Short-term outcomes after a neonatal arterial ischemic stroke

Epidemiology, causes, and morbidities of stroke in the young

PURPOSE OF REVIEW

The purpose is to describe the latest research on epidemiology, causes, and morbidities of stroke in neonates and children.

RECENT FINDINGS

The global incidence of childhood stroke is approximately 2 per 100 000 person-years, which is significantly lower compared to neonates (20-40 per 100 000 live births) and adults (80-90 per 100 000 person-years). Placental abnormalities are a risk factor for perinatal stroke, although cause is usually multifactorial. In children, nonatherosclerotic arteriopathies and arteriovenous malformations are major causes of ischemic and hemorrhagic strokes, respectively. The perinatal period confers a high risk of stroke and can lead to long-term disability, including motor delay, cognitive or speech impairment, and epilepsy. Recent studies suggest that at least 50% of survivors of perinatal stroke have abnormal neurodevelopmental scores in long-term follow up. Childhood stroke is associated with significant morbidity, including epilepsy, motor impairments, and behavioral disability. Recent studies have also identified an association between pediatric stroke and behavioral disorders, such as attention deficit hyperactivity disorder and autism.

SUMMARY

Perinatal and childhood strokes are important causes of neurological morbidity. Given the low incidence of childhood stroke, prospective research studies on epidemiology, causes, and outcomes remain limited, highlighting the need for continued multisite collaborations.

Prediction model for hepatocellular carcinoma recurrence after hepatectomy: Machine learning-based development and interpretation study

Background

Identifying patients with hepatocellular carcinoma (HCC) at high risk of recurrence after hepatectomy can help to implement timely interventional treatment. This study aimed to develop a machine learning (ML) model to predict the recurrence risk of HCC patients after hepatectomy.

Methods

We retrospectively collected 315 HCC patients who underwent radical hepatectomy at the Third Affiliated Hospital of Sun Yat-sen University from April 2013 to October 2017, and randomly divided them into the training and validation sets at a ratio of 7:3. According to the postoperative recurrence of HCC patients, the patients were divided into recurrence group and non-recurrence group, and univariate and multivariate logistic regression were performed for the two groups. We applied six machine learning algorithms to construct the prediction models and performed internal validation by 10-fold cross-validation. Shapley additive explanations (SHAP) method was applied to interpret the machine learning model. We also built a web calculator based on the best machine learning model to personalize the assessment of the recurrence risk of HCC patients after hepatectomy.

Results

A total of 13 variables were included in the machine learning models. The multilayer perceptron (MLP) machine learning model was proved to achieve optimal predictive value in test set (AUC = 0.680). The SHAP method displayed that γ-glutamyl transpeptidase (GGT), fibrinogen, neutrophil, aspartate aminotransferase (AST) and total bilirubin (TB) were the top 5 important factors for recurrence risk of HCC patients after hepatectomy. In addition, we further demonstrated the reliability of the model by analyzing two patients. Finally, we successfully constructed an online web prediction calculator based on the MLP machine learning model.

Conclusion

MLP was an optimal machine learning model for predicting the recurrence risk of HCC patients after hepatectomy. This predictive model can help identify HCC patients at high recurrence risk after hepatectomy to provide early and personalized treatment.

Role of advanced (magnetic resonance) neuroimaging and clinical outcomes in neonatal strokes: Experience from tertiary care center

Neonatal strokes constitute a major cause of pediatric mortality and morbidity. Neuroimaging helps in its diagnosis as well as prognostication. However, advanced imaging, including magnetic resonance imaging (MRI), carries multiple challenges. Limited data exists in the literature on imaging-based predictors of neurological outcomes in neonatal stroke in the Indian population. In this study, we reviewed our available data on neonatal stroke patients between 2015 and 2020 for clinico-radiological patterns. During this period, 17 neonatal strokes were admitted and the majority were term births with a slight male preponderance. Seizures and encephalopathy were the most common presentation. Multiple maternal risk factors such as gestational diabetes, meconium-stained liquor, APLA syndrome, fever, deranged coagulation profile, oligohydramnios, cord prolapse, and non-progressive labor were seen. Cardiac abnormalities were seen in only less than half of these patients with the most common finding being atrial septal defects (ASD). Transcranial ultrasound was performed in eight neonates and the pick-up rate of ultrasound was poor. MR imaging showed large infarcts in 11 patients. The MCA territory was most commonly involved. Interestingly, five neonates had venous thrombosis with three showing it in addition to arterial thrombosis. Associated ictal, as well as Wallerian changes, were noted in 10. Although large territorial infarcts were the most common pattern, non-contrast MR angiography did not show major vessel occlusion in these cases. Outcomes were fairly good and only three patients had a residual motor deficit at 1 year. No recurrence of stroke was seen in any of the neonates.

Neonatal Arterial Ischemic Stroke Secondary to Carotid Artery Dissection: A Case Report and Systematic Literature Review

BACKGROUND

Carotid artery (CA) dissection is a rare etiology of neonatal arterial ischemic stroke (NAIS).

METHODS

We describe one novel case and conduct a systematic literature review on NAIS attributed to CA dissection, to collect data on its clinical-radiological presentation, treatment, and outcome.

RESULTS

Eight published cases of NAIS attributed to CA dissection were identified and analyzed with our case. All patients (nine of nine) were born at term, and eight of nine experienced instrumental/traumatic delivery or urgent Caesarean section. None had fetal problems during pregnancy or thrombophilia. Signs and symptoms at presentation (between days of life 0 and 6) included seizures (eight of nine), respiratory distress or irregular breathing (five of nine), hyporeactivity, decreased consciousness or irritability (four of nine), and focal neurological signs (two of nine). At magnetic resonance imaging (MRI), stroke was unilateral in seven of nine and extensive in five of nine. CA dissection was documented by neuroimaging or at postmortem studies (seven of nine), and hypothesized by the treating physicians based on delivery and neuroradiology characteristics (in the remaining two of nine). Antithrombotic treatment was used in two of nine. According to available follow-up, one of eight died at age seven days, seven of eight had neurological/epileptic sequelae, and CA recanalization occurred in three of four.

CONCLUSIONS

NAIS attributed to CA dissection is rarely identified in the literature, often preceded by traumatic/instrumental delivery, presenting with seizures and systemic signs/symptoms, and often characterized by extensive MRI lesions and neurological sequelae. Definite evidence and recommendations on antithrombotic treatment are lacking.