Spontaneous cerebrospinal fluid rhinorrhea as a primary presentation of idiopathic intracranial hypertension, management strategies, and clinical outcome.

Background: Causes of cerebrospinal fluid (CSF) rhinorrhea could be divided into primary (spontaneous) and secondary (head trauma and iatrogenic). Idiopathic intracranial hypertension (IIH) has emerged as a cause for spontaneous CSF rhinorrhea but is still underestimated, may be overlooked and needs special consideration in management. The objective of this study is to demonstrate spontaneous CSF rhinorrhea as the primary presentation of IIH and explore the algorithm of management.

SLA-MLP: Enhancing Sleep Stage Analysis from EEG Signals Using Multilayer Perceptron Networks.

: Sleep stage analysis is considered to be the key factor for understanding and diagnosing various sleep disorders, as it provides insights into sleep quality and overall health. : Traditional methods of sleep stage classification, such as manual scoring and basic machine learning approaches, often suffer from limitations including subjective biases, limited scalability, and inadequate accuracy. Existing deep learning models have improved the accuracy of sleep stage classification but still face challenges such as overfitting, computational inefficiencies, and difficulties in handling imbalanced datasets.

Changes of blood cholinesterase activities among pesticides-exposed agricultural workers in Iraq: A meta-analysis.

Numerous studies in Iraq have attempted to determine blood cholinesterase (ChE) activities with varying results in agricultural workers and veterinarians exposed to pesticides. This meta-analysis answers the specific inquiry of whether or not blood ChE activities decrease in agricultural workers exposed previously to pesticides. The meta-analysis included 14 records of blood ChE activities extracted from 12 studies after employing the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA).

Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort.

Schizophrenia presents significant diagnostic and treatment challenges, particularly in distinguishing between treatment-resistant (TRS) and non-treatment-resistant schizophrenia (NTRS). This cross-sectional study analyzed routine laboratory parameters as potential biomarkers to differentiate TRS, NTRS, and healthy individuals within a Qatari cohort. The study included 31 TRS and 38 NTRS patients diagnosed with schizophrenia, alongside 30 control subjects from the Qatar Biobank.