Meta-Analysis Demonstrates Statistically Significant Reduction in Postoperative Myocardial Infarction with the Use of Thoracic Epidural Analgesia
Notice bibliographique
Résumé
To the Editor: We read with interest the secondary analysis of the MASTER trial in which the authors found no significant improvement in major morbidity or mortality after major abdominal surgery from perioperative epidural analgesia (1). The authors comment that their results are at odds with the results of previous meta-analyses (2–4). We wish to clarify some questions raised by Peyton et al. regarding our meta-analysis (2). All patients, including those who died in the first 24 h after surgery, were included in our analysis. Funnel plotting suggested an absence of publication bias. Furthermore, we examined the effect of known comorbidities on the outcome. Thoracic epidural analgesia reduced postoperative myocardial infarction (MI) despite a higher proportion of patients with angina, previous MI, use of beta-blockers, or chronic obstructive pulmonary disease in the group receiving epidural analgesia. Four randomized controlled trials (RCTs) (5–8), which compared postoperative epidural analgesia with systemic opioid analgesia, were published after our meta-analysis. We have updated our meta-analysis on postoperative MI with the results from three of the RCTs (5–7) in which data were available (Fig. 1). Our meta-analysis continues to demonstrate statistically significant reduction in postoperative MI with the use of thoracic epidural analgesia (odds ratio 0.60; 95% confidence interval 0.37, 0.96; P = 0.03).Figure 1: The effect of postoperative epidural analgesia on postoperative myocardial infarction. CI = confidence interval, OR = odds ratio.The MASTER Trial was powered to detect an absolute risk reduction of 10% (or a relative risk reduction of 20%) with a control event rate of 50%, a type I error rate of 5%, and a power of only 80% for the combined outcome of mortality and major postoperative morbidity (8). Unfortunately, with the exception of the outcome “at least one morbid end point,” the rates of all postoperative complications were less than 50% in the control group (1). The MASTER Trial appears underpowered to detect clinically significant differences in important postoperative outcomes. For example, to detect a 20% relative risk reduction (or increase) in cardiovascular events with 5% type I error rate, 80% power, and the control event rate seen in the MASTER Trial (24%), a sample size of 2,388 subjects is needed. Peyton et al. have pointed out that large RCTs may reach different conclusions from meta-analyses of small RCTs addressing the same clinical question. In such instances, the estimate of treatment effect from the large RCT would be more accurate than the estimate from the meta-analysis. We agree with the authors’ concerns with the limitations of meta-analysis. However, with regards to specific postoperative complications such as pneumonia or MI, the definitive answer to the question of benefit (or harm) of perioperative epidural analgesia remains to be found. A much larger RCT is needed. W. Scott Beattie, MD, PhD Neal H. Badner, MD Peter T-L. Choi, MD, MSc(Epid)
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 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 | 0,017 | 0,091 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,010 | 0,011 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
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 ».