Impact of cardiac arrest centers on the survival of patients with nontraumatic out‐of‐hospital cardiac arrest : a systematic review and meta‐analysis

Background The role of cardiac arrest centers (CACs) in out‐of‐hospital cardiac arrest care systems is continuously evolving. Interpretation of existing literature is limited by heterogeneity in CAC characteristics and types of patients transported to CACs. This study assesses the impact of CACs on survival in out‐of‐hospital cardiac arrest according to varying definitions of CAC and prespecified subgroups. Methods and Results Electronic databases were searched from inception to March 9, 2021 for relevant studies. Centers were considered CACs if self‐declared by study authors and capable of relevant interventions. Main outcomes were survival and neurologically favorable survival at hospital discharge or 30 days. Meta‐analyses were performed for adjusted odds ratio (aOR) and crude odds ratios. Thirty‐six studies were analyzed. Survival with favorable neurological outcome significantly improved with treatment at CACs (aOR, 1.85 [95% CI, 1.52–2.26]), even when including high‐volume centers (aOR, 1.50 [95% CI, 1.18–1.91]) or including improved‐care centers (aOR, 2.13 [95% CI, 1.75–2.59]) as CACs. Survival significantly increased with treatment at CACs (aOR, 1.92 [95% CI, 1.59–2.32]), even when including high‐volume centers (aOR, 1.74 [95% CI, 1.38–2.18]) or when including improved‐care centers (aOR, 1.97 [95% CI, 1.71–2.26]) as CACs. The treatment effect was more pronounced among patients with shockable rhythm ( P =0.006) and without prehospital return of spontaneous circulation ( P =0.005). Conclusions were robust to sensitivity analyses, with no publication bias detected. Conclusions Care at CACs was associated with improved survival and neurological outcomes for patients with nontraumatic out‐of‐hospital cardiac arrest regardless of varying CAC definitions. Patients with shockable rhythms and those without prehospital return of spontaneous circulation benefited more from CACs. Evidence for bypassing hospitals or interhospital transfer remains inconclusive

Predicting atrial fibrillation after ischemic stroke: clinical, genetics and electrocardiogram modelling

Introduction: Detection of atrial fibrillation (AF) is challenging in patients after ischemic stroke due to its paroxysmal nature. We aim to determine the utility of a combined clinical, electrocardiographic and genetic variables model to predict AF in a post-stroke population. Materials and Methods: We performed a cohort study at a single comprehensive stroke centre from 09/11/2009 to 31/10/2017. All patients recruited were diagnosed with acute ischemic stroke or transient ischemic attacks. Electrocardiographic variables including p-wave terminal force (PWTF), corrected QT interval (QTc) and genetic variables including single nucleotide polymorphisms (SNP) at the 4q25 (rs2200733) were evaluated. Clinical, electrocardiographic and genetic variables of patients without AF and those who developed AF were compared. Multiple logistic regression analysis and receiver operating characteristics were performed to identify parameters and determine their ability to predict the occurrence of AF. Results: Out of 709 patients (median age of 59 years, IQR 52-67) recruited, sixty (8.5%) were found to develop AF on follow-up. Age (odds ratio (OR): 3.49, 95% confidence interval (CI): 2.03-5.98, p<0.0001), hypertension (OR: 2.76, 95% CI: 1.36-5.63, p=0.0052) and valvular heart disease (OR: 8.49, 95% CI: 2.62-27.6, p<0.004 were the strongest predictors of AF, with area under receiver operating value of 0.76 (95% CI: 0.70-0.82), and 0.82 (95% CI: 0.77-0.87) when electrocardiographic variables (PWTF and QTc) were added. SNP did not improve prediction modelling. Conclusion: We demonstrated that a model combining clinical and electrocardiographic variables provided robust prediction of AF in our post-stroke population. Role of SNP in prediction of AF was limited

Corrigendum to ‘Neurology of COVID-19 in Singapore (vol 418, 117118, 2020)

10.1016/j.jns.2021.117406JOURNAL OF THE NEUROLOGICAL SCIENCES42