Notice bibliographique
Résumé
To the Editor: In 2023, while searching the literature on the incidence of heart attacks caused by electroconvulsive therapy, I found “Major Adverse Cardiac Events and Mortality Associated with Electroconvulsive Therapy: A Systematic Review and Meta-analysis,”1 published in Anesthesiology. The authors suggest that their review offers “a more robust estimate about the incidence of major adverse cardiac events and mortality after electroconvulsive therapy” than had previously been available. It will probably, therefore, be the estimate that psychiatrists use in future when informing patients who are considering having electroconvulsive therapy, and their families. So, we have a shared responsibility to get this right. The abstract states, “Major adverse cardiac events and death after electroconvulsive therapy are infrequent and occur in about 1 of 50 patients.” The belief that 1 in 50 people experiencing major adverse cardiac events as a result of a medical procedure is “infrequent” seems, to say the least, unusual. It is even stranger that the 1 in 50 figure does not accurately describe the probability of a major adverse cardiac event reported in the review itself. The rates of the two most commonly reported events were 24.0 per 1,000 patients (acute heart failure) and 25.83 per 1,000 (life-threatening arrhythmia). These rates equal 1 in 41.7 and 1 in 38.7 patients, respectively. These figures might reasonably be summarized as "about 1 in 40". They are clearly not "about 1 in 50." This distortion is repeated in the Discussion: “The results of this systematic review and meta-analysis show that an estimated 25.83 (14.83 to 45.00) per 1,000 patients (approximately 1 in 50 patients) develop major adverse cardiac events after electroconvulsive therapy (2%)” (p. 86). Again, the numbers are inappropriately described as “low frequency” (p. 87). The review ends by repeating both the misrepresentation and the minimization: “In conclusion, this systematic review and meta-analysis shows that major adverse cardiac events after electroconvulsive therapy are infrequent and occur in about 1 in 50 patients” (p. 90). Furthermore, the authors mistakenly based their estimation of the probability of one or more of the six events occurring on the probability of only the most frequent event. The rather obvious “additive law of probability”2 means that to estimate the actual probability of at least one of the six events, one must sum the probabilities of each of the events (myocardial infarction, life-threatening arrhythmia, acute pulmonary edema, pulmonary embolism, acute heart failure, and cardiac arrest). Adding the six probabilities together results in 65.47 events per 1,000 people,3 which is 1 event per 15.3 people. In 2008, the United Nations declared, “It is of vital importance that ECT [electroconvulsive therapy] be administered only with the free and informed consent of the person concerned, including on the basis of information on the secondary effects and related risks such as heart complications, confusion, loss of memory and even death.”4 In “Major Adverse Cardiac Events and Mortality Associated with Electroconvulsive Therapy: Correcting and Updating a 2019 Meta-analysis,”3 I document some other flaws in the Duma et al. review1 and note how that article is consistent with a general tendency in electroconvulsive therapy literature for the harms caused by electroconvulsive therapy to be minimized and its effectiveness exaggerated.5,6 After adjusting for the errors in the 2019 review, and including five studies published since 2019, I estimate that the probability of having one of the six cardiac events covered by Duma et al.1 is actually between 1 in 15 and 1 in 30 electroconvulsive therapy patients.3 This, I suggest, is what patients and families should be told, along with the fact that cardiac events are the leading cause of electroconvulsive therapy–related mortality.5 If we want to responsibly apply the important ethical principle of informed consent,6 terms like “infrequent” and “about 1 in 50” should be avoided. Competing Interests The author has been a paid expert witness in legal cases concerning electroconvulsive therapy in Canada, New Zealand, and the United States.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».