An Open-Label Study of Nefazodone Treatment of Major Depression in Patients with Congestive Heart Failure
Bibliographic record
Abstract
OBJECTIVES: To evaluate the feasibility of screening and recruiting patients with major depression and congestive heart failure (CHF) in a tertiary care cardiology hospital and to obtain preliminary efficacy, tolerability, and safety data for nefazodone treatment of a major depressive episode in CHF patients. METHOD: We conducted a 12-week, open-label trial of nefazodone given in dosages up to 600 mg daily. We assessed patients at baseline, 1, 2, 4, 8, and 12 weeks. Measures used were the 17-item Hamilton Depression Rating Scale (HDRS), the Clinical Global Impression Scale, the Beck Depression Inventory, Spielberger's State-Trait Anxiety Inventory, and the Minnesota Living with Heart Failure Questionnaire. We also obtained pre- and poststudy ECGs, 24-hour Holter monitor recordings, and plasma levels of norepinephrine. RESULTS: After screening 443 CHF patients, 28 patients with major depression met study eligibility criteria. The 23 patients who completed 4 or more weeks of medication showed significant improvement on all depression scales and in quality of life. Of 19 subjects who completed the full 12-week trial, 74% experienced a decline of 50% or more on HDRS scores. The completers also showed a significant reduction in heart rate, an increase in QT intervals (but not in the QTc), and a marginally significant decrease in plasma norepinephrine. There were no changes in heart rate variability. CONCLUSIONS: It is feasible to screen and recruit CHF patients with major depression for an anti-depressant trial. Nefazodone seems sufficiently safe, tolerable, and efficacious to justify a larger, placebo-controlled trial.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".