Background: Epilepsy is a common, long-term neurological condition. Several previous case-control, cohort and cross-sectional studies have highlighted the role of prenatal, delivery and postnatal factors in the onset of epilepsy. In this systematic review, we evaluate the impact of these factors on the development of epilepsy in children and adolescents.Methods: We searched PubMed and Google Scholar for literature on the relationship between prenatal, delivery and postnatal factors and the occurrence of epilepsy. The research was performed according to the PRSIMA 2020 flowchart and checklist. Data were extracted and pooled according to the ReviewManager 5.3 software using a random-effects model. Sensitivity analysis and subgroup analysis were used to evaluate the source of heterogeneity.Results: We identified 25 reports, including 45,044 cases with confirmed epilepsy and 2,558,210 controls. Premature birth is significantly associated with the risk of epilepsy (pooled OR = 4.36 [95% CI: 1.26–15.09],P = 0.02). Smoking during pregnancy significantly increases this risk by 28% (pooled OR = 1.28 [95% CI:1.1–1.49],P = 0.002). Furthermore, maternal epilepsy confers a pooled OR of 2.06 [95% CI:1.26–3.36]. Eclampsia is linked to a 16.9-fold increased risk of epilepsy. In addition, both pregnancy metrorrhagia and maternal infection are significantly associated with the epilepsy risk (pooled OR = 2.24 [95% CI: 1.36–3.71] and 1.28 [95% CI: 1.17–1.41], respectively). For delivery conditions, cord prolapse (pooled OR = 2.58 [95% CI: 1.25–5.32]), prolonged labor (> 6 h) (OR = 6.74 [95% CI: 3.57–12.71]) and head trauma (pooled OR = 2.31 [95% CI: 1.54–3.48]) represent a meaningful risk of epilepsy occurrence. Moreover, birth complications (OR = 3.91 [95% CI: 2.43–6.29]), low birth weight (pooled OR = 1.83 [95% CI: 1.5–2.23]) and male birth (pooled OR = 1.18 [95% CI: 1.06–1.32]) are associated with an elevated risk of epilepsy in childhood and adolescence.Conclusions: Epilepsy in children and adolescents can be attributed to a multitude of intricate factors, notably those during pregnancy, delivery and the postnatal period. These findings highlight the crucial role of prenatal and postnatal care in reducing the impact of these factors on epilepsy occurrence.

Background: Diagnosis of Alzheimer's disease (AD) is crucial for effective intervention and care planning. Recently, artificial intelligence-driven eye-tracking (AI-driven ET) tools have emerged as promising diagnostic aids. Objective: To evaluate the diagnostic accuracy of AI-driven ET models for AD detection. Methods: A systematic review and meta-analysis were conducted according to PRISMA2020. Different database and grey literature were searched up to March 2025. Data were analyzed with Meta-Disc 1.4 and R software. This meta-analysis has been registered in PROSPERO (CRD420251020284). Results: Ten papers were included in the narrative synthesis and eight in the meta-analysis. Our systematic review found that most studies reported moderate to good accuracy of AI-driven ET tools in AD detection. The meta-analysis revealed that AI-driven ET tools achieved a sensitivity of 0.75 [95% CI: 0.67; 0.79], specificity of 0.75 [95% CI: 0.67; 0.81], positive likelihood ratio of 3.29 [95% CI: 2.36; 4.59], negative likelihood ratio of 0.36 [95% CI: 0.27; 0.48], diagnostic odds ratio of 10.40 [95% CI: 5.58; 19.39], and area under the ROC curve of 0.81. Deep learning seems to have better performance than supervised machine learning (SML). Among classification algorithms, support vector machines appear most robust across studies. The meta-regression identified population size, patient preparation, measurement systems, AI techniques, and SML algorithms as significant sources of heterogeneity. Conclusions: AI-driven ET tools suggest moderate to good diagnostic accuracy for distinguishing AD patients from healthy controls, based on available case-control studies. However, evidence for effective screening in broader populations is lacking. Further research is needed to confirm these results across diverse clinical settings and strengthen model robustness.

Background: Migraine is a prevalent and debilitating neurological condition that significantly impact the academic lives of university students. Despite its high prevalence, migraine is often underreported, underdiagnosed, and inadequately managed particularly in the Middle East and North Africa (MENA) region. Objective: This study aimed to determine the prevalence of migraine identified by screening, related disability, and psychological comorbidities among university students in the MENA region. Methods: We conducted a multinational cross-sectional study among university students in 11 low and middle-income countries in the MENA region, using an anonymous self-administered questionnaire. The convenience and snowball sampling methods were used. This study utilized a validated questionnaire to collect data on migraine frequency, characteristics, disability, associated depression, anxiety, and triggers. Results: The present study screened a total of 5,954 students for migraine. Of them, 26.1% screened positive for migraine. Iraq had the highest prevalence 38.9%, followed by Algeria 31.5%, and the lowest was in Egypt 19.9% and Morocco 18.4%. Common migraine triggers included sleeping disturbances 59.7%, noise 47.4%, and sun exposure 45.6%. Among positive cases, 23.2% had severe disability, 29.9% had moderate anxiety, and 72.5% had severe depression. The main predictors of migraine were females, older age, and non-medical field university students. Adequate hydration, sufficient sleep, regular physical activity, higher fluid intake, and extended study hours were associated with a lower risk of migraine. Daily caffeine consumption was associated with increased migraine risk. A modest negative relationship was found between academic success and migraine disability score. Conclusion: Our results demonstrated a high proportion of students screened positive for migraine with significant associations to depression, anxiety, and disability. These findings highlight the need for targeted interventions to increase awareness about migraine-related comorbidities, screening programs to help in early detection, and lifestyle modification. Universities should develop and implement coping strategies to support affected students.