Coronary Heart Disease and Depression: The Next Steps
Notice bibliographique
Résumé
Abbreviations used in this article CHD coronary heart disease ENRICHD Enhancing Recovery in Coronary Heart Disease Patients CBT cognitive-behavioural therapy MI myocardial infarction SSRI selective serotonin reuptake inhibitor Since the exciting findings in the late 1980s and early 1990s that depression predicts prognosis in patients recovering from heart attacks, there has been little substantive advance in the treatment of mood disorders in patients with CHD. Although confirmatory epidemiologic studies have continued to appear (see the summary in the accompanying article by Frasure-Smith and Lesperance, 1), there has been little clinically relevant research. Because most clinical trials of antidepressants have excluded patients with medical comorbidity and because such patients, including those with CHD, often take multiple other medications that can interact with some antidepressants, the existing evidence base for depression treatment does not directly translate to CHD patients. The landmark ENRICHD Trial (2), funded by the United States National Heart, Lung and Blood Institute between 1996 and 2002, was designed as the first step in improving clinical treatment for post-Mi patients suffering from depression. At the same time, the ENRICHD Trial tested the hypothesis that treating depression with CBT, plus an SSRI antidepressant when needed, can improve cardiac prognosis. As summarized in the accompanying article (1), the results were disappointing. The usual care control group received a good deal of cointervention with antidepressants, and although overall differences in changes in depression were statistically significant, they were small. There was no evidence of a difference in cardiac events over the average follow-up period of 29 months. Since the publication of the results in 2003, researchers and clinicians have been wondering what the next step should be. Is it really possible to change depression symptoms in cardiac patients sufficiently to affect either the pathophysiology of cardiac disease or patient compliance with medical treatment and thus save lives? Imagine, for a moment, that the results of ENRICHD had been positive. What if, in addition to reducing depression symptoms, CBT plus sertraline as needed had resulted in better survival than usual care? Most of us working in behavioural cardiology would be a good deal happier and would probably have been much more productive over the last 3 years. However, what would we have known? We would have had a better idea of how to treat CHD patients suffering from depression, but we would not have known whether reducing depression symptoms per se results in decreased cardiac events. We also would not have known which component of the intervention was crucial for the reduction in cardiac events. This is because, like many other medical treatments, depression treatment-whether by CBT or SSRIs-has pleiotropic effects on body systems other than the brain, including the cardiovascular system. This means that the net effect on cardiac outcomes of any treatment for depression is likely to be at least as much a function of the sum of its impact on the cardiovascular mechanisms linking depression with prognosis as a function of its impact on depressive symptoms per se. As summarized in the accompanying review by Skala, Freedland, and Carney (3), in addition to the behavioural mechanism of adherence to medical advice and risk factor modification, there are reasonable data supporting that 5 biological mechanisms are involved in the link between depression and CHD: exaggerated platelet activation (4-7); reduced heart rate variability, reflecting increased sympathetic activity and (or) reduced vagal activity (8); increased innate inflammatory response (9,10); endothelial dysfunction (11,12); and reduced levels of omega-3 free fatty acids(13,14). Itis plausible that antidepressants have some effects on several of these mechanisms. …
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,005 | 0,010 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,012 | 0,021 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,023 | 0,006 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».