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Zusammenfassung Hintergrund Für die Behandlung von Menschen mit Schizophrenien wird vorrangig antipsychotische Monotherapie empfohlen. Antipsychotische Polypharmazie (APP) wird dennoch oft eingesetzt und dient als Qualitätsindikator. Ziel der Arbeit Das Auftreten von APP an 9 psychiatrischen Kliniken des LVR zu untersuchen und die Nutzbarkeit als Qualitätsindikator zu diskutieren. Material und Methoden Es wurden Behandlungsdaten von stationären und teilstationären Fällen mit der Hauptdiagnose ICD-10 F20.x im Zeitraum 6/2016 bis 6/2017 hinsichtlich der APP-Rate analysiert. Ergebnisse Bei 6788 Behandlungsfällen wurde eine APP-Rate von 55,5 % ermittelt. Männliches Geschlecht, längere Verweildauer, keine Zwangsunterbringung und der Standort der Klinik waren mit APP assoziiert. Diskussion Die APP-Rate ist im Vergleich bisherigen Ergebnissen hoch und weist erhebliche Unterschiede zwischen den Kliniken auf. Die Verwendung des Qualitätsindikators APP wird diskutiert.

Schizophrenia is associated with heterogeneous clinical symptoms and neuroanatomical alterations. In this work, we aim to disentangle the patterns of neuroanatomical alterations underlying a heterogeneous population of patients using a semi-supervised clustering method. We apply this strategy to a cohort of patients with schizophrenia of varying extends of disease duration, and we describe the neuroanatomical, demographic and clinical characteristics of the subtypes discovered. Methods We analyze the neuroanatomical heterogeneity of 157 patients diagnosed with Schizophrenia, relative to a control population of 169 subjects, using a machine learning method called CHIMERA. CHIMERA clusters the differences between patients and a demographically-matched population of healthy subjects, rather than clustering patients themselves, thereby specifically assessing disease-related neuroanatomical alterations. Voxel-Based Morphometry was conducted to visualize the neuroanatomical patterns associated with each group. The clinical presentation and the demographics of the groups were then investigated. Results Three subgroups were identified. The first two differed substantially, in that one involved predominantly temporal-thalamic-peri-Sylvian regions, whereas the other involved predominantly frontal regions and the thalamus. Both subtypes included primarily male patients. The third pattern was a mix of these two and presented milder neuroanatomic alterations and comprised a comparable number of men and women. VBM and statistical analyses suggest that these groups could correspond to different neuroanatomical dimensions of schizophrenia. Conclusion Our analysis suggests that schizophrenia presents distinct neuroanatomical variants. This variability points to the need for a dimensional neuroanatomical approach using data-driven, mathematically principled multivariate pattern analysis methods, and should be taken into account in clinical studies.

In this web-based field study, we compared the diagnostic accuracy and clinical utility of 10 selected mental disorders between the ICD-11 Clinical Descriptions and Diagnostic Guidelines (CDDG) and the ICD-10 CDDG using vignettes in a sample of 928 health professionals from all WHO regions. On average, the ICD-11 CDDG displayed significantly higher diagnostic accuracy (71.9% for ICD-11, 53.2% for ICD-10), higher ease of use, better goodness of fit, higher clarity, and lower time required for diagnosis compared to the ICD-10 CDDG. The advantages of the ICD-11 CDDG were largely limited to new diagnoses in ICD-11. After limiting analyses to diagnoses existing in ICD-11 and ICD-10, the ICD-11 CDDG were only superior in ease of use. The ICD-11 CDDG were not inferior in diagnostic accuracy or clinical utility compared to the ICD-10 CDDG for any of the vignettes. Diagnostic accuracy was consistent across WHO regions and independent of participants' clinical experience. There were no differences between medical doctors and psychologists in diagnostic accuracy, but members of other health professions had greater difficulties in determining correct diagnoses based on the ICD-11 CDDG. In sum, there were no differences in diagnostic accuracy for diagnoses existing in ICD-10 and ICD-11, but the introduction of new diagnoses in ICD-11 has improved the diagnostic classification of some clinical presentations. The favourable clinical utility ratings of the ICD-11 CDDG give reason to expect a positive evaluation by health professionals in the implementation phase of ICD-11. Yet, training in ICD-11 is needed to further enhance the diagnostic accuracy.

Combining antipsychotics is common in schizophrenia treatment, despite evidence-based guidelines generally not recommending such practice. Otherwise, evidence remains inconclusive, especially regarding specific combinations. The trial aimed to test whether a combination of amisulpride plus olanzapine is more effective than either intervention as a monotherapy.A multicentre, 16-week, randomised, double-blind, controlled trial was done at 16 psychiatric in-patient centres throughout Germany. Inclusion criteria were adults aged 18-65 years with non-first episode schizophrenia or schizoaffective disorder and with a Positive and Negative Syndrome Scale (PANSS) total score of at least 70 and at least two items of the positive symptoms subscale rated at least 4. Patients were randomly assigned to receive 16 weeks of treatment with either amisulpride plus olanzapine, amisulpride plus placebo, or olanzapine plus placebo (1:1:1), and block randomisation was stratified by study site. To keep patients and investigators masked throughout the duration of the trial, amisulpride, olanzapine, and placebo were administered as identical capsules. Flexibly dosed monotherapy of oral amisulpride (amisulpride plus placebo, 200-800 mg per day) or olanzapine (olanzapine plus placebo, 5-20 mg per day) was compared with a combination of amisulpride plus olanzapine. The primary outcome was symptom reduction measured by the PANSS total score after 8 weeks, in the modified intention-to-treat population (all patients randomly assigned to an intervention and receiving at least one study drug dose). As determined a priori, group differences were examined by t tests (Bonferroni-Holm-adjustment) followed by pre-planned Bayesian analyses as well as imputation methods based on mixed models to account for missing values and post-hoc ANCOVA adjusting for PANSS baseline scores. The study was registered on ClinicalTrials.gov, NCT01609153; the German Clinical Trials Register, DRKS00003603; and the European Union Drug Regulating Authorities Clinical Trials Database, EudraCT-No. 2011-002463-20.Between June 15, 2012, and Dec 15, 2018, 13 692 patients were assessed for eligibility. 13 364 patients were excluded (including for not meeting inclusion criteria, declining to participate, or inappropriate reasons for changing pharmacological treatment), and 328 were then randomly assigned to an intervention group. 112 patients were randomly assigned to receive amisulpride plus olanzapine, 109 were randomly assigned to receive amisulpride plus placebo, and 107 were randomly assigned to receive olanzapine plus placebo. 321 patients were analysed for the primary outcome in the modified intention-to-treat population after exclusion of screening failures and patients who did not receive the intervention (110 for amisulpride plus olanzapine, 109 for amisulpride plus placebo, and 102 for olanzapine plus placebo). Among the 321 patients who were randomly assigned to intervention groups and analysed for the primary outcome, 229 (71%) were male, 92 (29%) were female; the mean age was 40·2 years (SD 11·7); and 296 (92%) were White and 25 (8%) were classified as other ethnicity. PANSS total score improved significantly more at 8 weeks in the amisulpride plus olanzapine group (-29·6 [SD 14·5]) than in the olanzapine plus placebo group (-24·1 [13·4], p=0·049, Cohen's d=0·396). A significant difference was not observed in reduction of PANSS total score between the amisulpride and olanzapine group compared with the amisulpride and placebo group (-25·2 [SD 15·9], p=0·095, Cohen's d=0·29). After 8 weeks and 16 weeks, sexual dysfunction, weight, and waist circumference increase were significantly higher for patients receiving amisulpride plus olanzapine than for those receiving amisulpride plus placebo, with no differences in serious adverse events. Two patients died during study participation; one randomly assigned to the amisulpride plus olanzapine group, and one assigned to the olanzapine plus placebo group (both assessed with no relation to treatment).The advantages of amisulpride plus olanzapine have to be weighed against a higher propensity for side-effects. The use of this specific combination therapy could be an alternative to monotherapy in certain clinical situations, but side-effects should be considered.German Federal Ministry of Education and Research.

OBJECTIVE Hypothermia is a potentially lethal adverse reaction to typical and atypical antipsychotic drugs (APD). Among predisposing factors are advanced age and comorbid somatic diseases. The aim of this study was to assess the incidence of hypothermia and quantify risk factors. METHOD Charts of N = 3002 psychogeriatric inpatients were screened for incidence of hypothermia (body core temperature

Antipsychotics are the cornerstone in the treatment of schizophrenia and are primarily recommended as monotherapy by evidence-based guidelines. Nevertheless, antipsychotic polypharmacy (APP) is prevalent in routine practice and APP is also used as a quality indicator since 2016 in quality management programs.Based on routine data of nine psychiatric hospitals of the Landschaftsverband Rheinland (LVR)/Germany the prevalence of APP was determined and correlated with factors of routine healthcare in order to monitor the adoption of APP and to discuss its feasibility as a quality indicator.All cases with schizophrenia (ICD-10 F20.x; ≥ 18 years) discharged between June 1st, 2016, and June 1st, 2017, (in-patient and day clinic) were extracted from an established research database shared by all nine hospitals and analyzed regarding APP prevalence at the time of discharge.Based on 6,788 cases, the prevalence of APP was 55.5 % with an average of 2.4 antipsychotics (SD = 0.6) administered simultaneously. In multivariate analyses, significant predictors for APP were: gender (male female), the number of days in hospital (long short), involuntary treatment (no yes) and the location of the hospital.We found a high proportion of polypharmacy in inpatient schizophrenia patients and significant differences between hospitals. The use of the results as a quality indicator (criteria ≥ 2 antipsychotics) remains dependent on the background of the individual treatment courses, which cannot be adequately represented by the existing routine data. The LVR has been using the quality indicator of ≥ 3 antipsychotics since 2018, which is discussed as a more appropriate approach for future evaluations.Für die Behandlung von Menschen mit Schizophrenien wird vorrangig antipsychotische Monotherapie empfohlen. Antipsychotische Polypharmazie (APP) wird dennoch oft eingesetzt und dient als Qualitätsindikator.Das Auftreten von APP an 9 psychiatrischen Kliniken des LVR zu untersuchen und die Nutzbarkeit als Qualitätsindikator zu diskutieren.Es wurden Behandlungsdaten von stationären und teilstationären Fällen mit der Hauptdiagnose ICD-10 F20.x im Zeitraum 6/2016 bis 6/2017 hinsichtlich der APP-Rate analysiert.Bei 6788 Behandlungsfällen wurde eine APP-Rate von 55,5 % ermittelt. Männliches Geschlecht, längere Verweildauer, keine Zwangsunterbringung und der Standort der Klinik waren mit APP assoziiert.Die APP-Rate ist im Vergleich bisherigen Ergebnissen hoch und weist erhebliche Unterschiede zwischen den Kliniken auf. Die Verwendung des Qualitätsindikators APP wird diskutiert.

Given the particular relevance of arousal and alerting in panic disorder (PD), here the alerting network was investigated (1) contrasting patients with PD and healthy controls, (2) as a function of anxiety sensitivity constituting a dimensional measure of panic-related anxiety, and (3) as a possible correlate of treatment response. Using functional magnetic resonance imaging (fMRI), 45 out-patients with PD (f = 34) and 51 matched healthy controls were investigated for brain activation patterns and effective connectivity (Dynamic Causal Modeling, DCM) while performing the Attention Network Task (ANT). Anxiety sensitivity was ascertained by the Anxiety Sensitivity Index (ASI). Forty patients and 48 controls were re-scanned after a 6 weeks cognitive-behavioral treatment (CBT) or an equivalent waiting time, respectively. In the alerting condition, patients showed decreased activation in fronto-parietal pathways including the middle frontal gyrus and the superior parietal lobule (MFG, SPL). In addition, ASI scores were negatively correlated with connectivity emerging from the SPL, the SFB and the LC and going to the MFG in patients but not in healthy controls. CBT resulted in an increase in middle frontal and parietal activation along with increased connectivity going from the MFG to the SPL. This change in connectivity was positively correlated with reduction in ASI scores. There were no changes in controls. The present findings point to a pathological disintegration of the MFG in a fronto-parietal pathway in the alerting network in PD which was observed to be reversible by a successful CBT intervention.

We investigated the effects of clozapine and haloperidol, drugs that are widely used in the treatment of schizophrenia, on gene expression in six cortical and subcortical brain regions of adult rats. Drug treatments started at postnatal day 85 and continued over a 12-week period. Ten animals received haloperidol (1 mg/kg bodyweight) and ten received clozapine (20 mg/kg bodyweight) orally each day. Ten control rats received no drugs. The ten genes selected for this study did not belong to the dopaminergic or serotoninergic systems, which are typically targeted by the two substances, but coded for proteins of the cytoskeleton and proteins belonging to the synaptic transmitter release machinery. Quantitative real-time PCR was performed in the prelimbic cortex, cingulate gyrus (CG1) and caudate putamen and in the hippocampal cornu ammonis 1 (CA1), cornu ammonis 3 (CA3) and dentate gyrus. Results show distinct patterns of gene expression under the influence of the two drugs, but also distinct gene regulations dependent on the brain regions. Haloperidol-medicated animals showed statistically significant downregulation of SNAP-25 in CA3 (p = 0.0134) and upregulation of STX1A in CA1 (p = 0.0133) compared to controls. Clozapine-treated animals showed significant downregulation of SNAP-25 in CG1 (p = 0.0013). Our results clearly reveal that the drugs' effects are different between brain regions. These effects are possibly indirectly mediated through feedback mechanisms by proteins targeted by the drugs, but direct effects of haloperidol or clozapine on mechanisms of gene expression cannot be excluded.

This report presents the rationale and design of a multi-center clinical trial that examines the efficacy and safety of antipsychotic combination treatment in acutely ill schizophrenia patients compared to antipsychotic monotherapy. Antipsychotic combination treatment is common in clinical practice worldwide, despite clinical guidelines generally not recommending such practice due to lacking evidence for its efficacy and safety. Olanzapine has a related chemical structure and comparable receptor-binding profile as clozapine, which demonstrated superior efficacy in combination studies, but has a more unfavorable side-effect profile compared to olanzapine. Amisulpride and olanzapine have shown promising therapeutic efficacy in meta-analyses in monotherapy for people with schizophrenia. Combining amisulpride and olanzapine, complementary receptor-binding properties may enhance efficacy and possibly reduce (or at least not augment) side effects due to the different receptor profiles and metabolization pathways. Accordingly, we hypothesize that patients treated with amisulpride plus olanzapine show greater improvement on the Positive and Negative Syndrome Scale total score after 8 weeks versus either monotherapy. A randomized, double-blind controlled trial is performed at 16 German centers comparing flexibly dosed monotherapy of oral amisulpride (400-800 mg/day), and olanzapine (10-20 mg/day) and amisulpride-olanzapine co-treatment. Sample size was calculated to be n = 101 per treatment arm, assuming an effect size of 0.500 and a two-sided alpha = 0.025 and beta = 0.90. Recruitment for this trial started in June 2012. Until December 2018, 328 patients have been randomized. Trial conduct has been extended to reach the projected sample size. Publication of the study results is expected in 2019 informing an evidence-based recommendation regarding specific antipsychotic combination treatment.

The German Society for Psychiatry, Psychosomatics and Psychotherapy (DGPPN,) conducted a comprehensive field study (principal investigator WG) funded by the German Federal Ministry of Health in cooperation with 4 other German medical societies in the field of mental health (DGPM, DGPPR, DeGFS, DGfS) * to support WHO's development of the ICD-11 (Chapters 6 and 17). The objective of the web-based field study was to compare ICD-10 and ICD-11 (beta draft) for selected mental disorders, regarding consistency, accuracy and assessment of utility. The first study (TP1) focused on the diagnostic classification and the second (TP2) on assignment of diagnostic codes.In TP1, clinicians used either the ICD-10 Clinical Descriptions and Diagnostic Guidelines (CDDG) version or a draft version of the ICD-11 CDDG to evaluate 10 case vignettes in a randomized study implemented through the WHO GCPN **. As hypothesized, consistency was in favor of the ICD-11 (p = .02; n = 319 expert participants) though there was some variability across the different diagnostic categories. In addition, time for diagnosis was shorter (p = .01) and clinicians' judgment of utility (ease of use; goodness of fit) was better for ICD-11 (p = .047 and p.001 respectively).TP2 focused on consistency of diagnostic code assignment for 25 short case descriptions (including explicit diagnosis and additional clinical information) using both ICD-10 and ICD-11 in a randomized web-based field study which was run on the WHO ICD-FiT *** platform. Based on 531 code assignments by120 expert clinicians, consistency for ICD-11 was significantly lower compared to ICD-10 (71 % vs. 82 %, p.001) contrary to study hypothesis, and time required was significantly higher for ICD-11 (p.001). Nevertheless, utility assessments were in favor of ICD-11 (p.005).In summary, in TP1, given vignettes with more complex clinical descriptions more similar to clinical cases, ICD-11 showed advantages in the consistency of correct diagnoses among clinicians, time required to reach a diagnosis, and clinicians' ratings of clinical utility. These results provide evidence for quality improvement of the diagnostic process due to the revision of the more complete diagnostic guidelines for ICD-11. In the coding task of TP2, coding by clinicians using the ICD-10 was more consistent and faster than coding using the ICD-11. This may be a result of the greater complexity for coding use of the ICD-11 (e. g., due to 'post-coordination'), as well as greater familiarity with the ICD-10 system (which German clinicians currently use) and lack of practice with the new ICD-11 codes and tools. In spite of this, users assessed the ICD-11 system as more useful than the ICD-10, in part also because of ICD-11's more systematic and comprehensive coding tools. In addition, time needed for coding improved with practice, indicating need for intense education and training initiatives when ICD-11 is adopted and implemented into clinical practice.Die Deutsche Gesellschaft für Psychiatrie, Psychotherapie, Psychosomatik und Nervenheilkunde (DGPPN) hat federführend (Projektleitung WG) in Kooperation mit vier weiteren medizinischen Fachgesellschaften (DGPM, DGPPR, DeGPT, DGfS) * eine von elf der vom Bundesministerium für Gesundheit geförderten Validierungsstudien zur Unterstützung der WHO-Revision der ICD-10 zur ICD-11 durchgeführt. Die internetbasierte Feldstudie hatte zum Ziel, für ausgewählte Kategorien aus dem Bereich psychischer Erkrankungen (Betadraft, Kapitel 6 und 17) die Konsistenz (Reliabilität) der Diagnosestellung (Teilprojekt TP 1) sowie der Zuweisung diagnostischer Codes (TP 2) nach ICD-11 im Vergleich zur ICD-10 zu überprüfen sowie Anwendereinschätzungen zur Praktikabilität und Nutzerfreundlichkeit zu erheben.TP 1 untersuchte in randomisiertem Design die Konsistenz der Diagnosestellung anhand von zehn Fallvignetten mittels klinischer Diagnoseleitlinien über die WHO GCPN-Plattform ** mit Hilfe von 319 rekrutierten Mitgliedern der beteiligten Fachgesellschaften. Hypothesenkonform war die Konsistenz für ICD-11 signifikant höher als für ICD-10 (p = 0,02). Zusätzlich waren Zeitdauer der Diagnosestellung kürzer (p = 0,01) und Anwenderbeurteilungen positiver für ICD-11 hinsichtlich Nutzerfreundlichkeit (p = 0,047) und Passgenauigkeit (p0,001).Ebenfalls randomisiert wurde in TP 2 die Konsistenz der Kodierung für 25 explizite Diagnosen mit kurzen epikritischen Fallbeschreibungen für ICD-11 und ICD-10 mittels WHO FiT-Tool *** erfasst (n = 531 Kodierungen von 120 Teilnehmenden). Entgegen der Hypothese fand sich eine unterlegene Konsistenz korrekter Kodierung für ICD-11 vs. ICD-10 (71 % vs. 82 %; p0,001) sowie ein höherer Zeitbedarf für ICD-11 (p0,001). Hingegen war die Nutzerbewertung für ICD-11 erneut überlegen (p0,005).Zusammenfassend weist die ICD-11 in der diagnostischen Güte bessere, in der Kodierleistung schlechtere Konsistenzergebnisse auf als ICD-10. Die Ergebnisse belegen, dass die revidierten diagnostischen Leitlinien die Qualität des diagnostischen Prozesses günstig beeinflussen, was durch die zeitlichen Leistungsmaße und Nutzerbeurteilungen gestützt wird. Demgegenüber fallen die Kodierleistungen für die ICD-11 noch zurück, was sowohl auf die mögliche höhere Kodierkomplexität (z. B. Komplex-Codes mit sog. „post-coordination“) als auch auf den ungeübten Umgang mit dem neuen Kodiertool für ICD-11 zurückzuführen sein dürfte. Dennoch wird der neue Kodierprozess aufgrund erweiterter und systematischerer Kodieroptionen günstiger beurteilt als für ICD-10. In den Verläufen der zeitlichen Leistungsmaße zeichnen sich überdies Lernerfolge für ICD-11 ab, die darauf hinweisen, dass eingehende Schulungs- und Trainingsmaßnahmen im Rahmen der künftigen Praxisimplementierung von ICD-11 nicht nur erforderlich, sondern auch erfolgreich sein dürften. Die über Diagnosekategorien hinweg variablen Konsistenzergebnisse weisen allerdings auch darauf hin, dass es in der gegenwärtigen Entwurfsfassung der ICD-11 noch Verbesserungspotenziale für Diagnostik und Kodierung gibt, die in abschließenden und kontinuierlichen Revisionsmaßnahmen i. S. eines „living document“ zu berücksichtigen sind.

ZusammenfassungDie Deutsche Gesellschaft für Psychiatrie, Psychotherapie, Psychosomatik und Nervenheilkunde (DGPPN) hat federführend (Projektleitung WG) in Kooperation mit vier weiteren medizinischen Fachgesellschaften (DGPM, DGPPR, DeGPT, DGfS) * eine von elf der vom Bundesministerium für Gesundheit geförderten Validierungsstudien zur Unterstützung der WHO-Revision der ICD-10 zur ICD-11 durchgeführt. Die internetbasierte Feldstudie hatte zum Ziel, für ausgewählte Kategorien aus dem Bereich psychischer Erkrankungen (Betadraft, Kapitel 6 und 17) die Konsistenz (Reliabilität) der Diagnosestellung (Teilprojekt TP 1) sowie der Zuweisung diagnostischer Codes (TP 2) nach ICD-11 im Vergleich zur ICD-10 zu überprüfen sowie Anwendereinschätzungen zur Praktikabilität und Nutzerfreundlichkeit zu erheben.TP 1 untersuchte in randomisiertem Design die Konsistenz der Diagnosestellung anhand von zehn Fallvignetten mittels klinischer Diagnoseleitlinien über die WHO GCPN-Plattform ** mit Hilfe von 319 rekrutierten Mitgliedern der beteiligten Fachgesellschaften. Hypothesenkonform war die Konsistenz für ICD-11 signifikant höher als für ICD-10 (p = 0,02). Zusätzlich waren Zeitdauer der Diagnosestellung kürzer (p = 0,01) und Anwenderbeurteilungen positiver für ICD-11 hinsichtlich Nutzerfreundlichkeit (p = 0,047) und Passgenauigkeit (p < 0,001).Ebenfalls randomisiert wurde in TP 2 die Konsistenz der Kodierung für 25 explizite Diagnosen mit kurzen epikritischen Fallbeschreibungen für ICD-11 und ICD-10 mittels WHO FiT-Tool *** erfasst (n = 531 Kodierungen von 120 Teilnehmenden). Entgegen der Hypothese fand sich eine unterlegene Konsistenz korrekter Kodierung für ICD-11 vs. ICD-10 (71 % vs. 82 %; p < 0,001) sowie ein höherer Zeitbedarf für ICD-11 (p < 0,001). Hingegen war die Nutzerbewertung für ICD-11 erneut überlegen (p < 0,005).Zusammenfassend weist die ICD-11 in der diagnostischen Güte bessere, in der Kodierleistung schlechtere Konsistenzergebnisse auf als ICD-10. Die Ergebnisse belegen, dass die revidierten diagnostischen Leitlinien die Qualität des diagnostischen Prozesses günstig beeinflussen, was durch die zeitlichen Leistungsmaße und Nutzerbeurteilungen gestützt wird. Demgegenüber fallen die Kodierleistungen für die ICD-11 noch zurück, was sowohl auf die mögliche höhere Kodierkomplexität (z. B. Komplex-Codes mit sog. „post-coordination“) als auch auf den ungeübten Umgang mit dem neuen Kodiertool für ICD-11 zurückzuführen sein dürfte. Dennoch wird der neue Kodierprozess aufgrund erweiterter und systematischerer Kodieroptionen günstiger beurteilt als für ICD-10. In den Verläufen der zeitlichen Leistungsmaße zeichnen sich überdies Lernerfolge für ICD-11 ab, die darauf hinweisen, dass eingehende Schulungs- und Trainingsmaßnahmen im Rahmen der künftigen Praxisimplementierung von ICD-11 nicht nur erforderlich, sondern auch erfolgreich sein dürften. Die über Diagnosekategorien hinweg variablen Konsistenzergebnisse weisen allerdings auch darauf hin, dass es in der gegenwärtigen Entwurfsfassung der ICD-11 noch Verbesserungspotenziale für Diagnostik und Kodierung gibt, die in abschließenden und kontinuierlichen Revisionsmaßnahmen i. S. eines „living document“ zu berücksichtigen sind.

Introduction Everyday clinical routine is frequently challenged by difficulty to choose among differential diagnostic options, since many psychiatric disorders share similar phenotypes. E.g., borderline personality disorder (BPD) and schizophrenia (SZ) can both be associated with psychotic syndromes. Objectives Our objective was to evaluate the effectiveness of combining sMRI data and pattern classification methods to differentiate between BPD and SZ. Aims We aim to introduce objective diagnostic measures to improve the reliability of clinical evaluations. Methods sMRI data of 114 female patients were used to train a multivariate disease classifier. MR images were processed using voxel-based morphometry and high-dimensional registration to the MNI template. Grey matter volume maps were fed into a machine learning pipeline consisting of adjustment for possible age effects, PCA for dimensionality reduction and linear ν-support vector classification. Diagnostic performance of the classifier was determined by repeated nested 10-fold cross-validation. Results We were able to correctly classify unseen test subjects’ diagnosis with 74% accuracy. Classification sensitivity and specificity was 74%. Volume reductions in SZ vs. BPD were predominantly located in the left peri- and intrasylvian regions, orbitofrontal regions, the nucleus caudatus and the right cerebellum. Volume reductions in BPD compared to SZ were found predominantly in the left cerebellum, in limbic areas and the left inferior occipital gyrus. Conclusions Our results suggest that SZ can be differentiated from BPD at the single-subject level using sMRI and pattern classification methods. In future, this method might enhance clinical evaluations and improve accuracy and reliability of differential diagnosis.