The risk of hyponatremia induced by SSRIs and SNRIs antidepressants: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: To systematically evaluate the risk differences of hyponatremia induced by selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs), stratify risks among individual drugs, and provide evidence-based guidance for clinical medication safety. METHODS: A systematic search was conducted across the Cochrane Library, PubMed, and Web of Science databases. Study quality was assessed using the Newcastle-Ottawa Scale (NOS), and the certainty of evidence was evaluated using the GRADE framework. A meta-analysis was performed to compare the event rates and odds ratios (ORs) of hyponatremia between SSRIs and SNRIs, followed by subgroup analysis and bias assessment. RESULTS: A total of 38 observational studies (including 30 cohort studies and 8 case-control studies) were included in this study. The overall event rate of hyponatremia with antidepressants was 6.03% (P < 0.001), with rates of 5.98% for SSRIs and 6.13% for SNRIs. Both drug classes significantly increased the risk of hyponatremia (SSRIs: OR = 2.158; SNRIs: OR = 2.270, P < 0.001), with SNRIs demonstrating a higher risk in clinically relevant hyponatremia (OR = 2.227, P < 0.001). Risk stratification among individual drugs revealed that fluoxetine (SSRIs) and venlafaxine (SNRIs) had the highest risk, while sertraline and duloxetine were associated with lower risks. CONCLUSION: Both SSRIs and SNRIs significantly increase the risk of hyponatremia, with SNRIs posing a slightly higher risk. Clinicians should consider individual patient characteristics when selecting lower-risk medications and enhance serum sodium monitoring in high-risk populations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".