Subgrouping time-dependent prescribing patterns of first-onset major depressive episodes by psychotropics dissection
作者机构:Department of Psychiatry&Center of Sleep DisordersNational Taiwan University HospitalTaipei 100Taiwan Center of Statistical Consultation and ResearchNational Taiwan University HospitalTaipei 100Taiwan Department of PsychiatryWan-Fang Hospital&School of MedicineCollege of MedicineTaipei Medical UniversityTaipei 100Taiwan Department of PsychiatryTaipei City HospitalSongde BranchTaipei 100Taiwan Department of Clinical PharmacySchool of PharmacyCollege of PharmacyTaipei Medical UniversityTaipei 110Taiwan Department of PsychiatryCheng-Hsin General HospitalTaipei 100Taiwan Graduate Institute of Epidemiology and Preventive MedicineCollege of Public HealthNational Taiwan UniversityTaipei 100Taiwan
出 版 物:《World Journal of Psychiatry》 (世界精神病学杂志)
年 卷 期:2021年第11卷第11期
页 面:1116-1128页
核心收录:
学科分类:1002[医学-临床医学] 100205[医学-精神病与精神卫生学] 10[医学]
基 金:Supported by the Ministry of Science and Technology,Taiwan,No.MOST 107-2314-B-002-219,No.MOST 108-2314-B-002-110-MY2 the National Taiwan University Hospital,No.UN110-021
主 题:First episode Depression Classification Psychopharmacology Depression treatment
摘 要:BACKGROUND Subgrouping patients with major depressive disorder is a promising solution for the issue of ***,the link between available subtypes and distinct pathological mechanisms is weak and yields disappointing results in clinical *** To develop a novel approach for classification of patients with time-dependent prescription patterns at first onset in real-world *** Drug-naive patients experiencing their first major depressive episode(n=105)participated in this *** agents prescribed in the first 24 mo following disease onset were recorded monthly and categorized as antidepressants,augmentation agents,and *** cumulative doses of agents in each category were converted into relevant *** parameters were used to summarize the time-dependent prescription patterns for each psychotropic load:Stability,amount,frequency,and the time trend of monthly prescriptions.A K-means cluster analysis was used to derive subgroups of participants based on these input parameters of psychotropic agents across 24 *** validity of the resulting data-driven clusters was compared using relevant severity *** Four distinct clusters were derived from K-means analysis,which matches experts’consent:Short-term antidepressants use,long-term antidepressants use,long-term antidepressants and sedatives use,andlong-term antidepressants,sedatives,and augmentation use.At the first 2 years of disease course,the four clusters differed on the number of antidepressants used at adequate dosage and duration,frequency of outpatient service use,and number of psychiatric *** the first 2 years following disease onset,depression severity was differed in the four *** Our findings suggested a new approach to optimize the subgrouping of patients with major depressive disorder,which may assist future etiological and treatment response studies.