Switch to Mania upon Discontinuation of Antidepressants in Patients with Mood Disorders: A Review of the Literature
Bibliographic record
Abstract
OBJECTIVE: To review the literature for reported cases of mania related to discontinuing antidepressant treatment, as well as for possible explanations of this phenomenon, and to present a case report. METHOD: We undertook a literature review through the PubMed index, using the key words mania, antidepressant withdrawal, and antidepressants in bipolar disorder. We reviewed 11 articles featuring 23 cases. Where available, we noted and tabulated certain parameters for both bipolar disorder (BD) and unipolar depression. We use a case example to illustrate the phenomenon of mania induced by antidepressant withdrawal. RESULTS: For patients with unipolar depression, we found 17 reported cases of mania induced by antidepressant withdrawal. Antidepressants implicated included tricyclic antidepressants (TCAs) (12/17), monoamine oxidase inhibitors (MAOIs) (2/17), trazodone (1/17), mirtazapine (1/17), and paroxetine (1/17). For patients with BD, we found 19 reported cases of mania induced by antidepressant withdrawal, including our own case example. Of these, selective serotonin reuptake inhibitors (SSRIs) (10/19), TCAs (4/19), MAOIs (2/19), and serotonin norepinephrine reuptake inhibitors (SNRIs) (2/19) were implicated. CONCLUSION: Our case report supports the observation of antidepressant withdrawal-induced mania in patients with BD. It is distinguishable from antidepressant-induced mania, physiological drug withdrawal, and mania as a natural course of the illness. Many theories have been put forward to explain this occurrence. Noradrenergic hyperactivity and "withdrawal-induced cholinergic overdrive and the cholinergic-monoaminergic system" are the 2 most investigated and supported models. The former is limited by poor clinical correlation and the latter by its applicability only to anticholinergic drugs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".