RESUMEN
Several magnetic resonance imaging (MRI) studies have reported reduction in anterior cingulate cortex (ACC) volume in individuals with major depressive disorder (MDD). However, some MRI studies did not find significant ACC volumetric changes in MDD, and sample sizes were generally small. This cross-sectional structural MRI study examined the relationship between current depressive symptoms and ACC volume in a large community sample of 1803 adults. A series of multiple linear regression analyses were conducted to predict right and left ACC volumes using Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) scores, intracranial volume, age, sex, race/ethnicity, alcohol use, tobacco use, and psychotropic medications as predictor variables. Right ACC volume was significantly negatively associated with QIDS-SR scores, while no significant association was found between left ACC volume and QIDS-SR scores. In addition, there was a significant negative association between QIDS-SR scores and right but not left ACC volumes in males, and no significant association between QIDS-SR scores and right or left ACC volumes in females. These findings suggest that right ACC volume is reduced in people with greater self-reported depressive symptom severity, and that this association is only significant in men.
Asunto(s)
Depresión , Trastorno Depresivo Mayor , Adulto , Estudios Transversales , Depresión/diagnóstico por imagen , Trastorno Depresivo Mayor/diagnóstico por imagen , Femenino , Giro del Cíngulo/diagnóstico por imagen , Humanos , Imagen por Resonancia Magnética/métodos , MasculinoRESUMEN
Measurement-based care (MBC) involves the systematic use of standardized measurements to inform treatment decisions. MBC can enhance clinical decision-making and quality of care by prompting personalized changes in treatment based on measured patient outcomes. MBC can also promote more precise communications between patients and clinicians around individual patient care. While commonly employed in psychiatric clinical research, the use of MBC in everyday practice can be complicated by clinic operations and variability across patients. We implemented MBC in the UT Southwestern Psychiatry Multispecialty Outpatient Clinic during the expansion of our general psychiatry clinic and subspecialty targeted programs. This article describes the top 10 lessons we learned as we confronted practical obstacles around implementing the ideals of MBC into a pre-existing, busy psychiatric clinical practice and how doing so impacts care, provider engagement, patient engagement, and research opportunity.
RESUMEN
Psychiatrists and mental health professionals regularly perform various clinical tasks (e.g., detection, differential diagnosis, prognostication, treatment selection and implementation). How well they perform each of these tasks has a direct impact on patient outcomes. Measurement-based care has brought greater precision to these tasks and has improved outcomes. This article provides an overview of the types of biomeasures and biomarkers, the clinical uses of biomarkers, and the challenges in their development and clinical use. Although still in their infancy, biomarkers hold the promise of bringing even greater precision and even better outcomes in mental health. Biomeasures that could become biomarkers include genetic, proteomic, metabolomic, and immunologic measures, as well as physiological, functional, and brain structural measures. Mechanistic markers reflect and are based on the specific pathobiological processes that are involved in the development of a clinically defined condition. Some clinically relevant biomarkers may rely on this mechanistic understanding while others may not. Clinical biomarkers serve three broadly defined goals. Diagnostic markers define what is wrong. Prognostic markers define what will happen in the natural course of the condition, although they may also predict the course of illness during treatment. Theranostic markers address issues pertinent to treatment by defining whether, when, whom, and how to treat. Other biomarkers may be used to monitor the overall effect of treatment regardless of the therapeutic effects or to monitor the specific therapeutic effects of the intervention on the disorder itself. Biomarkers can also be used to estimate susceptibility/risk of developing the condition or the biological consequences of having had the disorder.
RESUMEN
The 16-item Quick Inventory of Depressive Symptomatology (QIDS), a new measure of depressive symptom severity derived from the 30-item Inventory of Depressive Symptomatology (IDS), is available in both self-report (QIDS-SR(16)) and clinician-rated (QIDS-C(16)) formats. This report evaluates and compares the psychometric properties of the QIDS-SR(16) in relation to the IDS-SR(30) and the 24-item Hamilton Rating Scale for Depression (HAM-D(24)) in 596 adult outpatients treated for chronic nonpsychotic, major depressive disorder. Internal consistency was high for the QIDS-SR(16) (Cronbach's alpha =.86), the IDS-SR(30) (Cronbach's alpha =.92), and the HAM-D(24) (Cronbach's alpha =.88). QIDS-SR(16) total scores were highly correlated with IDS-SR(30) (.96) and HAM-D(24) (.86) total scores. Item-total correlations revealed that several similar items were highly correlated with both QIDS-SR(16) and IDS-SR(30) total scores. Roughly 1.3 times the QIDS-SR(16) total score is predictive of the HAM-D(17) (17-item version of the HAM-D) total score. The QIDS-SR(16) was as sensitive to symptom change as the IDS-SR(30) and HAM-D(24), indicating high concurrent validity for all three scales. The QIDS-SR(16) has highly acceptable psychometric properties, which supports the usefulness of this brief rating of depressive symptom severity in both clinical and research settings.