1977 and all drug prescriptions during the previous year were identified. We followed patients for up to five years regarding hospital admissions with depression and performed adjusted Cox regression analyses calculating hazard rate ratios (HRR) including 95%-confidence intervals (CI) to test the association between medical diseases and depression admission following the index depressive episode.

Among 117,585 patients with depression (444,696 person-years follow-up), any prior medical hospital contact (N=114,206; 97.1%) was associated with increased risks of admission for depression among individuals aged 18-30 (HRR=1.50; 95%CI=1.15-1.95), 31-65 (HRR=1.69; 95%CI=1.28-2.21), and >65 years (HRR=1.38; 95%CI=1.10-1.75), fitting a dose-response relationship (p<0.005) with increasing number of prior medical diseases among those aged <65. All specific medical diseases were associated with increased risks of admission for depression, particularly among individuals aged<65 (HRR ranging from 1.57 to 2.38). Drug prescriptions and medical hospital contacts in the year before the depression diagnosis were associated with reduced risks of admission.

The medical load seems to be associated with an increased risk for depression admission, particularly among individuals aged <65. The lower risk for people in medical care during the previous year may indicate better compliance and care/treatment.

The medical load seems to be associated with an increased risk for depression admission, particularly among individuals aged less then 65. The lower risk for people in medical care during the previous year may indicate better compliance and care/treatment.

An outbreak of coronavirus disease 2019 (COVID-19) is a public health emergency of international concern and poses a big challenge to medical staff and general public. The aim is to investigate psychological impact of COVID-19 epidemic on medical staff in different working posts in China, and to explore the correlation between psychological disorder and the exposure to COVID-19.

A multicenter WeChat-based online survey was conducted among medical staff in China between 26 February and 3 March 2020. Medical staff deployed to Hubei province from other provinces and medical staffs in different posts outside Hubei were selected to represent diverse exposure intensities to the threat of COVID-19. Anxiety, depression, sleep quality, stress and resilience were evaluated using scales including GAD-7, PHQ-9, PSQI, PSS-14, and CD-RISC-10. Latent class analysis was performed to identify potential staff requiring psychological support.

A total of 274 respondents were included, who serving at 4 posts as follows, staders, suggesting continuous and proper psychiatric intervention are needed.

High prevalence of anxiety, depression and insomnia exist in medical staff related to COVID-19. The higher the probability and intensity of exposure to COVID-19 patients, the greater the risk that medical staff will suffer from mental disorders, suggesting continuous and proper psychiatric intervention are needed.

Neuroinflammation plays a role in the pathophysiology of Bipolar Disorder Depression (BDD) and altered levels of inflammatory mediators, such as monocyte chemoattractant protein-1 (MCP-1, aka CCL2) have been reported. This study reports specifically on MCP-1 levels, as a potential marker of BDD and/or treatment response in patients receiving combination treatment with the cyclooxygenase-2 inhibitor, celecoxib (CBX).

In this randomized, 10-week, double-blind, two-arm, placebo-controlled study, 47 patients with treatment resistant BDD received either escitalopram (ESC)+CBX, or ESC+placebo (PBO). Plasma MCP-1 levels were measured at 3 time points in the BDD subjects, and in a healthy control (HC) group. Depression severity was quantified using the Hamilton Depression Scale (HAMD-17).

The CBX group had significantly lower HAMD-17 scores vs. PBO at week 4 (P=0.026) and week 8 (P=0.002). MCP-1 levels were not significantly different in BDD vs. selleck compound HC subjects at baseline (P=0.588), nor in CBX vs. PBO groups at week 8 (P=0.