Korean Medication Algorithm Project for Generalized Anxiety Disorder 2009 (I) : Initial Treatment Strategy
Bibliographic record
Abstract
Department of Psychiatry, School of Medicine, CHA University, Seoul, KoreaObjectivesZZThis study investigated the consensus about treatment strategies for the initial treat-ment of generalized anxiety disorder (GAD). This issue represents one of the subjects addressed by the Korean Medication Algorithm Project for GAD in Korea.MethodsZZThe executive committee of the Korean Medication Algorithm Project for GAD, support-ed by The Korean Association of Anxiety Disorders, developed questionnaires about treatment st-rategies for patients with GAD, based on guidelines or algorithms and clinical trial studies previ-ously published in foreign countries, especially by the International Psychopharmacology Algori-thm Project, the National Institute for Clinical Excellence, and the Canadian Psychiatric Associat-ion. Fifty-five (64%) of 86 experts on a committee reviewing GAD in Korea responded to the quest-ionnaires. We classified the consensus of expert opinions into three categories (first-line, second-line, and third-line treatment strategies) and identified the treatment of choice according using a Chi-square test and a 95% confidence interval.ResultsZZFor the initial treatment of GAD, antidepressant monotherapy and the combination of antidepressants and benzodiazepines as anxiolytics were recommended as the first line strate-gies. Escitalopram, paroxetine CR and venlafaxine XR were selected as first-line antidepressant tr-eatments, and alprazolam, clonazepam and lorazepam were the preferred benzodiazepines. The mean starting doses and mean maximum doses of the drugs were 7.55±3.09 mg and 24.91±8.14 mg for escitalopram, 12.57±2.83 mg and 44.76±15.00 mg for paroxetine CR, and 46.81±16.74 mg and 223.32±60.64 mg for venlafaxine XR.ConclusionZZThese results, which reflect recent studies and clinical experiences, may provide guidelines for the initial.;J Korean Neuropsychiatr Assoc 2010 49:546-552KEY WORDSZZGeneralized anxiety disorder · Pharmacotherapy · Algorithm · Initial treatment strategy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".