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Background: Kaposi Sarcoma (KS) is a rare low‐grade vascular neoplasm that is associated with Human herpesvirus 8 (HHV‐8). KS commonly affects HIV or immunocompromised patients. However, classical KS can be present even in the absence of these factors. In this case report, we describe a case of KS in an 83‐year‐old, HIV‐negative Saudi male who was misdiagnosed for two years. Case Presentation: The patient presented with right foot pain and swelling with two large masses. The patient was initially diagnosed with stasis dermatitis and chronic venous ulcer due to venous insufficiency and treated with endovenous thermal ablation. However, the patient’s symptoms did not resolve, and he experienced several episodes of cellulitis that required multiple hospital admissions over a 2‐year period. When the patient presented to our center, a biopsy was taken from the lesion, and it confirmed the diagnosis of KS. Conclusion: KS or other underlying etiologies should be suspected in cases of recurrent unresolved infections, particularly in older patients. A high index of suspicion and a low threshold for biopsy are recommended to prevent missed or delayed diagnoses, which could ultimately lead to the worst prognosis.

Objectives: To investigate the referral practices across different medical specialties and identify possible barriers to hand surgery referral. Rheumatoid hand deformities (RHDs) and thumb carpometacarpal (CMC) arthritis may require surgery once deformities occur. However, in Saudi Arabia, the rate of referrals to hand surgeons remains low. Methods: This was a cross-sectional study that included 102 consultants of family medicine, rheumatology, and orthopedics across various regions of Saudi Arabia. A total of 30 institutions were contacted and requested to distribute a survey questionnaire to their physicians; these institutions included 8 private hospitals, 16 government hospitals, and 6 primary healthcare centers. The survey included questions on the incidence, rate, management, knowledge, and referral of patients with RHD and CMC arthritis using a 5-point Likert scale. The Kruskal-Wallis H test was utilized in our analysis to evaluate the differences in responses among the 3 specialties. Results: For RHD and thumb CMC arthritis, the referral rate was higher among orthopedic surgeons compared to rheumatologists and family medicine physicians. The main barriers to referral were patient refusal, medical treatment alone being deemed adequate, and a lack of awareness of surgical options for management. Conclusion: Our findings highlight discrepancies in patterns of physician referral of RHD and thumb CMC arthritis cases to hand surgeons, indicating the need for targeted interventions to improve referral rates and enhance patient outcomes. Keywords: rheumatoid arthritis, hand deformities, carpometacarpal joint, thumb; arthritis, Saudi Arabia, referral and consultation, physician practice patterns

BackgroundAdverse childhood experiences (ACEs) are traumatic events that occur before 18 years of age. ACEs have been associated with many negative health problems, including the development of chronic diseases, such as irritable bowel syndrome (IBS), a functional gastrointestinal disorder characterized by abdominal pain. We investigated the prevalence of ACEs among patients with IBS, identified the types of ACEs commonly related to patients with IBS, and further assessed the impact of ACEs on IBS severity.MethodologyA cross-sectional study was performed. The study targeted patients with IBS aged ≥ 18 years who were recruited from gastroenterology outpatient clinics at King Abdulaziz University Hospital. Adults were contacted and invited to take part in the study by completing a survey. Data were collected using two validated questionnaires, the ACE questionnaire for adults and the IBS symptom severity scoring system.ResultsThe study included 109 patients with IBS (59.6% females). The prevalence of ACEs (patients with IBS exposed to at least one ACE) was 63.3%. The most prevalent type was emotional abuse (34.9%), followed by both physical abuse and emotional neglect (28.4%). Females reported significantly more ACEs (p = 0.035) than males. The overall IBS symptoms (r = 0.195, p = 0.043) and abdominal pain (r = 0.240, p = 0.012) severity were significantly correlated with total ACEs score.ConclusionsOur findings point to a probable association between ACEs exposure and IBS, demonstrating their long-term impacts on symptoms severity. Further studies are needed to acquire a better understanding of the potential impact of ACEs on IBS.

Appendectomy is the preferred treatment for acute uncomplicated appendicitis and the most common emergency abdominal surgery. While previous studies have investigated variables affecting post-appendectomy complications, local research is limited, and data on complication rates are scarce. Therefore, this study aimed to investigate appendectomy outcomes and the factors influencing them. This retrospective record review included all patients who underwent appendectomies at our center between 2013 and 2023, excluding those who underwent appendectomies as part of other procedures. Data were retrieved from the hospital database and recorded on predesigned Google Forms. A total of 556 patients were included. Complications occurred in 60 patients (10.8%); the most common included intra-abdominal collections (n=19, 3.4%), postoperative fever (n=13, 2.3%), and surgical site infections (n=11, 2.0%). The most frequently documented histopathological diagnoses included acute appendicitis (n=402, 72.3%), perforated appendicitis (n=109, 19.6%), and gangrenous appendicitis (n=19, 4.4%). Surgical site infection rates were higher after open appendectomies (6.0% vs. 0.9%, P=0.006), while intra-abdominal collections were more frequent after laparoscopic appendectomies (4.1% vs. 0.0%, P=0.095). Additionally, histopathology results showing complicated or chronic appendicitis were associated with higher complication rates (P<0.001, odds ratio=3.793, 95% confidence interval=1.957-7.350). To the best of our knowledge, this is the largest retrospective review of appendectomy cases in Saudi Arabia. However, this study was conducted in a tertiary care center, which may have caused the rates of complications to appear lower than those in primary centers. We recommend a multi-center study be conducted to establish more accurate results.

Diabetes mellitus (DM), including type 1 diabetes (T1D) and type 2 diabetes (T2D), affects the absorption of glucose from the blood. DM has serious complications that can be prevented by adequate knowledge of the disease and its complications, a healthy lifestyle, a modified diet, and regular glucose monitoring. Hence, this study aimed to assess the effects of frequent glucose monitoring on the occurrence of DM complications. This cross-sectional study was performed at King Abdulaziz University Hospital between June and December 2022 and included patients with T1D or T2D. After consent, participants who agreed to join filled out an online questionnaire that was used to acquire information, such as demographic data, type of diabetes, blood glucose monitoring, and diabetic complications. A total of 206 diabetic patients participated in this study, with a mean age of 41.2±19.37, with 53.4% having T1D. Most participants monitored their glucose levels (85.4%), and the majority (65.3%) monitored them once or more daily. Patients who monitored their glucose levels more frequently had significantly fewer complications (p = 0.002). Continuous glucose monitoring (CGM) was the best monitoring method, as it demonstrated the lowest rate of complications compared to other methods (p = 0.002). Frequent glucose monitoring and the use of CGM devices were associated with a decreased number of DM complications. Thus, we recommend that physicians encourage patients to perform CGM as it helps increase the frequency of monitoring.

Introduction Despite Saudi Arabia's' free healthcare system, breast cancer (BC) has a major impact on affected individuals. Previous studies have shown that socioeconomic variables could contribute to inequities in receiving treatment. Although early detection and treatment are essential, delays are frequently influenced by either insurance status or other socioeconomic variables. Assessing characteristics that influence the duration of BC treatment for Saudi women will aid in improving health equity and lowering system costs. Methods This was a cross-sectional study that included all female patients who were diagnosed with BC between 2016 and 2023 at a tertiary care center. All patients were contacted by phone calls to fill out a questionnaire. Results A total of 113 females were included; the mean age at the time of diagnosis with BC was 48.88±10.97 years, and the majority were Saudis (58.4%). Additionally, the median duration for treatment initiation was 28 (15.50-45.50) days from the date of diagnosis. Factors influencing the time for initiating the treatment included nationality, as non-Saudis took longer to receive their treatment (27.00 (13.00-39.25) days vs. 30.00 (18.00-59.00) days, p = 0.176). Moreover, patients living further from the hospital demonstrated a delay in receiving treatment compared to those living near the hospital. However, the relation was not statistically significant. Conclusion Our study investigated the demographic disparities among BC patients. Our results showed that some variables contributed to a delay in treatment initiation, including nationality and distance from the hospital, which suggest further areas for investigation. We recommend further studies be conducted with a larger sample size to improve accessibility and reduce treatment delays for BC patients.

Triage systems play a vital role in effectively prioritizing patients according to the seriousness of their condition. However, conventional emergency triage systems in pediatric care predominantly rely on subjective evaluations. Machine learning technologies have shown significant potential in various medical fields, including pediatric emergency medicine. Therefore, this study seeks to employ pediatric emergency department records to train machine learning algorithms and evaluate their effectiveness and outcomes in the triaging system. This model will improve accuracy in pediatric emergency triage by categorizing cases into three urgency levels (nonurgent, urgent, and emergency). This is a retrospective observational cohort study that used emergency patient records obtained from the Emergency Department at King Faisal Specialist Hospital & Research Centre. Using the emergency severity index (a scale of 1 to 5), various machine learning techniques were employed to build different machine learning models, such as regression, instance-based, regularization, tree-based, Bayesian, dimensionality reduction, and ensemble algorithms. The accuracy of these models was compared to reach the most accurate and precise model. A total of 38,891 pediatric emergency patient records were collected. However, due to numerous outliers and incorrectly labeled data, clinical knowledge and a confident learning algorithm were employed to preprocess the dataset, leaving 18,237 patient records. Notably, ensemble algorithms surpassed other models in all evaluation metrics, with CatBoost achieving an F-1 score of 90%. Importantly, the model never misclassified an urgent patient as nonurgent or vice versa. The study successfully created a machine learning model to classify pediatric emergency department patients into three urgency levels. The model, tailored to the specific needs of pediatric patients, shows promise in improving triage accuracy and patient care in pediatric emergency departments. The implication of this model in the real-life sitting will increase the accuracy of the pediatric emergency triage and will reduce the possibilities of over or under triaging.

This retrospective study addresses the intersection of Down syndrome (DS) and congenital heart defects (CHD), including the prevalence and characteristics of CHD in trisomy 21 patients at a secondary hospital in the Eastern Province of Saudi Arabia. The study investigated the electronic medical records retrieved from the Qatif Central Hospital database, specifically targeting individuals diagnosed with DS (identified by the International Classification of Diseases, Tenth Revision (ICD-10) code Q90.9) between March 2012 and March 2022. The primary aim was to detect cardiac anomalies diagnosed via echocardiography performed at the hospital, along with subsequent follow-up assessments and documented patient outcomes. Among the 161 patients reviewed, the study revealed a significant prevalence of diagnosed heart defects through echocardiograms, constituting approximately 72.7%. Notably, patent ductus arteriosus was the most common condition, found in 29.81% of cases, followed by atrial septal defect (27.95%) and atrioventricular septal defect (17.39%). Among the study participants, 22.98% required surgical intervention. Unfortunately, mortality impacted 32.3% of individuals, while the majority (60.87%) remained alive. In addition, a small percentage (6.83%) discontinued follow-up within our center. This study contributes significant data on cardiac anomalies in DS patients in Saudi Arabia, highlighting a high prevalence of CHD with specific patterns of anomalies. The need for early diagnosis, timely surgical intervention, and ongoing management is evident. These findings provide a foundation for improving clinical practices and shaping public health policies tailored to the needs of this population in Saudi Arabia and similar regions.

Background Thyroid cancer is the most common endocrine malignancy. Previous research has linked the ABO blood group system to the risk and progression of different types of cancer. However, the association between specific blood groups and thyroid cancer risk and disease aggressiveness remains unclear. In this study, we aimed to investigate the relationship between ABO blood groups, thyroid cancer risk, aggressiveness, and metastasis risk. Methods All adult patients who underwent thyroidectomy in our centre between January 2012 and January 2021 were included. A total of 569 files were reviewed, and a total sample of 435 patients were matched after excluding patients with missing data. All sociodemographic, ABO blood groups, Rh factor, and histopathology records were accessed in the study. Result Out of 435 patients, the majority had malignant thyroid diseases (69.9%). Papillary thyroid cancer was the most common (82.0%). Positive lymph nodes were found in 25% of patients, with blood type B having the highest rate (26.7%). Blood type AB had significantly higher rates of vascular invasion than all other blood types (40% vs. 16.3%; p  = 0.03). Blood type AB was also associated with follicular subtype (20%), larger tumour size, higher capsular invasion (33.3%), and distant metastasis (6.7%). Meanwhile, blood type O had the lowest rates of both lymph node invasion and capsular invasion. Benign disease was significantly associated with hypothyroidism ( p  < 0.001). Additionally, thyroiditis (31.8%) and Hashimoto’s (18.2%) were more common in blood Group B. Conclusion Blood type AB had the highest rates of capsular invasion, vascular invasion, and distant metastasis compared to other blood types, indicating its potential aggressiveness. On the other hand, blood type O could be less aggressive than other blood groups.

Melanoma is a fatal type of skin cancer; the fury spread results in a high fatality rate when the malignancy is not treated at an initial stage. The patients’ lives can be saved by accurately detecting skin cancer at an initial stage. A quick and precise diagnosis might help increase the patient’s survival rate. It necessitates the development of a computer-assisted diagnostic support system. This research proposes a novel deep transfer learning model for melanoma classification using MobileNetV2. The MobileNetV2 is a deep convolutional neural network that classifies the sample skin lesions as malignant or benign. The performance of the proposed deep learning model is evaluated using the ISIC 2020 dataset. The dataset contains less than 2% malignant samples, raising the class imbalance. Various data augmentation techniques were applied to tackle the class imbalance issue and add diversity to the dataset. The experimental results demonstrate that the proposed deep learning technique outperforms state-of-the-art deep learning techniques in terms of accuracy and computational cost.