id,collection,dc.contributor.author[],dc.date.accessioned[],dc.date.available[],dc.date.issued[],dc.description.abstract[en],dc.format.extent[],dc.identifier.uri,dc.identifier.uri[],dc.language[],dc.rights.uri[],dc.subject.ddc,dc.subject[],dc.title.subtitle[],dc.title[],dc.type[],dcterms.accessRights.openaire,dcterms.bibliographicCitation.doi[],dcterms.bibliographicCitation.url[],dcterms.bibliographicCitation[],refubium.affiliation[de],refubium.mycore.derivateId[],refubium.mycore.fudocsId[],refubium.resourceType.isindependentpub[] "0e5f2ad1-74e0-44a4-8a48-80a91a4cf705","fub188/15","Adli, Mazda||Wiethoff, Katja||Baghai, Thomas C.||Fisher, Robert||Seemüller, Florian||Laakmann, Gregor||Brieger, Peter||Cordes, Joachim||Malevani, Jaroslav||Laux, Gerd||Hauth, Iris||Möller, Hans-Jürgen||Kronmüller, Klaus-Thomas [u.a.]","2018-06-08T11:08:04Z","2017-11-02T10:26:57.044Z","2017","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.","10 S.","http://dx.doi.org/10.17169/refubium-24967","https://refubium.fu-berlin.de/handle/fub188/21679","eng","http://creativecommons.org/licenses/by-nc/4.0/","600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit","treatment algorithms||antidepressants||treatment-resistant depression||medical decision making||German Algorithm Project","Results from the Randomized Controlled Multicenter German Algorithm Project 3 Trial","How Effective Is Algorithm-Guided Treatment for Depressed Inpatients?","Wissenschaftlicher Artikel","open access","10.1093/ijnp/pyx043","http://doi.org/10.1093/ijnp/pyx043","International Journal of Neuropsychopharmacology. - 20 (2017), 9, 721–730","Charité - Universitätsmedizin Berlin","FUDOCS_derivate_000000009069","FUDOCS_document_000000028425","no"