Who Develops Severe or Fatal Adverse Drug Reactions to Selective Serotonin Reuptake Inhibitors?
Bibliographic record
Abstract
OBJECTIVE: To ascertain the risk factors associated with the development of severe and fatal adverse drug reactions (ADRs) or intentional overdoses by patients on selective serotonin reuptake inhibitors (SSRIs). METHODS: We undertook a data analysis of Health Canada's database of Adverse Drug Reactions to SSRIs from 1986 to 1996, as well as a literature review. RESULTS: Among the complete ADR reports in the SSRI database, there were no sex differences in occurrences of all ADRs (n = 1011), severe ADRs (n = 295), drug-drug interactions (n = 312), deaths (n = 87), or intentional overdoses (n = 79), when sex differences in prescription practices were considered. There were no differences in ADR rates among different SSRIs. The most common cause of death among patients taking SSRIs was intentional overdose (n = 65, 74.7%). This was reported in 47 (72.3%) women and 18 (27.7%) men. The most common drugs taken with SSRIs in patients who died of intentional overdoses were benzodiazepines, tricyclic antidepressants (TCAs), narcotics, alcohol, and diphenhydramine. Patients who had severe or fatal ADRs were more likely to be taking an SSRI with 2 or more other drugs, including alcohol. Drug combinations that included another CYP-450 drug were especially problematic. A total of 129 cardiovascular ADRs were reported, most of which were severe. These included rhythm disturbances, blood pressure perturbations, and chest pain or angina. Cardiovascular ADRs most often occurred with concomitant drug use of benzodiazepines, TCAs, histamine H2 antagonists, lithium, and calcium channel blockers. There were 3 deaths from malignant neuroleptic syndrome unassociated with intentional overdose. CONCLUSIONS: SSRIs are relatively safe when their widespread use is compared with the prevalence of ADRs. SSRIs may, however, be associated with ADRs, and even death, following intentional overdose or when taken with 2 or more other drugs or alcohol (particularly another drug metabolized by CYP-450). Physicians prescribing SSRIs need to consider drug-drug interactions and carefully monitor patients with severe affective disorders, comorbid medical conditions (especially cardiovascular disease), alcohol abuse, or a history of overdosing.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".