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Suicide is a devastating public health problem and very few biological treatments have been found to be effective for quickly reducing the intensity of suicidal ideation (SI). We have previously shown that a single dose of ketamine, a glutamate N-methyl-d-aspartate (NMDA) receptor antagonist, is associated with a rapid reduction in depressive symptom severity and SI in patients with treatment-resistant depression.
We conducted a randomized, controlled trial of ketamine in patients with mood and anxiety spectrum disorders who presented with clinically significant SI (n = 24). Patients received a single infusion of ketamine or midazolam (as an active placebo) in addition to standard of care. SI measured using the Beck Scale for Suicidal Ideation (BSI) 24 h post-treatment represented the primary outcome. Secondary outcomes included the Montgomery–Asberg Depression Rating Scale – Suicidal Ideation (MADRS-SI) score at 24 h and additional measures beyond the 24-h time-point.
The intervention was well tolerated and no dropouts occurred during the primary 7-day assessment period. BSI score was not different between the treatment groups at 24 h (p = 0.32); however, a significant difference emerged at 48 h (p = 0.047). MADRS-SI score was lower in the ketamine group compared to midazolam group at 24 h (p = 0.05). The treatment effect was no longer significant at the end of the 7-day assessment period.
The current findings provide initial support for the safety and tolerability of ketamine as an intervention for SI in patients who are at elevated risk for suicidal behavior. Larger, well-powered studies are warranted.
Individuals with major depressive disorder (MDD) are characterized by maladaptive responses to both positive and negative outcomes, which have been linked to localized abnormal activations in cortical and striatal brain regions. However, the exact neural circuitry implicated in such abnormalities remains largely unexplored.
In this study 26 unmedicated adults with MDD and 29 matched healthy controls (HCs) completed a monetary incentive delay task during functional magnetic resonance imaging (fMRI). Psychophysiological interaction (PPI) analyses probed group differences in connectivity separately in response to positive and negative outcomes (i.e. monetary gains and penalties).
Relative to HCs, MDD subjects displayed decreased connectivity between the caudate and dorsal anterior cingulate cortex (dACC) in response to monetary gains, yet increased connectivity between the caudate and a different, more rostral, dACC subregion in response to monetary penalties. Moreover, exploratory analyses of 14 MDD patients who completed a 12-week, double-blind, placebo-controlled clinical trial after the baseline fMRI scans indicated that a more normative pattern of cortico-striatal connectivity pre-treatment was associated with greater improvement in symptoms 12 weeks later.
These results identify the caudate as a region with dissociable incentive-dependent dACC connectivity abnormalities in MDD, and provide initial evidence that cortico-striatal circuitry may play a role in MDD treatment response. Given the role of cortico-striatal circuitry in encoding action–outcome contingencies, such dysregulated connectivity may relate to the prominent disruptions in goal-directed behavior that characterize MDD.
Electronic medical records (EMR) provide a unique opportunity for efficient, large-scale clinical investigation in psychiatry. However, such studies will require development of tools to define treatment outcome.
Natural language processing (NLP) was applied to classify notes from 127 504 patients with a billing diagnosis of major depressive disorder, drawn from out-patient psychiatry practices affiliated with multiple, large New England hospitals. Classifications were compared with results using billing data (ICD-9 codes) alone and to a clinical gold standard based on chart review by a panel of senior clinicians. These cross-sectional classifications were then used to define longitudinal treatment outcomes, which were compared with a clinician-rated gold standard.
Models incorporating NLP were superior to those relying on billing data alone for classifying current mood state (area under receiver operating characteristic curve of 0.85–0.88 v. 0.54–0.55). When these cross-sectional visits were integrated to define longitudinal outcomes and incorporate treatment data, 15% of the cohort remitted with a single antidepressant treatment, while 13% were identified as failing to remit despite at least two antidepressant trials. Non-remitting patients were more likely to be non-Caucasian (p<0.001).
The application of bioinformatics tools such as NLP should enable accurate and efficient determination of longitudinal outcomes, enabling existing EMR data to be applied to clinical research, including biomarker investigations. Continued development will be required to better address moderators of outcome such as adherence and co-morbidity.
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