Background: Distractor efficiency (DE) of multiple-choice questions (MCQs) responses is a component of the psychometric analysis used by the examiners to evaluate the distractors’ credibility and functionality. This study was conducted to evaluate the impact of the DE on the difficulty and discrimination indices. Methods: This cross-sectional study was conducted from April to June 2023. It utilizes the final exam of the Principles of Diseases Course with 45 s-year students. The exam consisted of 60 type A MCQs. Item analysis (IA) was generated to evaluate KR20, difficulty index (DIF), discrimination index (DIS), and distractor efficiency (DE). DIF was calculated as the percentage of examinees who scored the item correctly. DIS is an item’s ability to discriminate between higher and lower 27% of examinees. For DE, any distractor selected by less than 5% is considered nonfunctional, and items were classified according to the non-functional distractors. The correlation and significance of variance between DIF, DI, and DE were evaluated. Results: The total number of examinees was 45. The KR-20 of the exam was 0.91. The mean (M), and standard deviation (SD) of the DIF of the exam was 37.5(19.1), and the majority (69.5%) were of acceptable difficulty. The M (SD) of the DIS was 0.46 (0.22), which is excellent. Most items were excellent in discrimination (69.5%), only two were not discriminating (13.6%), and the rest were of acceptable power (16.9%). Items with excellent and good efficiency represent 37.3% each, while only 3.4% were of poor efficiency. The correlation between DE and DIF (p = 0.000, r= -0.548) indicates that items with efficient distractors (low number of NFD) are associated with those having a low difficulty index (difficult items) and vice versa. The correlation between DE and DIS is significantly negative (P = 0.0476, r=-0.259). In such a correlation, items with efficient distractors are associated with low-discriminating items. Conclusions: There is a significant moderate negative correlation between DE and DIF (P = 0.00, r = -0.548) and a significant weak negative correlation between DE and DIS (P = 0.0476, r = -0.259). DIF has a non-significant negative correlation with DIS (P = 0.7124, r = -0.0492). DE impacts both DIF and DIS. Items with efficient distractors (low number of NFD) are associated with those having a low difficulty index (difficult items) and discriminating items. Improving the quality of DE will decrease the number of NFDs and result in items with acceptable levels of difficulty index and discrimination power.

Background: Sedentary lifestyles, urbanization and improvements in socio-economic status have had serious effects on the burden of diabetes across the world. Diabetes is one of the 10 leading causes of death globally, and individuals with diabetes have a 2–3-fold increased risk of all-cause mortality. Adipose tissue is increasingly understood as a highly active endocrine gland that secretes many biologically active substances, including adipocytokines. However, the exact and discrete pathophysiological links between obesity and T2DM are not yet fully elucidated. Methods: In the current study, we present the association of five diverse adipocytokines, adiponectin, leptin, resistin, visfatin and chemerin, with T2DM in 87 patients (46 males and 41 females) with type 2 diabetes mellitus and 85 healthy controls (44 males and 41 females) from the Asir region of Saudi Arabia. The patients were divided into four groups: normal BMI, overweight, obese and severely obese. The baseline biochemical characteristics, including HbA1c and anthropometric lipid indices, such as BMI and waist–hip ratio, were determined by standard procedures, whereas the selected adipokine levels were assayed by ELISA. Results: The results showed significantly decreased levels of adiponectin in the T2DM patients compared to the control group, and the decrease was more pronounced in obese and severely obese T2DM patients. Serum leptin levels were significantly higher in the females compared to the males in the controls as well as all the four groups of T2DM patients. In the male T2DM patients, a progressive increase was observed in the leptin levels as the BMI increased, although these only reached significantly altered levels in the obese and severely obese patients. The serum leptin levels were significantly higher in the severely obese female patients compared to the controls, patients with normal BMI, and overweight patients. The leptin/adiponectin ratio was significantly higher in the obese and severely obese patients compared to the controls, patients with normal BMI, and overweight patients in both genders. The serum resistin levels did not show any significant differences between the males and females in thr controls or in the T2DM groups, irrespective of the BMI status of the T2DM patients. The visfatin levels did not reveal any significant gender-based differences, but significantly higher levels of visfatin were observed in the T2DM patients, irrespective of their level of obesity, although the higher values were observed in the obese and highly obese patients. Similarly, the serum chemerin levels in the controls, as well as in T2DM patients, did not show any significant gender-based differences. However, in the T2DM patients, the chemerin levels showed a progressive increase, with the increase in BMI reaching highly significant levels in the obese and severely obese patients, respectively. Conclusion: In summary, it is concluded that significantly altered concentrations of four adipokines, adiponectin, leptin, visfatin and chemerin, were found in the T2DM patient group compared to the controls, with more pronounced alterations observed in the obese and highly obese patients. Thus, it can be surmised that these four adipokines play a profound role in the onset, progression and associated complications of T2DM. In view of the relatively small sample size in our study, future prospective studies are needed on a large sample size to explore the in-depth relationship between adipokines and T2DM.

Background: The ongoing outbreak of SARS-CoV-2 represents a significant challenge to international health. Several reports have highlighted the importance of ACE2 on the pathogenesis of COVID-19. The spike protein of SARS-CoV-2 efficiently binds to the angiotensin-converting enzyme 2 (ACE2) receptors and facilitates virus entry into the host cell. In the present study, we hypothesize that a functional insertion/deletion polymorphism-rs4646994 I/D and rs4240157 T > C in the ACE gene could be associated with SARS-CoV-2 infection and mortality. Methodology: This study included 117 consecutive COVID-19 patients and 150 age matched healthy controls (ACE2-rs4646994 I/D) and 100 age matched healthy controls with ACE2 rs4240157 T > C. We used Mutation specific PCR (MSP) for ACE2-rs4646994 I/D genotyping and amplification refractory mutation system (ARMS-PCR) for ACE2 rs4240157 T > C genotyping. Results: Results indicated that there were significant differences in the genotype distributions of ACE2-rs4646994 I/D polymorphisms (p < 0.030) and ACE2 rs4240157 T > C between COVID-19 patients and controls (p-values < 0.05). Higher frequency of DD genotype (48.71%) and D allele (0.67) was reported in COVID-19 patients than controls. Our results showed that the ACE2-DD genotype was strongly associated with increased COVID-19 severity (OR 2.37 (95%) CI = (1.19–4.70), RR = 1.39 (1.09–1.77), p < 0.013) and also a strong association was seen with ACE2-ID genotype with COVID-19 severity (OR 2.20 (95%) CI = (1.08–4.46), p < 0.020) in the codominant model. In allelic comparison, the D allele was strongly associated with COVID-19 severity (OR 1.58 (95% CI) (1.11–2.27), RR 1.21 (1.05–1.41) p < 0.010). A significant correlation of ACE2-I/D genotypes was reported with Age (p < 0.035), T2D (p < 0.0013), hypertension (p < 0.0031) and coronary artery disease (p < 0.0001). Our results indicated ACE2-DD genotype was strongly associated with increased COVID-19 mortality (OR 8.25 (95%) CI = (2.40 to 28.34), p < 0.008) and also ACE2-DD + DI genotype was strongly associated with increased COVID-19 mortality with OR 4.74 (95%) CI = (1.5214 to 14.7915), p < 0.007. A significant correlation was reported between COVID-19 patients and age matched controls (p < 0.0007). Higher frequency of heterozygosity TC (40%) followed by ACE2-CC genotype (24.78%) was reported among COVID-19 patients. Using multivariate analysis, ACE2–CT genotype was strong associated with SARS-CoV-2 severity with an OR 2.18 (95% CI) (1.92–3.99), p < 0.010 and also ACE2–CC genotype was linked with COVID-19 severity with an OR 2.66 (95% CI) (1.53–4.62), p < 0.005. A significant correlation of ACE2-T > C genotypes was reported with gender (p < 0.04), T2D (p < 0.035). ACE2-CC genotype was strongly associated with increased COVID-19 mortality OR 3.66 (95%) CI = (1.34 to 9.97), p < 0.011 and also ACE2-C allele was associated with COVID-19 mortality OR 2, 01 (1.1761–3.45), p < 0.010. Conclusions: It is concluded that ACE-DD genotype and D allele was strongly associated with increased COVID-19 patient severity. In addition, ACE I/D polymorphism were strongly associated with advanced age, diabetes and ischemic heart disease in COVID-19 patients whereas ACE-II genotype was a protective factor against the development of severe COVID-19. ACE2-DD genotype was strongly associated with increased COVID-19 mortality. Additionally, ACE2–CC and CT genotypes were strongly associated with COVID-19 severity. Therefore, our study might be useful for identifying the susceptible population groups for targeted interventions and for making relevant public health policy decisions.

Although the coronavirus disease 2019 (COVID-19) pandemic continues to rage worldwide, clinical and laboratory studies of this disease have been limited in many countries. We investigated the epidemiologic, clinical, and laboratory findings of COVID-19 infected patients to identify the effective indicators correlated with the disease. A retrospective study was conducted at King Abdullah Hospital in Bisha Province, Saudi Arabia, from March 20 to June 30, 2020. Patients of different age groups were confirmed as having COVID-19 infection using a real-time polymerase chain reaction. The demographic, clinical, and laboratory data of the patients were statistically analyzed. Of the 132 patients, 85 were male and 47 were female, with a mean age of 50.9 years (SD±16.7). The patients were elderly (n = 29) and adults (n = 103). Of these, 54 (40.9%) had comorbidities, (25%) were admitted to the intensive care unit (ICU), and 12 (9.1%) died. On admission, the main clinical manifestations were fever (84.1%), cough (64.4%), shortness of breath (25%), chest pain (20.5%), and fatigue (18.2%). In all patients, increased neutrophils and decreased lymphocytes were observed. Patients’ lactate dehydrogenase (LDH) was elevated. C-reactive protein (CRP) was elevated in 48.5%, D-dimer in 43.2%, and the erythrocyte sedimentation rate (ESR) in 40.9% of patients. The elderly showed higher neutrophil (p = 0.011) and lower lymphocyte (p = 0.009) counts than adults. Glucose, creatine kinase-MB, LDH, bilirubin, D-dimer, and ESR were significantly higher in the elderly than in the adults. The COVID-19 death group had a higher leucocyte count (p = 0.036), and higher urea (p = 0.029) and potassium (p = 0.022) than the recovered group but had a lower hemoglobin concentration (p = 0.018). A significant association was determined between COVID-19 death and the presence of cardiovascular disease (χ2(1) = 16.297, p<0.001), hypertension (χ2(1) = 12.034, p = 0.001), renal failure (χ2(1) = 3.843, p = 0. 05), old age (t (130) = 4.9, p <0.001), and ICU admission (χ2(1) = 17.6 (1), p<0.001). Investigating some of the laboratory and clinical parameters could help assess the disease progression, risk of mortality, and follow up patients who could progress to a fatal condition.

Background: Rheumatic diseases encompass a diverse group of autoimmune disorders that affect the joints and connective tissues. The red blood cell distribution width (RDW) has been widely investigated as an inflammatory marker. This scoping review aimed to explore the potential utility of RDW as an inexpensive marker for disease activity in patients with rheumatic diseases. By summarizing the available evidence, we aimed to determine whether RDW can serve as a reliable and accessible indicator of disease activity in these patients. Methods: A comprehensive search was systematically performed across electronic databases, encompassing PubMed, Embase, and Web of Science. Studies have explored the relationship between RDW and disease activity in rheumatic diseases. Data extraction focused on the study characteristics, methodologies, and findings related to RDW as a disease activity marker. Results: After removing duplicates, the initial search yielded 25 relevant studies. These studies encompassed a variety of rheumatic diseases, with rheumatoid arthritis being the most frequently studied condition. The association between RDW and disease activity was assessed by using various disease activity indices and clinical parameters. While some studies have reported a significant correlation between elevated RDW and disease activity, others have yielded inconclusive results. Conclusion: From this review, we concluded that RDW is an inexpensive potential marker for the evaluation of disease activity in rheumatic diseases. RDW is promising as an inexpensive and readily available marker; however, its clinical utility in assessing disease activity in rheumatic conditions warrants more rigorous investigation through well-designed prospective studies.

Introduction: With the incorporation of artificial intelligence (AI), significant advancements have occurred in the field of fetal medicine, holding the potential to transform prenatal care and diagnostics, promising to revolutionize prenatal care and diagnostics. This scoping review aims to explore the recent updates in the prospective application of AI in fetal medicine, evaluating its current uses, potential benefits, and limitations. Methods: Compiling literature concerning the utilization of AI in fetal medicine does not appear to modify the subject or provide an exhaustive exploration of electronic databases. Relevant studies, reviews, and articles published in recent years were incorporated to ensure up-to-date data. The selected works were analyzed for common themes, AI methodologies applied, and the scope of AI’s integration into fetal medicine practice. Results: The review identified several key areas where AI applications are making strides in fetal medicine, including prenatal screening, diagnosis of congenital anomalies, and predicting pregnancy complications. AI-driven algorithms have been developed to analyze complex fetal ultrasound data, enhancing image quality and interpretative accuracy. The integration of AI in fetal monitoring has also been explored, with systems designed to identify patterns indicative of fetal distress. Despite these advancements, challenges related to the ethical use of AI, data privacy, and the need for extensive validation of AI tools in diverse populations were noted. Conclusion: The potential benefits of AI in fetal medicine are immense, offering a brighter future for our field. AI equips us with tools for enhanced diagnosis, monitoring, and prognostic capabilities, promising to revolutionize the way we approach prenatal care and diagnostics. This optimistic outlook underscores the need for further research and interdisciplinary partnerships to fully leverage AI’s potential in driving forward the practice of fetal medicine.