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In this study, a nested grouped random parameter negative binomial framework is proposed to model crash counts at the segment level, a three-level longitudinal framework. The proposed model accounts for correlations along county routes and over time and thus includes a time variable, the year index, to analyze crash counts. The model is applied to crashes on undivided two-lane arterial roads in Ohio from 2012 to 2017. The results present two variants of the model: one with varying intercepts and fixed slopes and the other with varying intercepts and slopes. Both variants have comparable interpretations concerning the fixed parameters, but the latter variant exhibits a significantly improved fit and provides additional information on the interpretations. The results show a significant quadratic relationship between the time variable and the crash count, indicating that, on average, the crash count of segments increases with a decreasing rate as time variable increases. Regarding random parameters, the findings show that 17% of segments within routes and 2% of routes exhibit crash counts that decrease at accelerating downward trend as time variable increases. The effect of the natural logarithm of the segment length varies significantly across different routes, with an increase in this value primarily leading to an increase in crashes. On the other hand, the effect of the total shoulder width also varies across routes, but unlike the former, an increase in this value generally results in a decrease in crashes. The proposed model shows high forecast accuracy for crash count prediction, making it a valuable tool for informed decision-making in safety improvement.
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INTRODUCTION: Osteoporosis is a major clinical problem that affects the whole population, especially women. It is a condition that is becoming more prevalent with aging. The increase in bone fragility associated with the disease can lead to fractures, even from minor trauma. Our goal is to evaluate the extent of knowledge about osteoporosis and perceptions of it among premenopausal women in Saudi Arabia. METHOD: This descriptive cross-sectional study was conducted among premenopausal women during the months of June and July 2021. We distributed an online questionnaire on social networking sites and applications that Saudi women use on a daily basis. We used the Osteoporosis Knowledge Assessment Tool (OKAT) to evaluate the responses. RESULT: A total of 661 women took part in our study; 159 of them were excluded because they had either reached the menopausal period or had already been diagnosed with the disease. The overall perception of osteoporosis is noticeably poor, as only 55% of respondents had an acceptable level of knowledge. In addition, we found a statistically significant association between education level and knowledge level (p-value = 0.044). CONCLUSION: The findings revealed that more than half the participants scored "acceptable" in terms of their understanding of the disease, which indicates a serious awareness gap. This outcome demonstrates the necessity of increasing community awareness about osteoporosis to reduce potential harm and the financial burden of healthcare.
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Objective Gestational diabetes mellitus (GDM) can occur during pregnancy. One of the leading causes of it is a hormone produced by the placenta that interferes with glucose absorption and causes glucose buildup in the bloodstream. Genetic variations between ethnicities are believed to be associated with GDM, and there has been some research on the association of ABO blood group with GDM in different populations. However, the results so far are inconsistent, and there is no conclusive evidence on how ABO blood group affects the occurrence of GDM. This study aims to examine the link between ABO blood group and GDM in pregnant women at King Abdulaziz University Hospital. Methodology A retrospective cohort study was conducted on a group of GDM patients between 2019 and 2022 using data collected from the patients' medical records at King Abdulaziz University Hospital. Results The overall prevalence of GDM was high at 74.7%, and the percentage of patients with A, O, B, and AB blood group who had GDM was 42.9%, 41.41%, 12.1%, and 3.59%, respectively. However, there was no significant difference in Rh status or any other clinical characteristic between the participants who had GDM and those who did not have GDM. Conclusion The present findings indicate that blood group is not associated with the development of GDM in this cohort from Saudi Arabia. However, more studies are required in the future to corroborate these findings.
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Background: Acute kidney injury (AKI) is associated with an increase in patient mortality and high rates of renal/non-renal complications. Late detection of the disease has been associated with worse prognosis, but no such study has been conducted from Saudi Arabia. Objectives: To assess the impact of early nephrology referral on the outcomes of patients with AKI. Methods: This retrospective record review included all adult patients (≥18 years) with AKI who were referred to the Nephrology Department at King Abdulaziz University Hospital, Jeddah, Saudi Arabia, between May 2019 and July 2020. AKI was defined according to the Kidney Disease Improving Global Outcomes criteria. AKI patients evaluated by nephrologists were stratified into early referral group (i.e., referral in <48 h from the first detection of AKI) and late referral group (referral ≥48 h after the first detection of AKI). Results: A total of 400 patients met the inclusion criteria, of which 264 (66%) were early referrals. A significant association was found between delayed referral and mortality rates and length of hospital stay (for both,P= 0.001). Late referral was also significantly associated with increased likeliness of the need for renal replacement therapy (P = 0.037) and sepsis (P = 0.005). Conclusions: The outcomes were worse for patients with AKI receiving late referrals to nephrologists. Raising the awareness of AKI among non-nephrologists would likely increase the proportion of earlier referrals.
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In this study, the dilemma zone types and lengths were studied according to their definitions based on Gazis, Herman, and Maradudin (GMH) and the probability-of-stopping models, and the link of the two models to each other was explored. Moreover, the effects of the joint and separate use of the speed/red-light camera (SRLC) and the traffic signal countdown timer (TSCT) on dilemma zone determination and safety were investigated. Multiple linear regression was conducted to define the minimum stopping and maximum passing distance boundaries, and binary logistic regression was conducted to define the boundary of dilemma zone type II based on the probability of stopping. The results show that SRLC significantly shifts the dilemma zone downstream and increases the probability of stopping by 11 %. TSCT was found not to have any significant effect on the dilemma zone, but it was found to increase the approaching speeds. It was also found that dilemma zone type II can capture all the dilemma zone types to a great extent.
