The study describes the general concept of the XLindley distribution. Forms of density and hazard rate functions are investigated. Moreover, precise formulations for several numerical properties of distributions are derived. Extreme order statistics are established using stochastic ordering, the moment method, the maximum likelihood estimation, entropies and the limiting distribution. We demonstrate the new family’s adaptability by applying it to a variety of real-world datasets.

The COVID-19 pandemic continues with new waves that could persist with the arrival of new SARS-CoV-2 variants. Therefore, the availability of validated and effective triage tools is the cornerstone for proper clinical management. Thus, this study aimed to assess the validity of the ISARIC-4C score as a triage tool for hospitalized COVID-19 patients in Saudi Arabia and to compare its performance with the CURB-65 score. This retrospective observational cohort study was conducted between March 2020 and May 2021 at KFHU, Saudi Arabia, using 542 confirmed COVID-19 patient data on the variables relevant to the application of the ISARIC-4C mortality score and the CURB-65 score. Chi-square and t-tests were employed to study the significance of the CURB-65 score and the ISARIC-4C score variables considering the ICU requirements and the mortality of COVID-19 hospitalized patients. In addition, logistic regression was used to predict the variables related to COVID-19 mortality. In addition, the diagnostic accuracy of both scores was validated by calculating sensitivities, specificities, positive predictive value, negative predictive value, and Youden's J indices (YJI). ROC analysis showed an AUC value of 0.834 [95% CI; 0.800–0.865]) for the CURB-65 score and 0.809 [95% CI; 0.773–0.841]) for the ISARIC-4C score. The sensitivity for CURB-65 and ISARIC-4C is 75% and 85.71%, respectively, while the specificity was 82.31% and 62.66%, respectively. The difference between AUCs was 0.025 (95% [CI; −0.0203-0.0704], p = 0.2795). Study results support external validation of the ISARIC-4C score in predicting the mortality risk of hospitalized COVID-19 patients in Saudi Arabia. In addition, the CURB-65 and ISARIC-4C scores showed comparable performance with good consistent discrimination and are suitable for clinical utility as triage tools for hospitalized COVID-19 patients.

This paper presents the bivariate Poisson-new XLindley distribution (BPNXLD), which may be used to represent dependent and over-dispersed countdata. Among the characteristics considered are the correlation coefficient, mean, and variance of the distribution. Acomparison with several Bivariate distributions is included. The goodness of fit of this novel model iscompared with the bivariate Poisson, bivariate negative binomial and bivariate Poisson-Lindley distributions using two data sets from a German Bundesliga season.

Background: Heart diseases are one of the major causes for death especially in developing countries across the world. According to WHO, the deaths due to heart diseases in Iraq has reached 18.50% of total death in 2017 and Iraq has been identified as 19 th rank at the international level. In our study, the heart diseases are categorized as electrical, circulatory and structural diseases. Method and Results: A Cross-sectional study was conceded out in a center for heart diseases at Al-Nasiriyah city, Thi-Qar governorate, Iraq, from 1 st April to 31 st May 2018. The patients who were diagnosed with heart diseases in the center were administered with a self-structured questionnaire, which explore the risk factors of heart diseases among them. A total of 80 patients (48 male and 32 female) who responded to questionnaire were included. Those who did not respond to the questionnaire were excluded. More than half of the patients (57.5%) were aged ≥ 60 and 37.5% of them were illiterate. About 65% of patients with circulatory heart diseases consumed red meat more than two times a week, however 81% of them consumed it rarely. Also, 40% of heart disease cases do not perform exercise daily. Conclusion: This study reveals that the risk of heart diseases increases with the factors such as increasing age, having fried food, avoiding fruits daily, eating red meat more than 2 times per week, physical inactivity and being a passive smoker.

Type of the article: Research ArticleAbstractThis study examines how patients’ health insurance claims were denied by different insurance providers at a Saudi Academic Medical Center (AMC), exploring the reasons for these rejections, their relationship to claim characteristics, and the factors that predict health insurance claim rejections. A descriptive study design was employed, involving a retrospective review of all insurance claims submitted by both inpatients and outpatients between January and December 2023 at a tertiary care AMC in Saudi Arabia. Following data screening using the UCAF 2.0 form, all denied insurance claims cases (n = 1,117) were subjected to qualitative analysis. The majority of rejected health insurance claims were submitted by female patients (56.9%) and outpatients (93.6%). Among the insurance companies studied, “Tawuniya” rejects the most insurance claims (n = 730). Variables such as age, gender, and insurance company were significantly associated with the reasons for denying claims (p < 0.05). Furthermore, variables such as age, cost, department type (inpatient/outpatient), and the month of claims are significant predictors of claim rejections (p < 0.05). However, gender, insurance companies, and clinical diagnosis were not significant (p > 0.05). The primary reasons for insurance claim denials in Saudi Arabia are missing medical data, system errors, and non-coverage of specific conditions. This study will help insurance companies and patients identify trends and reasons for claim rejections, enabling them to implement more effective preventive and corrective measures.AcknowledgmentsThe authors expressed their gratitude to Imam Abdulrahman Bin Faisal University for granting permission [IRB-2024-03-188] to conduct this study.