A study to create a risk factor models to predict the development of keratoconus among the Saudi Arabian population.

OBJECTIVE: An interaction between hereditary and environmental variables is thought to be the cause of keratoconus, a progressive ectatic corneal condition. The identification of risk factors is necessary since they are currently the subject of intense debate and are crucial to the management and prevention of the disease. The objective of this study is to gain a better understanding of the risk factors associated with the onset and progression of keratoconus. It would be valuable for both eye care professionals and patients in Saudi Arabia. PATIENTS AND METHODS: Patients seeking eye care at Qassim University eye clinic were included in this study. Participants were divided into: cases (with keratoconus) and control (without keratoconus but with other ocular problems). Keratoconus diagnoses of the participants were made by the attending optometrists or ophthalmologists. Multivariate logistic analyses were performed to identify the risk factors for keratoconus. Moreover, by performing logistic regression and CART analysis, supervised learning algorithms were developed to predict the likelihood of keratoconus based on the risk factors. RESULTS: There were 75 keratoconus patients and 75 control. The CART model to predict the chances of keratoconus occurrence has an accuracy of 73%. Our prediction model can be a baseline model for future risk factor analysis studies that will be done in the Middle Eastern region. The models can be better trained by refining the risk factor quality and also by increasing the keratoconus population in the study. Including clinical parameters in the prediction models would result in complex as well as models with better prediction accuracy. CONCLUSIONS: Clinical ocular parameters including the corneal topographic variables have to be obtained to better correlate the risk factors with specific changes or the subtypes of the keratoconus. Complex diseases like keratoconus require machine learning models apart from statistical analysis for association and causation. Machine learning models would not only predict the disease but also provide insight into how the risk factors interact with each other.

Morphological evaluation of the incisive canal with reference to gender and age: A cone-beam computed tomography study.

BACKGROUND: The incisive canal (IC) is an important anatomical structure in the premaxilla that should be considered during many dental procedures. AIMS: The objective of this study is to associate the IC morphology and dimensions with reference to gender and age by means of cone-beam computed tomography (CBCT). PATIENTS AND METHODS: A retrospective study was conducted using archived CBCT records of patients who sought treatment at the Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. OnDemand 3D Imaging software was utilized in image reconstruction and measurement determination. The parameters evaluated were the IC shape and dimensions in a sagittal and coronal view at two levels: palatal opening and nasal opening. The variables were compared according to age and gender using one-way Analysis of Variance (ANOVA) and Kruskal Wallis tests. Confidence level was obtained at P < 0.05. RESULTS: Out of the 370 CBCT images assessed, only 100 images fulfilled the inclusion criteria; 50 males and 50 females. No substantial variance in IC shapes was found in both the sagittal and coronal perspectives with reference to age and gender. Likewise, there was no statistical variation in IC dimensions with reference to age. On the other hand, there was a statistical difference in IC length when correlated with gender as the male subjects had longer IC as compared to females (P < 0.01). CONCLUSION: There is no association between IC morphology, age and gender. However, substantial variation in IC length was observed between genders.

Melioidosis: Case reports of confirmed Burkholderia pseudomallei in Saudi Arabia.

Melioidosis is an infectious disease of tropical climates. The disease is caused by the bacterium Burkholderia pseudomallei. Most cases are diagnosed in southeast Asia and northern Australia. Some imported cases diagnosed in returning tourists, soldiers, and immigrants from endemic areas. It caught much attention since the Centers for Disease Control and Prevention (CDC) designated B. pseudomallei as an agent for biological warfare and terrorism. We describe two cases of a 26-year-old Saudi woman who had fulminant sepsis soon after returning from Thailand & a 48-year-old woman with a long history of fever. B. pseudomallei was isolated from both patients blood cultures, and they had different consequences. A confirmed case of melioidosis was not reported before in Saudi Arabia.