A factor analytic comparison of three commonly used depression scales (HAMD, MADRS, BDI) in a large sample of depressed inpatients.

BACKGROUND: Quantifying depression mainly relies on the use of depression scales, and understanding their factor structure is crucial for evaluating their validity. METHODS: This post-hoc analysis utilized prospectively collected data from a naturalistic study of 1014 inpatients with major depression. Confirmatory and exploratory factor analyses were performed to test the psychometric abilities of the Hamilton Depression Rating Scale, the Montgomery Asberg Depression Rating Scale, and the self-rated Beck Depression Inventory. A combined factor analysis was also conducted including all items of all scales. RESULTS: All three scales showed good to very good internal consistency. The HAMD-17 had four factors: an "anxiety" factor, a "depression" factor, an "insomnia" factor, and a "somatic" factor. The MADRS also had four factors: a "sadness" factor, a neurovegetative factor, a "detachment" factor and a "negative thoughts" factor, while the BDI had three factors: a "negative attitude towards self" factor, a "performance impairment" factor, and a "somatic" factor. The combined factor analysis suggested that self-ratings might reflect a distinct illness dimension within major depression. CONCLUSIONS: The factors obtained in this study are comparable to those found in previous research. Self and clinician ratings are complementary and not redundant, highlighting the importance of using multiple measures to quantify depression.

Parkinson and depression: review and outlook.

Depression in Parkinson's Disorder (DPD) has been estimated to appear in up to 40% of people with PD and negatively impacts quality of life, motor and cognitive deficits and functional disability. Knowledge of the pathophysiology of DPD is unclear, DPD may be related to dysfunction in subcortical nuclei and the prefrontal cortex, striatal-thalamic-prefrontal and basotemporal limbic circuits, brainstem monoamine, and indolamine (i.e. dopamine, serotonin, and norepinephrine) systems. DPD is characterized by sadness, loss of interest, increased exhaustibility, feelings of helplessness, reduced drive, dysphoria, irritability, and pessimism about future. The diagnosis is complicated by overlap with PD symptoms, Detection of depression in PD should be made by psychometric depression scales. DPD is underrecognized and undertreated in clinical practice. Treatment mainly includes antidepressive medications and behavioral interventions as psychotherapy. Dopamine agonists showed some antidepressant effects, there are no sufficient numbers of RCTs. Important randomized clinical trials (RCTs) are summarized. SSRIs and SNRIs have a satisfying efficacy in DPD. TCAs are also good for improving depression. Side effects of different antidepressants (e.g. TCAs, SSRIs, SNRIs, bupropion, MAOIs) and potential interactions should be considered. In existing guidelines so far no statements, algorithms and recommendations are given for diagnosis and treatment of DPD. Methodologically adequate designed RCTs and comparative studies (NIS) which offer evidence-based results are urgently needed having the impact of DPD in mind.

Chronic vs non-chronic depression in psychiatric inpatient care - Data from a large naturalistic multicenter trial.

BACKGROUND: Around 20% - 30% of depressed individuals experience a chronic form of depression lasting two or more years. This naturalistic study investigates the characteristics and the course of chronic depressed patients (CD) during standard antidepressant treatment in comparison to not chronically depressed (NCD) patients. METHODS: Data of 954 patients were drawn from the prospective naturalistic, multicenter study of the German research network on depression, CD was met as classifier by 113 patients (11.8%), whereas 841 patients (88.2%) had non-chronic courses (NCD). RESULTS: CD was significantly associated with a low age at onset, use of benzodiazepines, psychotherapy at baseline, substance abuse, a depressive personality disorder and a low degree of extraversion. CD patients showed a longer hospital stay, lower remission rates, increased rates of suicidal ideation as well as higher depression scores at discharge. In addition, individuals with chronic depression continued to obtain higher neuroticism scores and lower extraversion scores at discharge. LIMITATION: Results were assessed by a post-hoc analysis, based on prospectively collected data. CONCLUSION: CD patients have an inferior outcome in clinical measures as well as personality dimensions (i.e. low extraversion) compared to non-CD patients. These findings support the notion that CD patients entering a setting of standard psychiatric inpatient care will show less benefit compared to non-CD patients, and that this difference as such may be used as a stratifying marker for providing specialized psychiatric treatment with optimized pharmacological and psychotherapeutic protocols.

Driving Performance Under Treatment of Most Frequently Prescribed Drugs for Mental Disorders: A Systematic Review of Patient Studies.

BACKGROUND: Mobility is important for daily life functioning, with particular challenges regarding road safety under pharmacological treatment in patients with a psychiatric disease. METHODS: According to PRISMA guidelines, a systematic literature search on PubMed database (January 1970 to December 2020) was performed. Primary endpoints were driving performance in on-road tests, driving simulator performance, or psychomotor and visual perception functions assessed to estimate fitness to drive according to legal regulations in patient studies. RESULTS: Forty studies were identified (1533 patients, 38% female, median age 45 years), of which more than 60% were cross-sectional and open-label trials. Under steady-state medication, 31% (range 27%-42.5%) of schizophrenic or schizoaffective patients under antipsychotics and 18% (range 16%-20%) of unipolar and bipolar patients under antidepressants showed severe impairment in skills relevant for driving. Data point to an advantage of second-generation antipsychotics compared with first-generation antipsychotics as well as modern antidepressants over tricyclic antidepressants with respect to driving. Most patients significantly improved or stabilized in driving skills within 2-4 weeks of treatment with non-sedative or sedative antidepressants. Diazepam significantly worsened driving the first 3 weeks after treatment initiation, whereas medazepam (low dose), temazepam, and zolpidem did not impair driving. In long-term users of sedating antidepressants or benzodiazepines, impairments in on-road tests were not evident. CONCLUSION: The available evidence suggests that psychopharmacologic medicines improve or at least stabilize driving performance of patients under long-term treatment when given on clinical considerations. To enhance treatment compliance, existing classification systems of medicinal drugs concerning impact on driving performance should also incorporate information about effects of long-term-treatment.

Combining machine learning algorithms for prediction of antidepressant treatment response.

OBJECTIVES: Predictors for unfavorable treatment outcome in major depressive disorder (MDD) applicable for treatment selection are still lacking. The database of a longitudinal multicenter study on 1079 acutely depressed patients, performed by the German research network on depression (GRND), allows supervised and unsupervised learning to further elucidate the interplay of clinical and psycho-sociodemographic variables and their predictive impact on treatment outcome phenotypes. EXPERIMENTAL PROCEDURES: Treatment response was defined by a change of HAM-D 17-item baseline score ≥50% and remission by the established threshold of ≤7, respectively, after up to eight weeks of inpatient treatment. After hierarchical symptom clustering and stratification by treatment subtypes (serotonin reuptake inhibitors, tricyclic antidepressants, antipsychotic, and lithium augmentation), prediction models for different outcome phenotypes were computed with random forest in a cross-center validation design. In total, 88 predictors were implemented. RESULTS: Clustering revealed four distinct HAM-D subscores related to emotional, anxious, sleep, and appetite symptoms, respectively. After feature selection, classification models reached moderate to high accuracies up to 0.85. Highest accuracies were observed for the SSRI and TCA subgroups and for sleep and appetite symptoms, while anxious symptoms showed poor predictability. CONCLUSION: Our results support a decisive role for machine learning in the management of antidepressant treatment. Treatment- and symptom-specific algorithms may increase accuracies by reducing heterogeneity. Especially, predictors related to duration of illness, baseline depression severity, anxiety and somatic symptoms, and personality traits moderate treatment success. However, prospectives application of machine learning models will be necessary to prove their value for the clinic.

What happens with schizophrenia patients after their discharge from hospital? Results on outcome and treatment from a "real-world" 2-year follow-up trial.

Aim of the study was to examine the course of schizophrenia patients within 2 years after discharge. Within a multicenter study of the German Competence Network on Schizophrenia, patients suffering from a schizophrenia spectrum disorder were examined regarding their psychopathological improvement, tolerability, and the treatment regime applied during hospitalization and a 2-year follow-up period. Response, remission, the level of everyday functioning, and relapse were furthermore evaluated during the follow-up period using established definitions for these outcome domains. The psychopharmacological treatment was specifically evaluated in terms of a potential association with relapse. 149 patients were available for analysis, with 65% of the patients being in response, 52% in symptomatic remission, and 64% having a satisfiable everyday functioning 2 years after their discharge from hospital. Despite these favorable outcome rates, 63% of the patients suffered from a relapse within the 2-year follow-up period with 86% of these patients being rehospitalized. Discharge non-responder and non-remitter were twice as likely to relapse during follow-up. A significant decrease of side-effects was observed with negligible rates of extrapyramidal side-effects, sedation, and weight gain during follow-up. Patients receiving treatment with atypical antipsychotics were found to have the lowest risk to relapse (p < 0.0001). The results highlight the natural and unsteady course of schizophrenia in most patients underlining the need to develop more specific treatment strategies ensuring ongoing stability and preventing relapse.

Remission in schizophrenia - What are we measuring? Comparing the consensus remission criteria to a CGI-based definition of remission and to remission in major depression.

BACKGROUND: Despite being recommended for use in clinical trials, the consensus remission criteria were found to leave patients with persisting symptoms, relevant areas of functional impairment and a decreased sense of wellbeing. Therefore, to evaluate the appropriateness of the schizophrenia consensus criteria, a definition of remission based on the Clinical Global Impression Scale (CGI) was developed and remitter subgroups were compared. METHODS: 239 patients with a schizophrenia spectrum disorder were evaluated regarding their remission status after inpatient treatment. Remission in schizophrenia was defined according to the symptom-severity component of the consensus criteria by Andreasen et al. and a CGI based definition was calculated using sensitivity and specificity using receiver operating curves (asymptomatic remitter). Both remitter groups (schizophrenia consensus versus asymptomatic remitters) were compared regarding different clinical variables at discharge as well as the likelihood to relapse within a 1-year follow-up period. Both schizophrenia remitter subgroups were compared to remitters in major depression as a reference value. RESULTS: Following the consensus criteria, 63% of the schizophrenia patients were in remission compared to only 18% following the asymptomatic criterion. The schizophrenia consensus remitters were less likely to be concurrent treatment responders (p < 0.0001), had a significantly greater illness severity (p < 0.0001) and less functioning (p = 0.0358) as well as a significantly greater risk to relapse (p = 0.0174) compared to the schizophrenia asymptomatic remitters as well as the depressed remitters. CONCLUSION: It should be critically re-evaluated if the currently proposed consensus criteria are adequate to measure what is traditionally understood to be remission.

The Dopamine Receptor Antagonism of Opipramol: Relevance to Parkinsonism?

Drug-induced Parkinsonism (DIP) represents the second most-frequent etiology of Parkinson syndromes after neurodegenerative disorders. It has been described mainly for antipsychotics, Ca-channel blockers, antiemetics, and gastrointestinal prokinetics. In this article, we present a clinical case series of 10 patients, retrieved within our movement disorders hospital, with DIP under intake of opipramol. Symptoms completely resolved after drug withdrawal, and associated risk factors were old age, high doses, and presence of cortical atrophy. This frequently prescribed anxiolytic drug has so far not been associated with DIP. Our objective is to raise awareness of DIP as an adverse effect of opipramol.

Comparing Schizophrenia Patients With a Predicted High/Low Risk of Nonresponse Receiving Treatment with Ziprasidone and Haloperidol: A Randomized-Controlled Study.

INTRODUCTION: The aim of this double-blind randomized study was to evaluate the response to antipsychotic treatment in schizophrenia patients with predicted high/low risk of nonresponse identified by applying a set of well-established scales and predictors of outcome and to compare efficacy between ziprasidone and haloperidol. METHODS: One hundred twelve schizophrenia patients (ziprasidone: n=54; haloperidol: n=58) were rated weekly on the Positive and Negative Syndrome Scale for Schizophrenia (PANSS), the Global Assessment of Functioning Scale (GAF), the Social and Occupational Functioning Scale (SOFAS), the Simpson-Angus Scale (SAS), and Hillside Akathisia Scale (HAS). RESULTS: Ninety-two patients (82%) were predicted to have a high risk of nonresponse. No significant difference regarding PANSS improvement in this subsample was found comparing ziprasidone and haloperidol (p=0.563). Also, for the total patient sample, no significant difference was found regarding the course of the PANSS total score, GAF (p=0.921), and SOFAS (p=0.658) between ziprasidone and haloperidol. Haloperidol resulted in higher scores on the SAS (p=0.001) and HAS (p=0.011). DISCUSSION: An alarmingly high number of patients were at high risk of nonresponse to antipsychotic treatment.

[Therapeutic drug monitoring in neuropsychopharmacology : Summary of the consensus guidelines 2017 of the TDM task force of the AGNP]. / Therapeutisches Drug-Monitoring in der Neuropsychopharmakologie : Zusammenfassung der Konsensusleitlinien 2017 der TDM-Arbeitsgruppe der AGNP.

Therapeutic drug monitoring (TDM) is the quantification and interpretation of drug concentrations in blood serum or plasma to optimize pharmacological therapy. TDM is an instrument with which the high interindividual variability of pharmacokinetics of patients can be identified and therefore enables a personalized pharmacotherapy. In September 2017 the TDM task force of the Working Group for Neuropsychopharmacology and Pharmacopsychiatry (AGNP) published an update of the consensus guidelines on TDM published in 2011. This article summarizes the essential statements for the clinical practice in psychiatry and neurology.

Subtypes of depression and their overlap in a naturalistic inpatient sample of major depressive disorder.

Subtyping depression is important in order to further delineate biological causes of depressive syndromes. The aim of this study was to evaluate clinical and outcome characteristics of distinct subtypes of depression and to assess proportion and features of patients fulfilling criteria for more than one subtype. Melancholic, atypical and anxious subtypes of depression were assessed in a naturalistic sample of 833 inpatients using DSM-IV specifiers based on operationalized criteria. Baseline characteristics and outcome criteria at discharge were compared between distinct subtypes and their overlap. A substantial proportion of patients (16%) were classified with more than one subtype of depression, 28% were of the distinct anxious, 7% of the distinct atypical and 5% of the distinct melancholic subtype. Distinct melancholic patients had shortest duration of episode, highest baseline depression severity, but were more often early improvers; distinct anxious patients had higher NEO-Five Factor Inventory (NEO-FFI) neuroticism scores compared with patients with unspecific subtype. Melancholic patients with overlap of anxious features had worse treatment outcome compared to distinct melancholic and distinct anxious subtype. Distinct subtypes differed in only few variables and patients with overlap of depression subtypes may have independent clinical and outcome characteristics. Studies investigating biological causes of subtypes of depression should take influence of features of other subtypes into account.

TDM in psychiatry and neurology: A comprehensive summary of the consensus guidelines for therapeutic drug monitoring in neuropsychopharmacology, update 2017; a tool for clinicians.

OBJECTIVES: Therapeutic drug monitoring (TDM) combines the quantification of drug concentrations in blood, pharmacological interpretation and treatment guidance. TDM introduces a precision medicine tool in times of increasing awareness of the need for personalized treatment. In neurology and psychiatry, TDM can guide pharmacotherapy for patient subgroups such as children, adolescents, pregnant women, elderly patients, patients with intellectual disabilities, patients with substance use disorders, individuals with pharmacokinetic peculiarities and forensic patients. Clear indications for TDM include lack of clinical response in the therapeutic dose range, assessment of drug adherence, tolerability issues and drug-drug interactions. METHODS: Based upon existing literature, recommended therapeutic reference ranges, laboratory alert levels, and levels of recommendation to use TDM for dosage optimization without specific indications, conversion factors, factors for calculation of dose-related drug concentrations and metabolite-to-parent ratios were calculated. RESULTS: This summary of the updated consensus guidelines by the TDM task force of the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie offers the practical and theoretical knowledge for the integration of TDM as part of pharmacotherapy with neuropsychiatric agents into clinical routine. CONCLUSIONS: The present guidelines for TDM application for neuropsychiatric agents aim to assist clinicians in enhancing safety and efficacy of treatment.

A standardized stepwise drug treatment algorithm for depression reduces direct treatment costs in depressed inpatients - Results from the German Algorithm Project (GAP3).

BACKGROUND: In a previous single center study we found that a standardized drug treatment algorithm (ALGO) was more cost effective than treatment as usual (TAU) for inpatients with major depression. This report aimed to determine whether this promising initial finding could be replicated in a multicenter study. METHODS: Treatment costs were calculated for two time periods: the study period (from enrolment to exit from study) and time in hospital (from enrolment to hospital discharge) based on daily hospital charges. Cost per remitted patient during the study period was considered as primary outcome. RESULTS: 266 patients received ALGO and 84 received TAU. For the study period, ALGO costs were significantly lower than TAU (ALGO: 7 848 ± 6 065 €; TAU: 10 033 ± 7 696 €; p = 0.04). For time in hospital, costs were not different (ALGO: 14 734 ± 8 329 €; TAU: 14 244 ± 8 419 €; p = 0.617). Remission rates did not differ for the study period (ALGO: 57.9%, TAU: 50.0%; p=0.201). Remission rates were greater in ALGO (83.3%) than TAU (66.2%) for time in hospital (p = 0.002). Cost per remission was lower in ALGO (13 554 ± 10 476 €) than TAU (20 066 ± 15 391 €) for the study period (p < 0.001) and for time in hospital (ALGO: 17 582 ± 9 939 €; TAU: 21 516 ± 12 718 €; p = 0.036). LIMITATIONS: Indirect costs were not assessed. Different dropout rates in TAU and ALGO complicated interpretation. CONCLUSIONS: Treatment algorithms enhance the cost effectiveness of the care of depressed inpatients, which replicates our prior results in an independent sample.

Driving Under the Influence of Antidepressants: A Systematic Review and Update of the Evidence of Experimental and Controlled Clinical Studies.

Introduction This review provides an update of experimental and clinical studies on the effects of antidepressants on driving performance. Methods A systematic literature search on the PubMed database (1980-2016) was performed. Results Twenty-eight studies could be included in this review, whereas only 5 studies investigated driving performance under antidepressants in patients. Most tri- and tetracyclics have acute deleterious effects on driving performance that, except for mianserin, attenuate after subchronic use. Selective serotonin reuptake inhibitors and the serotonin norepinephrine reuptake inhibitor's venlafaxine and milnacipran did not affect driving ability. Trazodone appears to have dose-related acute effects on driving skills. Acute use of mirtazapine does produce impairments that diminish when given as a nocturnal dose and cannot be seen in healthy subjects when initially given as a low dose or after repeated dosing. Additive effects with alcohol were most pronounced with sedating antidepressants. Most patients definitely benefit from treatment with newer antidepressants with respect to driving skills. Discussion Much more patient studies are needed to elucidate a crucial question: from which antidepressant treatment do patients benefit most with respect to driving performance?

How Effective Is Algorithm-Guided Treatment for Depressed Inpatients? Results from the Randomized Controlled Multicenter German Algorithm Project 3 Trial.

Background: Treatment algorithms are considered as key to improve outcomes by enhancing the quality of care. This is the first randomized controlled study to evaluate the clinical effect of algorithm-guided treatment in inpatients with major depressive disorder. Methods: Inpatients, aged 18 to 70 years with major depressive disorder from 10 German psychiatric departments were randomized to 5 different treatment arms (from 2000 to 2005), 3 of which were standardized stepwise drug treatment algorithms (ALGO). The fourth arm proposed medications and provided less specific recommendations based on a computerized documentation and expert system (CDES), the fifth arm received treatment as usual (TAU). ALGO included 3 different second-step strategies: lithium augmentation (ALGO LA), antidepressant dose-escalation (ALGO DE), and switch to a different antidepressant (ALGO SW). Time to remission (21-item Hamilton Depression Rating Scale ≤9) was the primary outcome. Results: Time to remission was significantly shorter for ALGO DE (n=91) compared with both TAU (n=84) (HR=1.67; P=.014) and CDES (n=79) (HR=1.59; P=.031) and ALGO SW (n=89) compared with both TAU (HR=1.64; P=.018) and CDES (HR=1.56; P=.038). For both ALGO LA (n=86) and ALGO DE, fewer antidepressant medications were needed to achieve remission than for CDES or TAU (P<.001). Remission rates at discharge differed across groups; ALGO DE had the highest (89.2%) and TAU the lowest rates (66.2%). Conclusions: A highly structured algorithm-guided treatment is associated with shorter times and fewer medication changes to achieve remission with depressed inpatients than treatment as usual or computerized medication choice guidance.

Add-on Antidepressants in the Naturalistic Treatment of Schizophrenia Spectrum Disorder - When, Who, and How?

The aim of this study was to evaluate antidepressant add-on treatment within the acute treatment of schizophrenia spectrum disorder patients. Antidepressant add-on was evaluated in 365 patients within a naturalistic multicenter study. Patients with/without antidepressant add-on were compared regarding clinical and treatment-related variables, response and remission, and remission of depressive and negative symptoms. The efficacy of antidepressant add-on treatment was furthermore analyzed applying marginal structure models. Twenty-three percent of the patients received antidepressant add-on for a mean duration of 50.28 (33.42) days. Patients with the diagnosis of a schizoaffective disorder, multiple illness episodes, and a longer duration of their illness as well as those with significantly fewer baseline positive symptoms, more negative and depressive symptoms, more side effects, and less subjective well-being were augmented with antidepressants. At discharge no significant effect of antidepressant add-on treatment was observed in terms of a 25% improvement (p=0.2623), a 50% improvement (p=0.3946), remission (p=0.0552), or remission of depressive (p=0.6336) and negative symptoms (p=0.8756). Also, when analyzing marginal structure models considering the diagnostic subgroups, no significant effect was found. Add-on with antidepressants is common. A final recommendation in terms of this strategy's efficacy cannot be given.

Pooled Analysis of Four Non-Interventional Studies: Effectiveness and Tolerability of the Antidepressant Agomelatine in Daily Practice.

INTRODUCTION: Meta-analyses are useful to increase knowledge and strengthen evidence about antidepressant treatment supplementary to individual studies. METHODS: A pooled analysis of four multicenter, open-label, prospective, non-interventional studies (2009-2013) was performed to provide further evidence about the antidepressant effectiveness and tolerability of agomelatine (25-50 mg/day) in a large number of non-selected German outpatients with major depressive disorder. The main analysis was performed after 12 weeks (n = 9601) and in subpopulations after 24 and 52 weeks by descriptive statistical methods. RESULTS: Overall, 60.1% of patients were pretreated with antidepressants. Concomitant psychiatric diseases (71.9%), co-medication with antidepressants (18.9%) and/or psychotropic medication (31.9%) were observed. Depressive symptoms improved according to the Clinical Global Impression (CGI) in 81% after 12 weeks, a response was observed in 78.7% (CGI-I ≤2), and remission in 34.5% of patients (CGI-S = 1 or 2). In subpopulations, response was documented in 79.3% (W24) and 75.9% (W52) and remission in 38.1% (W24) and 47.5% (W52), respectively. Over 12 weeks, adverse drug reactions (ADRs) were reported for 511 patients (5.32%), most frequently headache (0.92%) and nausea (0.75%), and serious adverse drug reactions (sADR) for 18 patients (0.19%). Between W12-W24 and W24-W52, ADRs were reported for 0.49%/0.99% and sADRs for 0.05%/0%, respectively. Overall, 49 patients (0.5%) showed clinically relevant transaminase elevations (AST/ALT >3 times upper normal value), with 19 patients (0.2%) showing preexisting elevations at the study start. One patient (0.03%) developed hepatitis with reversible symptoms after treatment discontinuation. ADR predominantly occurred within the first weeks of treatment. Mean weight and body mass index (BMI) remained unchanged over 24 weeks. CONCLUSION: In this pooled data analysis, 9601 depressed patients of clinical practice were evaluated over 12 weeks and subpopulations were also analyzed over 24 and 52 weeks. Agomelatine effectively reduced depressive symptoms (CGI-response and remission) with good general tolerability.