Transdiagnostic and functional predictors of depression severity and trajectory in the Penn state psychiatry clinical assessment and rating evaluation system (PCARES) registry.

BACKGROUND: Timely, accurate diagnosis and subsequent identification of risk factors for depression that is difficult-to-treat can aid in decreasing the burden of depressive illness and reducing probability of future disability. We aimed to identify sociodemographic, clinical, and functional factors that predict depression severity over one year in a real-world, naturalistic, transdiagnostic clinical sample. A subset sample with moderate depression was examined to determine the magnitude of improvement. METHODS: The Penn State Psychiatry Clinical Assessment and Rating System (PCARES) Registry houses data from systematically-structured patient-reported outcomes and clinical data from an Electronic Medical Record (EMR) gathered during routine clinical care of patients seeking mental health care at a mid-Atlantic clinic. Self-report symptom and functional measures were obtained, and sociodemographic features and clinical diagnoses were extracted from the EMR from 1,766 patients between 2/6/2016 to 9/30/2019. The Patient Health Questionnaire 9 (PHQ-9) depression scale was obtained at each visit. Using a discrete mixture clustering model, the study population was divided into five longitudinal trajectory groups, termed depression severity groups, based on intra-individual PHQ-9 score trajectories over one year. Multinomial logistic regression models were estimated to evaluate associations between characteristics and the likelihood of depression severity group membership. To determine the magnitude of improvement, predictors of the slope of the PHQ-9 trajectory were examined for patients with moderate depression. RESULTS: The strongest predictors of high depression severity over one year were poor functioning, high transdiagnostic DSM-5 Level 1 crosscutting symptom score, diagnosis of Post-Traumatic Stress Disorder (PTSD), public/self-pay insurance, female gender, and non-White race. Among the subset of patients with moderate depression, strong predictors of improvement were commercial insurance and exposure to trauma; the strongest predictors of worsening were high functional impairment, high transdiagnostic Level 1 symptom score, diagnosis of PTSD, diagnosis of bipolar disorder, and marital status of single or formerly married; depression-specific symptom measures were not predictive. LIMITATIONS: Limitations include inferring education and income status from zip code level-data, the non-random missingness of data, and the use of diagnoses collected from the electronic medical record. CONCLUSION: Functional impairment, transdiagnostic measures of symptom burden, and insurance status are strong predictors of depression severity and poor outcome.

Predictors of diagnostic delay: Assessment of psychiatric disorders in the clinic.

BACKGROUND: Diagnostic delay contributes to morbidity in psychiatric disorders. METHODS: Patients in an ambulatory psychiatry clinic were given patient-reported outcome measures at an initial visit, and a subset (N = 493) were given a structured interview (MINI International Neuropsychiatric Interview, MINI), in addition to the clinical encounter (CLIN). Diagnostic agreement between MINI and CLIN was assessed at an initial and follow-up visit. Diagnostic delay was identified if diagnostic disagreement between MINI and CLIN occurred at the initial visit and changed to an agreement at a follow-up visit. Registry data was compiled by an honest broker. RESULTS: Significant agreement occurred between MINI and CLIN diagnoses for major depressive disorder (MDD), bipolar disorder (BD), generalized anxiety disorder, and panic disorder. Diagnostic agreement for MDD occurred at initial visit for 63% of patients, and at follow-up for 87% of those with initial diagnostic disagreement; for BD, 75% at initial visit and 28% at follow-up. No demographic, socioeconomic, symptom severity or functioning measures predicted diagnostic agreement for the MDD group at the first visit, however initial psychopathological symptom complexity predicted diagnostic agreement in the diagnostic delay group. Initial diagnostic agreement for BD was predicted by lower symptom burden and better social, physical, and occupational functioning. No factors predicted additional diagnostic agreement at the second visit in the diagnostic delay group. CONCLUSION: Initial assessment by a structured interview aided physicians in identifying MDD by the second visit in patients with complex psychopathology. Patients with high complexity/severity of symptoms and more difficulty with functioning were less commonly identified with BD even with the assistance of a structured interview. Use of structured assessment tools may improve the detection of psychiatric illness by clinicians at the first visit.