Prescribing Tricyclic Antidepressants in the Elderly
Bibliographic record
Abstract
Introduction Although not recommended as a first-line treatment for old patients with depressive, anxiety or somatic symptom disorders, we continue seeing tricyclic antidepressants being frequently prescribed. Objectives To estimate the prevalence and to assess the implementation of safety measures related to the prescription of such molecules in the elderly. To explain their choice as a first-line treatment. Methods We included all new patients aged 65 years or over between 1st January 2011 and 31st December 2015 whom, were prescribed an antidepressant. Recommendations of the Canadian coalition for seniors’ mental health, of the world federation of societies of biological psychiatry and of the national institute for health and care excellence were our evaluation tools. We compared tricyclic receivers to those having newer antidepressants to try to understand the choice of tricyclics as a first-line treatment. Results Eighty patients were included. Mean age was of 75 years. 46% were prescribed a tricyclic as a first line treatment. Depressive disorders were the most diagnosed ones (79%) followed by anxiety disorders (14%) and somatic symptom disorders (7%). An electrocardiogram was not performed to all patients prior to the initiation of the tricyclic nor at anytime later. 11% continued being prescribed tricyclics in spite of contraindications. Only a low economic level was significantly related to their choice as a first-line treatment (P = 0.001). Conclusions Tricyclics’ prescribing rate was high. Safety measures were not applied for all patients. Regular availability of newer antidepressants in public health structures and a better awareness of antidepressants prescribing guidelines in the elderly are mandatory. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".