Mortality and Long-Term Outcome of Neonates with Congenital Heart Disease and Acute Perinatal Stroke: A Population-Based Case-Control Study

Abstract

Objective: Neonates with congenital heart disease (CHD) and perinatal stroke have high mortality and survivors are at risk for poor long-term neurodevelopmental outcome. The aim of this study was to assess the risk factors and outcome of neonates with both CHD and MRI-confirmed perinatal stroke (Study Group) and compare those to the risk factors and outcome of infants matched for CHD without stroke (Control-1) and of infants matched for MRI-confirmed stroke without CHD (Control-2). Methods: We conducted a population-based case-control study enrolling 28 term neonates with CHD and MRI-confirmed acute perinatal stroke born between 2007-2017 in the Central-Hungarian Region. Each of the control groups included 56 infants. The Bayley Scales of Infant Development-II, the Brunet-Lézine test and the Binet Intelligence scales-V were used for neurodevelopmental follow-up at a median age of 61 months. Results: Mortality was highest in the Study Group (25% compared to 5% and 2%, respectively, p = 0.001). Adverse neurodevelopmental outcome was prevalent in the Study (53%) and Control-2 Groups (52%, p = 0.03). Significantly different parameters among the three groups included Apgar scores, mode of delivery, gestational age at birth, cardiac interventions and twin pregnancy. In a multivariable regression analysis adjusted for clinically relevant parameters, patients in the Study Group had significantly higher odds for mortality compared to patients in the Control-1 Group (OR: 6.5 95% CI: 1.1-39.4). Conclusions: Neonates with perinatal stroke and CHD are at a higher risk for dying compared to neonates with CHD without stroke. In addition, the stroke-associated direct insult to the brain likely plays an important role in the development of neurodevelopmental morbidity in these patients.

Deep Learning-Enabled Brain Stroke Classification on Computed Tomography營mages

“…Typically, CT is the primary step in detecting stroke, as it allows checking the volume, type, and severity of the lesion. In addition, CT is considered to be the fastest and most cost-effective technology for diagnosing stroke [4]. As a result, given the need for rapid diagnosis, the paramount importance of decision support systems that analyze CT images to assist physicians in making medical decisions is undeniable [5].…”