Dry eye disease (DED) is a multifactorial condition affecting the ocular surface. Recombinant human nerve growth factor (rhNGF) has emerged as a potential new treatment for neurosensory dysfunction. The aim of this study is to evaluate the efficacy and safety of rhNGF in patients with DED. A comprehensive search of six online databases—Medline, CENTRAL, Web of Science, Ovid Medline, ClinicalTrials.gov, and Google Scholar—was conducted to identify randomized controlled trials (RCTs) evaluating the efficacy and safety of rhNGF in patients with dry eye disease, focusing on outcomes such as tear production, ocular surface integrity, and adverse events. The results demonstrated that rhNGF significantly improved tear production compared with placebo, as measured by the Schirmer test (MD = 3.84; 95
There is a great need to categorize cancer types for early cancer detection and treatment. RNA-Seq data is essential for getting insight into the differentially expressed genes. Due to its high dimensionality and complexity, performing an analysis on RNA-Seq data is quite challenging. In the past, RNA-Seq data were analyzed for a single cancer type as a two-class problem (either positive or negative) and did not contain information from other classes of cancer types. To classify different cancer types and discover the most promising genes, RNA-Seq data for different types of cancer should be examined. Multiple repositories offer RNA-Seq-based cancer types data. The present study incorporates a dataset from the Mendeley repository for classification. RNA-Seq values are then converted to their respective 2D images using some transformations. The classification problem is handled by five Transfer Learning (TL) algorithms (VGG16, VGG19, Resnet50, Resnet101, and Resnet152). Four different splitting strategies are applied for each classifier presented in the results and discussion section. A comparative analysis is also carried out with and without data augmentation. Results show that classifiers perform best at a split of 70-30. VGG16 attained the best position on overall results by achieving an accuracy of 95%. Hence, VGG16 is the leading TL algorithm for classification among all the accessible models and is not difficult to execute and easy to comprehend.
Background Chronic diseases are the leading causes of death and disability, and their care consumes a large proportion of healthcare expenditures. Early detection and appropriate management of chronic diseases can significantly mitigate their health, societal, and economic consequences. Monitoring the national prevalence of chronic diseases and their risk factors is essential to inform health policy and guide public health interventions. Methods The Saudi national Health INdicators survEy (SHINE) aimed to assess the prevalence of selected non-communicable diseases (NCDs) and their risk factors among adults in Saudi Arabia. The SHINE was a national telephone-based survey conducted in 2023 by the Saudi Public Health Authority. Participants aged 18 years or older were randomly selected from a national sampling frame of cell phone numbers, encompassing all administrative regions of Saudi Arabia. Data were collected on the prevalence of NCDs, including hypertension, diabetes, heart disease, renal disease, and asthma, as well as risk factors such as obesity and tobacco use. Multivariable regression analyses were conducted to assess associations between risk factors and NCDs. Results The total sample size was 2,650 participants. Hypertension and diabetes were the most commonly reported chronic conditions, with a national prevalence of 16.1% and 13.0%, respectively. Approximately 10% of the population reported having been diagnosed with two or more chronic conditions. Obesity was reported by 32.8% of the population, and tobacco use was reported by 24.9%. Body mass index was the strongest independent predictor of self-reported diagnosed diabetes, hypertension, asthma, and multimorbidity after adjustment for sociodemographic characteristics. Conclusions NCDs impose a significant health burden on the Saudi population, particularly among aging Saudi nationals. Continuous monitoring of the prevalence of chronic diseases and their risk factors is vital to inform and optimize national prevention efforts.
Background:Ectopic pregnancy (EP) is an abnormal condition in which blastocyst implantation occurs outside the lining of the uterus and is the leading cause of pregnancy-related death. Women who have had one ectopic pregnancy are at increased risk. Early diagnosis may reduce the risk of fallopian tube rupture. Aim:This study assessed the level of knowledge related to ectopic pregnancy among married Saudi women in Riyadh, Saudi Arabia. Method:A descriptive cross-sectional design was used. This study was conducted at outpatient obstetrics clinics at the Women's Health Specialist Hospital at King Fahad National Guard Hospital in Riyadh. The convenience sample consisted of 255 pregnant women. The data were collected through a structured interviewing questionnaire, which consisted of demographic data and an ectopic pregnancy knowledge assessment tool. Results:The study's findings revealed that the mean age of the women was 35.50 ± 6.45 years. More than half of the study sample (66.7%) had a university education, and 63.9% delivered via normal vaginal delivery, whereas 27.8% delivered via cesarean section. More than half of the sample had a poor level of knowledge regarding signs and symptoms, diagnosis, complications, and management of EP, with the total mean knowledge score for ectopic pregnancy being 56.96 ± 17.09. Overall, the study sample (60.40%) demonstrated a poor level of knowledge, 31% had a fair level of knowledge, and only 8.6% had a good level of knowledge. Recommendations:Designing an educational program for women to increase awareness of ectopic pregnancy, including its signs, symptoms, and risk factors, to improve the understanding and prevention of complications of EP.
Migraine is a common neurological disorder that substantially impacts individuals' health and quality of life. This study aimed to estimate the prevalence of migraine and identify factors associated with it among patients attending primary healthcare centers (PHCs) in Saudi Arabia. We conducted a cross-sectional study from March to July 2023, involving 14,239 participants from 48 PHCs within Health Cluster 2 in the Riyadh region of Saudi Arabia. We collected data on participants' sociodemographic characteristics, behavioral risk factors, and existing comorbidities using a validated questionnaire. Migraine status was determined based on participants' self-reported prior physician diagnosis of migraine. To identify factors independently associated with migraine, we used multivariable logistic regression analysis. The adjusted odds ratios (AORs) and their 95% confidence intervals (CIs) were calculated to show the strength of these predictors. The prevalence of migraine was 5.9%. In the multivariable analysis, males had significantly lower odds of migraine compared to females (AOR = 0.69, 95% CI [0.59, 0.80], P < .001). Individuals with insurance coverage had higher odds of migraine (AOR = 2.44, 95% CI [2.11, 2.82], P < .001). Smoking (AOR = 2.44, 95% CI [2.05, 2.92], P < .001), and exercise (AOR = 1.46, 95% CI [1.18, 1.82], P < .001) were associated with higher odds of migraine. Several comorbidities were also significantly associated with migraine: obesity (AOR = 6.08, 95% CI [4.95, 7.47], P < .001), hypercholesterolemia (AOR = 2.59, 95% CI [2.07, 3.25], P < .001), hypertension (AOR = 1.47, 95% CI [1.15, 1.86], P = .002), and heart disease (AOR = 3.25, 95% CI [2.55, 4.15], P < .001). In this Saudi Arabian population, female sex, insurance coverage, smoking, obesity, hypercholesterolemia, hypertension, and heart disease were identified as significant predictors of migraine. These findings highlight the need for targeted preventive strategies and integrated care approaches addressing modifiable risk factors and comorbidities to reduce the burden of migraine.
