Antidepressant discontinuation syndrome: consensus panel recommendations for clinical management and additional research.
Bibliographic record
Abstract
OBJECTIVE: Currently, no evidence-based guidelines exist for the management of serotonin reuptake inhibitor (SRI) discontinuation syndrome. This article summarizes recommendations with respect to future research as well as clinical management recommendations for SRI discontinuation syndrome. PARTICIPANTS: In April 2004, a panel of physicians convened in New York City to discuss recommendations for clinical management of and additional research on SRI discontinuation syndrome. EVIDENCE: Previous guidance for management of SRI discontinuation syndrome was proposed in 1997 in a consensus meeting also chaired by Alan F. Schatzberg. A literature search of the PubMed database was conducted to identify articles on SRI discontinuation syndrome that have been published since 1997. CONSENSUS PROCESS: The 2004 panel reviewed important preclinical and clinical studies, discussed prospective investigation of this syndrome in clinical trials, and suggested the establishment of a research network to collect data in naturalistic settings. The panel also reviewed the management recommendations published in 1997 and subsequently updated the recommendations, taking into account the latest clinical data as well as the personal experience of its members with patients. CONCLUSIONS: Additional preclinical and clinical studies are necessary to further elucidate the underlying biological mechanisms of SRI discontinuation syndrome and to identify the patient populations and agents that are most affected by this phenomenon. Management strategies include gradual tapering of doses and should emphasize clinical monitoring and patient education.
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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 | 0.070 | 0.102 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.012 | 0.005 |
| Research integrity | 0.023 | 0.017 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".