The Effect of Venlafaxine on Electrocardiogram Intervals During Treatment for Depression in Older Adults
Bibliographic record
Abstract
PURPOSE/BACKGROUND: Venlafaxine is a commonly used antidepressant with both serotonergic and noradrenergic activity. There are concerns that it may prolong the corrected QT interval (QTc), and older adults may be at higher risk for this adverse effect, especially at higher dosages of the medication. METHODS/PROCEDURES: In this secondary analysis of a prospective clinical trial, we measured changes in QTc and other electrocardiogram (ECG) parameters in 169 adults 60 years or older with a major depressive disorder treated acutely with venlafaxine extended release up to 300 mg daily. We examined the relationship of venlafaxine dosage and ECG parameters, as well as the relationship between serum levels of venlafaxine and ECG parameters. FINDINGS/RESULTS: Venlafaxine exposure was not associated with an increase in QTc. Heart rate increased with venlafaxine treatment, whereas the PR interval shortened, and QRS width did not change significantly. The QTc change from baseline was not associated with venlafaxine dosages or serum concentrations. Age, sex, cardiovascular comorbidities, and depression remission status did not predict changes in QTc with venlafaxine. IMPLICATIONS/CONCLUSIONS: Venlafaxine treatment did not prolong QTc or other ECG parameters, even in high dosages in older depressed adults. These findings indicate that venlafaxine does not significantly affect cardiac conduction in most older patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".