Serotonin-Norepinephrine Reuptake Inhibitors and the Risk of AKI
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: A safety signal regarding cases of AKI after exposure to serotonin-norepinephrine reuptake inhibitors (SNRIs) was identified by Health Canada. Therefore, this study assessed whether the use of SNRIs increases the risk of AKI compared with selective serotonin reuptake inhibitors (SSRIs) and examined the risk associated with each individual SNRI. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Multiple retrospective population-based cohort studies were conducted within eight administrative databases from Canada, the United States, and the United Kingdom between January 1997 and March 2010. Within each cohort, a nested case-control analysis was performed to estimate incidence rate ratios (RRs) of AKI associated with SNRIs compared with SSRIs using conditional logistic regression, with adjustment for high-dimensional propensity scores. The overall effect across sites was estimated using meta-analytic methods. RESULTS: There were 38,974 cases of AKI matched to 384,034 controls. Current use of SNRIs was not associated with a higher risk of AKI compared with SSRIs (fixed-effect RR, 0.97; 95% confidence interval [95% CI], 0.94 to 1.01). Current use of venlafaxine and desvenlafaxine considered together was not associated with a higher risk of AKI (RR, 0.96; 95% CI, 0.92 to 1.00). For current use of duloxetine, there was significant heterogeneity among site-specific estimates such that a random-effects meta-analysis was performed showing a 16% higher risk, although this risk was not statistically significant (RR, 1.16; 95% CI, 0.96 to 1.40). This result is compatible with residual confounding, because there was a substantial imbalance in the prevalence of diabetes between users of duloxetine and users of others SNRIs or SSRIs. After further adjustment by including diabetes as a covariate in the model along with propensity scores, the fixed-effect RR was 1.02 (95% CI, 0.95 to 1.10). CONCLUSIONS: There is no evidence that use of SNRIs is associated with a higher risk of hospitalization for AKI compared with SSRIs.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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".