Reply: Hemorrhages during Escitalopram—Venlafaxine— Mirtazapine Combination Treatment of Depression
Bibliographic record
Abstract
Dear Editor: The publication of Dr Benazzi's case report (1) is somewhat worrying. Although the report does not suggest that the treatment in this case is routine or normal practice, the concluding statement that clinicians should take care when combining several antidepressants that increase serotonin appears to condone the treatment outlined in the paper. Apart from the fact that all treatment algorithms for resistant depression recommend lithium augmentation prior to combined antidepressants, which in most cases come well down the list of strategies, given the limited evidence for this intervention, and putting aside the fact that, when recommended, the combination of antidepressants refers to 2 antidepressants, to add 2 antidepressants at once to an alreadyprescribed antidepressant is to court disaster. That nasal and rectal bleeding were the only consequences of this dangerous cocktail could be viewed as fortunate. What level of hemoglobin this patient bled down to is not revealed in the report, and it must be presumed that this was checked and was not of great concern. What is of concern is the risk that this report will encourage this sort of prescribing. References I. Benazzi F. Hemorrhages during escitalopram-venlafaxine-mirtazapine combination treatment of depression. Can J Psychiatry 2005;50:184. Andrew Al-Adwani, MRCPsych North Lincolnshire, UK Reply: Hemorrhages During Escitalopram-VenlafaxineMirtazapine Combination Treatment of Depression Dear Editor: I thank Dr Al-Adwani for his comments on the treatment of resistant depression, as the topic is a hot one. There are several guidelines on the treatment of depression, which should be distinguished as bipolar disorder I, bipolar disorder II, and major depressive (unipolar) disorder. Among these disorders, the treatment of bipolar II depression is the most understudied, even if bipolar II depression is at least as common as unipolar depression in nontertiary care outpatients (1,2). The several guidelines on the treatment of bipolar and unipolar depression follow different steps. What matters most is that these guidelines are the result of a consensus among academic experts, based on literature reviews and personal opinions, not on data from usual clinical practice. The result is that these guidelines are detached from real-world clinical practice (described as an irrelevant evidence base for clinical practice; 3). Even if we rely on the evidence we can find in the literature, this is of little help; at most it may guide the choice of a second antidepressant when the first one has failed. I have been in clinical practice for 21 years with the National Health Service as part-time consultant and with my private outpatient practice. In this latter setting (which is also the setting of most of my studies), I have thousands of visits yearly. Patients often come to see me after the failure of 1 or 2 antidepressants. …
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.025 | 0.028 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".