Clinical Guideline (CANMAT 2016) Discordance of Medications for Patients with Major Depressive Disorder in China
Bibliographic record
Abstract
Yuncheng Zhu,1– 3,* Zhiguo Wu,4,* Dongmei Zhao,5 Xiaohui Wu,2 Ruoqiao He,6 Zuowei Wang,1,3 Daihui Peng,2 Yiru Fang2,7– 9 1Division of Mood Disorders, Shanghai Hongkou Mental Health Center, Shanghai, People’s Republic of China; 2Clinical Research Center & Division of Mood Disorders, Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai, People’s Republic of China; 3Clinical Research Center for Mental Health, School of Medicine, Shanghai University, Shanghai, People’s Republic of China; 4Clinical Research Center in Mental Health, Shanghai Yangpu District Mental Health Center, Shanghai University of Medicine & Health Sciences, Shanghai, People’s Republic of China; 5Division of Psychiatry, Shanghai Changning Mental Health Center, Shanghai, People’s Republic of China; 6New York University, New York, NY, USA; 7Department of Psychiatry & Affective Disorders Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 8CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, People’s Republic of China; 9Shanghai Key Laboratory of Psychotic Disorders, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yiru Fang, Email yirufang@aliyun.comObjective: This survey aims to explore the current medical treatment of major depressive disorder (MDD) in China and match its degree with Canadian Network for Mood and Anxiety Treatments (CANMAT).Methods: A total of 3275 patients were recruited from 16 mental health centers and 16 general hospitals in China. Descriptive statistics presented the total number and percentage of drugs, as well as all kinds of treatments.Results: Selective serotonin reuptake inhibitors (SSRIs) accounted for the largest proportion (57.2%), followed by serotonin-noradrenaline reuptake inhibitors (SNRIs) (22.8%) and mirtazapine (7.0%) in the first therapy, while that of SNRIs (53.9%) followed by SSRIs (39.2%) and mirtazapine (9.8%) in the follow-up therapy. An average of 1.85 medications was administered to each MDD patient.Conclusion: SSRIs were the first choice in the first therapy, while the proportion of those drugs decreased during the follow-up therapy and were replaced by SNRIs. Plenty of combined pharmacotherapies were directly selected as the first trial of patients, which was inconsistent with guideline recommendations.Keywords: major depressive disorder, Chinese, guideline, antidepressants
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".