Design and Rationale for a Randomized, Controlled Trial of Interpersonal Psychotherapy and Citalopram for Depression in Coronary Artery Disease
Bibliographic record
Abstract
Objective: Recognition that depression is associated with increased morbidity and mortality in coronary artery disease (CAD) patients has augmented the need for evidence-based treatment guidelines. This article presents the design of a multisite, Canadian trial of the efficacy, safety, and tolerability of interpersonal psychotherapy (IPT), an empirically supported, depression-focused therapy, and the selective serotonin reuptake inhibitor citalopram, alone or in combination, in the treatment of major depression in CAD patients. Methods: Two hundred eighty stable CAD patients with a current major depressive episode of at least 4 weeks’ duration, based on the Structured Clinical Interview for Depression (SCID), and who have a baseline score 19 on a centralized, telephone-administered, 24-item Hamilton Depression Rating Scale (HAM-D) will be randomly assigned to receive 12 weekly IPT sessions or 12 weekly sessions of standardized clinical management (CM). Patients are also randomly assigned to receive 20 to 40 mg per day of citalopram or pill-placebo. This results in a 2-by-2 factorial design with four groups: IPT plus pill-placebo, IPT plus citalopram, CM plus pill-placebo, and CM plus citalopram. This permits the evaluation of both IPT and citalopram. Blinded, centralized, 24-item, HAM-D telephone ratings constitute the primary outcome variable. The self-report Beck Depression Inventory-II is the secondary outcome. Analyses will involve the intent-to-treat principle with last observation carried forward for incomplete assessments. Results: Not applicable. Conclusions: The results of this trial will contribute to the development of evidence-based clinical guidelines for managing depression in the context of CAD. Key words: psychotherapy, selective serotonin reuptake inhibitor, 2-by-2 factorial, telephone assessment, clinical trial, coronary artery disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.057 | 0.051 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.027 | 0.005 |
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".