Pharmacological preventions and treatments for pericardial complications after open heart surgeries

BACKGROUND: Pericardial complications following cardiac surgery are common and debilitating, significantly impacting patients' survival. We performed this network meta-analysis to identify the most effective and safest preventions and treatments for pericardial complications following cardiac surgery. METHODS: We systematically searched PubMed/MEDLINE, EMBASE and Cochrane CENTRAL from inception to 22 January 2024. Pairs of reviewers screened eligible studies. They included randomised controlled trials that enrolled adults undergoing major cardiac surgeries and reported postpericardiotomy syndrome, pericardial effusion and pericarditis as primary or secondary outcomes. We summarised the effects of interventions using relative risks and corresponding 95% CIs. We performed a frequentist random-effects network meta-analysis using the restricted maximum likelihood estimator. RESULTS: We included 39 trials that enrolled a total of 6419 participants. Our network meta-analysis demonstrates colchicine reduces the risk of postpericardiotomy syndrome (RR 0.53, 95% CI 0.38 to 0.73). Beta-blockers probably prevent atrial fibrillation with a large magnitude of effect (RR 0.4, 95% CI 0.20 to 0.81) and may prevent postoperative pericarditis (RR 0.66, 95% CI 0.45 to 0.97) compared with control. Fish oil (RR 0.28, 95% CI 0.09 to 0.90), non-steroidal anti-inflammatory drugs (RR 0.37, 95% CI 0.23 to 0.59) and colchicine (RR 0.37, 95% CI 0.23 to 0.59) may reduce the risk of postoperative atrial fibrillation. We found no evidence of a difference in the risk of pleural effusion, all-cause mortality, serious adverse events or postoperative ICU stay. CONCLUSIONS: The results of our study highly recommend colchicine use to reduce the risk of the postpericardiotomy syndrome and beta-blocker use to reduce postoperative atrial fibrillation. Additionally, our study suggests that further research is needed to investigate other interventions and to evaluate newly proposed interventions in large, high-quality trials, as the current evidence for some interventions is relatively weak.