Neurosciences最新文献

Objectives: To measure sleep patterns and quality during summer vacation and weeks 1-4 of the academic year among female university students.

Methods: This retrospective prospective cohort study included female students at a university in Riyadh, Saudi Arabia. Participants were recruited with convenience sampling and completed questionnaires online. The questionnaire asked about 5 occasions using the Sleep Quality Scale (SQS) and about their sleep schedule during summer vacation and weeks 1-4 of the academic year.

Results: There were 385 participants. The number of students who slept before midnight increased over time from n=127 (32.9%) students during vacation to n=172 (44.6%) students in week 4 (p<0.001). The average sleep hours decreased from 8.97 (standard deviation (SD)=2.6) hours during summer to 7.01 (p<0.001, SD=2.7) hours in week 4. Students reported poorer sleep quality during the academic year, particularly in week 1 (p=0.023), than summer. Students reported higher satisfaction with sleep during summer vacation (n=97; 25.2%) than week 1 (n=38; 9.9%) and week 4 (n=36; 9.4%) (p<0.001). Students experienced daytime fatigue and tiredness (n=79; 20.5%; p=0.002) and low concentration in week 4 (n=79; 20.5%; p<0.001) compared to summer.

Conclusion: In the studied population, multiple sclerosis was the most prevalent cause of ON. Women were more likely to have ON. The prognosis for eyesight was substantially connected with the length of ON.

Objectives: To investigate the effects of Cervical Mobilization (CM) and Clinical Pilates Exercises (CPE) in Cervigogenic Headache (CHA).

Methods: The 37 patients were randomized into the 3 groups. The CM for 1st group, CPE for 2nd group and CM+CPE for 3rd group were applied 3 days/a week for 6 weeks. Pain frequency, pain intensity, number of analgesic, were recorded. The posture was measured by Posture Screen application, the cervical range of motion by the CROM device, deep neck flexor muscle endurance by the pressurized biofeedback device. Evaluations were applied 2 times as pre-post treatment.

Results: In within-group comparison a decrease in pain parameters, neck-shoulder postural deviation and an increase DNFE and CROM were observed in all groups (p<0.05). In between-group comparison pain frequency, intensity and number of analgesics were significant changes in the CM and CM+CPE groups according to CPE (respectively p<0,001, p=0,001, p=0,018). Head and shoulder angulation were significant in the CPE and CM+CPE groups according to CM (respectively p=0.009, p=0,011). It was determined that the cervical right lateral flexion range of motion and right rotation were significant changes in the CM and CM+CPE groups according to CPE (respectively p=0,026, p=0,040). DNFE were significantly increased in CM+CPE according to CM and CPE (p=0.001).

Conclusion: This study suggests that it would be beneficial to add CM and CPE to the treatment plans of patients with CHA.

Moyamoya disease is an idiopathic chronic and progressive vaso-occlusive disease ofthe bilateral intracranial branches of the internal carotid artery. Growth hormone failure, thyroid dysfunction, and low cortisol hormones are consequences of hypopituitarism. A 14-year-old girl with short stature presented with right-sided weakness associated with dysarthria. Ahormonal assay test showed abnormality ofthe anterior pituitary hormones. Magnetic resonance imaging of the brain and pituitary gland showed a reduction in the size of the adenohypophysis. A cerebral vessel angiogram showed multiple areas of stenosis in the right internal carotid artery. Magnetic resonance angiography demonstrated stenosis at the suprasellar region of the bilateral internal carotid artery. Pituitary dysfunction associated with moyamoya disease is rare but must be considered as adifferential diagnosis for any patient with hypopituitarism. Hypothalamopituitary dysfunction as result of carotid ischemia might be associated with moyamoya disease. Such patients require close follow-up and hormonal assay tests.

Objectives: To investigate the clinical results of optic neuritis (ON) patients in a tertiary medical facility in Makkah, Kingdom of Saudi Arabia.

Methods: The data of patients assessed for ON at Makkah, Saudi Arabia's King Abdullah Medical Center (KAMC), was examined retrospectively.

Results: We identified 15 patients with ON. The ON was caused by multiple sclerosis (MS) in 73.3% of patients and neuromyelitis optica spectrum disorder (NMOSD) in 26.7% of patients. The disease was bilateral in 60% of patients and unilateral in 40% of patients. Additionally, 60% of patients had 2 or more episodes of ON, whereas 40% had a single episode. Patients with ON who presented with painful eye movements had a significantly longer disease duration (p=0.032). Moreover, patients whose disease duration was 11-15 days did not achieve a complete resolution of their symptoms and experienced some residual vision loss compared to 30.8% who had continued visual changes (p=0.049).

Conclusion: In the studied population, multiple sclerosis was the most prevalent cause of ON. Women were more likely to have ON. The prognosis for eyesight was substantially connected with the length of ON.

Objectives: To assess clinicians' adherence to fingolimod's effective use according to the prescribed recommendations to reduce safety risk, identify the consequences, and highlight areas for improvement to policy makers for the benefit of both patient and care-giver.

Methods: A retrospective observational study conducted at a tertiary hospital targeting multiple sclerosis patients on fingolimod from January 2017 to December 2021. The physicians' adherence to the manufacturer's instructions was assessed and categorized into good, moderate, and poor based on adherence to fingolimod instructions and monitoring measures. Four monitoring measures were assessed: bradycardia observation, ophthalmic examination, liver enzymes, and infections. In addition, the impact of adherence on patient safety was also assessed.

Results: A total of 140 patients were included. Seventy-twopatients (51.4%) had physician with poor adherence (followed only one instruction or none). Sixty-five patients (46.4%) had 2-3 manufacture recommendations where physician's adherence was moderate. Three patients (2.10%) had all manufacturer's recommendations. In terms of fingolimod complications, 18 patients found to have bradycardia after the first does, macular oedema and infections was reported in 4 patients, and the elevation in hepatic enzymes was reported in 6 patients. Poor physician's adherence has resulted in treatment incompleteness and highest fingolimod discontinuation or switching to other treatment options.

Conclusion: Adherence to fingolimod instructions was poor among physicians which resulted in highest drug switching or discontinuing rate.

Objectives: To develop a machine learning model to accurately predict stroke risk based on demographic and clinical data. It also sought to identify the most significant stroke risk factors and determine the optimal machine learning algorithm for stroke prediction.

Methods: This cross-sectional study analyzed data on 438,693 adults from the 2021 Behavioral Risk Factor Surveillance System. Features encompassed demographics and clinical factors. Descriptive analysis profiled the dataset. Logistic regression quantified risk relationships. Adjusted mutual information evaluated feature importance. Multiple machine learning models were built and evaluated on metrics like accuracy, AUC ROC, and F1 score.

Results: Key factors significantly associated with higher stroke odds included older age, diabetes, hypertension, high cholesterol, and history of myocardial infarction or angina. Random forest model achieved the best performance with accuracy of 72.46%, AUC ROC of 0.72, and F1 score of 0.74. Cross-validation confirmed its reliability. Top features were hypertension, myocardial infarction history, angina, age, diabetes status, and cholesterol.

Conclusion: The random forest model robustly predicted stroke risk using demographic and clinical variables. Feature importance highlighted priorities like hypertension and diabetes for clinical monitoring and intervention. This could help enable data-driven stroke prevention strategies.