Efficacy and Safety of Injectable Dulaglutide 1.5 mg Among Type 2 Diabetes Patients in Clinics at King Saud Medical City, Riyadh, Saudi Arabia.

INTRODUCTION: Type 2 diabetes mellitus is the most common type of diabetes, characterized by varying degrees of insulin resistance and diminishing beta-cell function, which increases the risk of macrovascular and microvascular complications. Dulaglutide is a long-acting glucagon-like peptide-1 receptor agonist that is administered once weekly and approved for treating adults with type 2 diabetes mellitus. It can be used as a monotherapy or in addition to oral hypoglycemic or insulin therapy. AIM: This study aims to provide information contributing to assessing the efficacy and safety of weekly 1.5 mg dulaglutide therapy in Saudi adult patients with type 2 diabetes mellitus. METHODS: A retrospective single-arm cohort study using a purposive sample to recruit type 2 diabetes mellitus patients on dulaglutide from endocrine and diabetic outpatient clinics in King Saud Medical City (N = 205). Data were collected from participants' medical profiles and through the phone using interview questionnaires. RESULTS: Most participants were female and married; approximately 33% had had diabetes for more than 20 years, 41.4% of the sample had third-class obesity, and more than half had used dulaglutide for the last 1-2 years. With therapy, weight, body mass index, hemoglobin A1c, and fasting blood sugar were significantly improved after 6 and 12 months from baseline. The main side effects reported were nausea (52%) and fatigue (28%). CONCLUSION: Dulaglutide is a safe and effective therapy that demonstrated favorable glycemic control and weight reduction in obese type 2 diabetes patients of Saudi origin.

Prevalence and Risk Factors of Voice Disorders Among Teachers in Saudi Arabia.

Introduction Voice is a crucial tool for communication, and voice problems are more likely to occur in professionals who frequently use their voice for work. Teachers, whose profession requires sustained vocal use, are particularly susceptible to occupation-related voice disorders. This study aimed to quantify the prevalence of voice disorders among teachers in Saudi Arabia, with the general population serving as a control group, and to identify associated risk factors. Methods A cross-sectional study was conducted utilizing an online self-administered questionnaire, which was completed by both teachers and the general population in Saudi Arabia. The latter group acted as a control. The questionnaire included sections on sociodemographic data, teaching patterns, symptoms of voice issues, and the Voice Handicap Index-10 (VHI-10) for assessing voice disorders among participants. Results The study included 640 participants, with 438 (68.4%) being teachers, the majority of whom were females (N = 406; 63.4%). The most common voice-related symptoms reported by teachers were hoarseness (N = 210; 37.9%) and dry throat (N = 147; 26.9%). Voice disorders, as determined by the VHI, affected 355 (55.5%) of the teachers. A high VHI score was associated with a diagnosis of voice disorders and GERD. There was no significant difference in the VHI scores between teachers and the general population (p > 0.05). Conclusion Teachers in Saudi Arabia exhibited a higher prevalence of voice disorders compared to the general population. Risk factors, such as smoking, longer teaching experience, and more teaching hours per week, were more common among teachers with voice disorders. Further investigative studies are warranted to elucidate the causal relationships between these variables and voice disorders.

A Case Report of a Large Splenic Cyst in a Pediatric Patient.

Splenic cysts in the pediatric population are rare but can present with a range of clinical manifestations. Acute abdominal pain, although uncommon, is a significant presentation that requires prompt evaluation and management. We present the case of an 11-year-old female who presented to the emergency department with severe left upper quadrant abdominal pain of 24 hours' duration. Physical examination revealed tenderness and guarding in the left upper quadrant with a palpable, firm mass. Elevated serum amylase and lipase levels initially raised suspicion of a pancreatic etiology, but further investigations confirmed the presence of a large cystic lesion in the spleen. The patient underwent laparoscopic splenectomy, and the resected specimen confirmed a benign splenic cyst. Postoperatively, she recovered uneventfully and was discharged with appropriate follow-up plans. This case report underscores the importance of early recognition and prompt surgical intervention in managing splenic cysts in pediatric patients. The diverse etiologies and pathophysiological mechanisms of splenic cysts necessitate a comprehensive diagnostic approach.

Nano-Emulsion Based Gel for Topical Delivery of an Anti-Inflammatory Drug: In vitro and in vivo Evaluation.

Introduction: Arthritic disorder is a common disease in elderly patients and the most common cause of joint dysfunction. This study aims to design Piroxicam-loaded nanoemulsion (PXM-NE) formulations to enhance the analgesic and anti-inflammatory activity of the drug for topical use. Methods: The nanoemulsion preparations were designed based on a high-pressure homogenization technique and were characterized for particle size (PS), poly dispersity index (Pi), zeta potential (ZP), drug content, and the selected formula was investigated for its topical analgesic activity and pharmacokinetic parameters. Results: The characterizations showed that the PS was 310.20±19.84 nm, Pi was 0.15±0.02, and ZP was -15.74±1.6 mV for the selected formula. A morphology study showed that the PXM-NE droplets were spherical with a uniform size distribution. The in vitro release study showed a biphasic release pattern with a rapid release within the first 2 hours followed by a sustained release pattern. The analgesic activity for optimal formula was 1.66 times higher than the commercial gel with a double duration of analgesic activity. The Cmax was 45.73±9.95 and 28.48±6.44 ng/mL for the gel form of the selected formula and the commercial gel respectively. The relevant bioavailability of the selected formula was 2.41 higher than the commercial gel. Conclusion: The results showed good physicochemical properties, higher bioavailability, and a longer analgesic effect of PXM from nanoemulsion gel, as compared to the commercial product.

Awareness of Oral Cancer Among Users of Smokeless Tobacco: A Cross-Sectional Study.

INTRODUCTION:  Smokeless tobacco (SLT) stands out for its higher nicotine absorption and its role in preventable fatalities. The Global Adult Tobacco survey in Saudi Arabia revealed SLT usage, while past legislation restricted its use. Linking SLT consumption to oral cancer and oral mucosal ulcers, the study addresses its prevalence in head and neck malignancies. METHODOLOGY: This study is cross-sectional and includes adult users of SLT. Raosoft (Raosoft Inc., Seattle, WA) was used to calculate the sample size. The data was analyzed using SPSS software (IBM Corp., Armonk, NY). RESULTS: The research study investigated various sociodemographic characteristics and prevalence of SLT use among participants. All participants reported using SLT, with toombak (33.2%) and shamma (36.0%) being the most prevalent. Notably, reasons for initiating SLT included influence from peer pressure (33.6%), alternatives to smoking (32.0%), and influence from relatives (19.0%). While 75.1% intended to quit within a year, awareness of SLT's harmfulness varied: 40.3% believed it was less harmful than smoking, and 57.7% recognized its link to oral cancer. Additionally, 62.2% believed SLT could lead to dependence. Sociodemographic factors generally did not significantly affect awareness of SLT causing oral cancer. CONCLUSION: The findings indicate a significant prevalence of SLT use, with toombak and shamma being the most common types consumed. Awareness of the potential harm of SLT use in relation to oral cancer varied among participants, with a notable proportion misunderstanding its harmfulness compared to smoking tobacco.

Impacts of Image Obfuscation on Fine-grained Activity Recognition in Egocentric Video.

Automated detection and validation of fine-grained human activities from egocentric vision has gained increased attention in recent years due to the rich information afforded by RGB images. However, it is not easy to discern how much rich information is necessary to detect the activity of interest reliably. Localization of hands and objects in the image has proven helpful to distinguishing between hand-related fine-grained activities. This paper describes the design of a hand-object-based mask obfuscation method (HOBM) and assesses its effect on automated recognition of fine-grained human activities. HOBM masks all pixels other than the hand and object in-hand, improving the protection of personal user information (PUI). We test a deep learning model trained with and without obfuscation using a public egocentric activity dataset with 86 class labels and achieve almost similar classification accuracies (2% decrease with obfuscation). Our findings show that it is possible to protect PUI at smaller image utility costs (loss of accuracy).

Detecting Screen Presence with Activity-Oriented RGB Camera in Egocentric Videos.

Screen time is associated with several health risk behaviors including mindless eating, sedentary behavior, and decreased academic performance. Screen time behavior is traditionally assessed with self-report measures, which are known to be burdensome, inaccurate, and imprecise. Recent methods to automatically detect screen time are geared more towards detecting television screens from wearable cameras that record high-resolution video. Activity-oriented wearable cameras (i.e., cameras oriented towards the wearer with a fisheye lens) have recently been designed and shown to reduce privacy concerns, yet pose a greater challenge in capturing screens due to their orientation and fewer pixels on target. Methods that detect screens from low-power, low-resolution wearable camera video are needed given the increased adoption of such devices in longitudinal studies. We propose a method that leverages deep learning algorithms and lower-resolution images from an activity-oriented camera to detect screen presence from multiple types of screens with high variability of pixel on target (e.g., near and far TV, smartphones, laptops, and tablets). We test our system in a real-world study comprising 10 individuals, 80 hours of data, and 1.2 million low-resolution RGB frames. Our results outperform existing state-of-the-art video screen detection methods yielding an F1-score of 81%. This paper demonstrates the potential for detecting screen-watching behavior in longitudinal studies using activity-oriented cameras, paving the way for a nuanced understanding of screen time's relationship with health risk behaviors.

ActiSight: Wearer Foreground Extraction Using a Practical RGB-Thermal Wearable.

Wearable cameras provide an informative view of wearer activities, context, and interactions. Video obtained from wearable cameras is useful for life-logging, human activity recognition, visual confirmation, and other tasks widely utilized in mobile computing today. Extracting foreground information related to the wearer and separating irrelevant background pixels is the fundamental operation underlying these tasks. However, current wearer foreground extraction methods that depend on image data alone are slow, energy-inefficient, and even inaccurate in some cases, making many tasks-like activity recognition- challenging to implement in the absence of significant computational resources. To fill this gap, we built ActiSight, a wearable RGB-Thermal video camera that uses thermal information to make wearer segmentation practical for body-worn video. Using ActiSight, we collected a total of 59 hours of video from 6 participants, capturing a wide variety of activities in a natural setting. We show that wearer foreground extracted with ActiSight achieves a high dice similarity score while significantly lowering execution time and energy cost when compared with an RGB-only approach.

A novel therapeutic approach for reducing postoperative inflammatory complications after impacted mandibular third molar removal.

BACKGROUND: This study was designed to compare effect of combined use of dexamethasone and honey versus each agent alone in controlling complications associated with removal of impacted mandibular third molar. METHODS: This randomized clinical study included patients suffering from impacted mandibular wisdom teeth. Patients were divided randomly into 4 groups. Group I, control, group II, received dexamethasone injection preoperatively, group III, received honey locally in the wound after extraction, and group IV, received dexamethasone injection preoperatively and topical honey application. All patients were evaluated preoperatively and postoperatively to assess facial edema, interincisal distance, pain, and total analgesic dose used. RESULTS: Significant edema developed in group I than other groups and improved significantly in group II and III on seventh postoperative day, and tenth postoperative day in group I. Insignificant edema developed in group IV. Significant decrease in interincisal distance occurred in all groups on third postoperative day that improved significantly on seventh postoperative days in all groups except group I, it improved on tenth postoperative day. Pain was significantly minimum in group IV than other groups and its maximum degree was in group I. CONCLUSION: Both dexamethasone and honey are an effective way of minimizing swelling, pain, and trismus after removal of impacted lower third molars. Both agents either alone or in combination provide simple, safe, painless, and cost-effective method to eliminate postoperative discomfort. However, dexamethasone or honey can decrease complications related to surgical extraction of mandibular third molar, the simultaneous application of both agents is more effective method in this regard.

Multiclass Classification for Detection of COVID-19 Infection in Chest X-Rays Using CNN.

Coronavirus took the world by surprise and caused a lot of trouble in all the important fields in life. The complexity of dealing with coronavirus lies in the fact that it is highly infectious and is a novel virus which is hard to detect with exact precision. The typical detection method for COVID-19 infection is the RT-PCR but it is a rather expensive method which is also invasive and has a high margin of error. Radiographies are a good alternative for COVID-19 detection given the experience of the radiologist and his learning capabilities. To make an accurate detection from chest X-Rays, deep learning technologies can be involved to analyze the radiographs, learn distinctive patterns of coronavirus' presence, find these patterns in the tested radiograph, and determine whether the sample is actually COVID-19 positive or negative. In this study, we propose a model based on deep learning technology using Convolutional Neural Networks and training it on a dataset containing a total of over 35,000 chest X-Ray images, nearly 16,000 for COVID-19 positive images, 15,000 for normal images, and 5,000 for pneumonia-positive images. The model's performance was assessed in terms of accuracy, precision, recall, and F1-score, and it achieved 99% accuracy, 0.98 precision, 1.02 recall, and 99.0% F1-score, thus outperforming other deep learning models from other studies.

SmokeMon: Unobtrusive Extraction of Smoking Topography Using Wearable Energy-Efficient Thermal.

Smoking is the leading cause of preventable death worldwide. Cigarette smoke includes thousands of chemicals that are harmful and cause tobacco-related diseases. To date, the causality between human exposure to specific compounds and the harmful effects is unknown. A first step in closing the gap in knowledge has been measuring smoking topography, or how the smoker smokes the cigarette (puffs, puff volume, and duration). However, current gold-standard approaches to smoking topography involve expensive, bulky, and obtrusive sensor devices, creating unnatural smoking behavior and preventing their potential for real-time interventions in the wild. Although motion-based wearable sensors and their corresponding machine-learned models have shown promise in unobtrusively tracking smoking gestures, they are notorious for confounding smoking with other similar hand-to-mouth gestures such as eating and drinking. In this paper, we present SmokeMon, a chest-worn thermal-sensing wearable system that can capture spatial, temporal, and thermal information around the wearer and cigarette all day to unobtrusively and passively detect smoking events. We also developed a deep learning-based framework to extract puffs and smoking topography. We evaluate SmokeMon in both controlled and free-living experiments with a total of 19 participants, more than 110 hours of data, and 115 smoking sessions achieving an F1-score of 0.9 for puff detection in the laboratory and 0.8 in the wild. By providing SmokeMon as an open platform, we provide measurement of smoking topography in free-living settings to enable testing of smoking topography in the real world, with potential to facilitate timely smoking cessation interventions.

Differences in knowledge about contraception among Saudi males and females at tertiary hospitals in Riyadh.

CONTEXT: Family planning is a voluntary practice that individuals engage in to control the number of children for promoting the health and development of countries. The aim is to evaluate the level of contraceptive knowledge in Saudi males and females in Riyadh at King Abdul-Aziz Medical City (KAMC) and King Abdullah Specialist Children's Hospital (KASCH). METHODS: A cross-sectional questionnaire-based study conducted among educated, under educated, single, married Saudi males and females (n = 385), and aged (20 to 65) years old. Healthcare providers and participants underwent permanent sterilization were excluded. RESULTS: Approximately half of the participants were aware about contraceptive methods. More males (n = 132, 70%) were significantly aware compared to females (n = 110, 56%) (P-value <0.001). The most commonly used contraceptive methods were oral contraceptive pills, male condom, and intrauterine device (69%, 34%, 22%, respectively). A significant difference was noted for the used and preferred contraceptive method, which was condom for male and oral contraceptive pills in female (P-value < 0.001). Healthcare provider was the main source of information and women significantly consult healthcare provider more than men 47% vs 32%, (χ2 = 9.23, P value = 0.002). Side effects were reported as a main reason for discontinuation 61% (n = 120) of females and 52% (n = 98) in males, respectively. Logistic regression indicated a significant association of contraceptive knowledge with age and parity. CONCLUSIONS: Regardless of educational level, high levels of awareness were identified in both genders. Oral contraceptive pills were reported as the most used, safest, and preferred method.

To Mask or Not to Mask? Balancing Privacy with Visual Confirmation Utility in Activity-Oriented Wearable Cameras.

Activity-oriented cameras are increasingly being used to provide visual confirmation of specific hand-related activities in real-world settings. However, recent studies have shown that bystander privacy concerns limit participant willingness to wear a camera. Researchers have investigated different image obfuscation methods as an approach to enhance bystander privacy; however, these methods may have varying effects on the visual confirmation utility of the image, which we define as the ability of a human viewer to interpret the activity of the wearer in the image. Visual confirmation utility is needed to annotate and validate hand-related activities for several behavioral-based applications, particularly in cases where a human in the loop method is needed to label (e.g., annotating gestures that cannot be automatically detected yet). We propose a new type of obfuscation, activity-oriented partial obfuscation, as a methodological contribution to researchers interested in obtaining visual confirmation of hand-related activities in the wild. We tested the effects of this approach by collecting ten diverse and realistic video scenarios that involved the wearer performing hand-related activities while bystanders performed activities that could be of concern if recorded. Then we conducted an online experiment with 367 participants to evaluate the effect of varying degrees of obfuscation on bystander privacy and visual confirmation utility. Our results show that activity-oriented partial obfuscation (1) maintains visual confirmation of the wearer's hand-related activity, especially when an object is present in the hand, and even when extreme filters are applied, while (2) significantly reducing bystander concerns and enhancing bystander privacy. Informed by our analysis, we further discuss the impact of the filter method used in activity-oriented partial obfuscation on bystander privacy and concerns.

I Can't Be Myself: Effects of Wearable Cameras on the Capture of Authentic Behavior in the Wild.

Wearable sensors can provide reliable, automated measures of health behaviors in free-living populations. However, validation of these measures is impossible without observable confirmation of behaviors. Participants have expressed discomfort during the use of ego-centric wearable cameras with first-person view. We argue that mounting the camera on different body locations with a different lens orientation, gives a device recording affordance that has the effect of reducing surveillance and social discomfort compared to ego-centric cameras. We call these types of cameras "activity-oriented" because they are designed to capture a particular activity, rather than the field of view of the wearer. We conducted an experiment of three camera designs with 24 participants, collecting qualitative data on participants' experience while wearing these devices in the wild. We provide a model explaining factors that lead to an increase in social presence and social stigma, which, therefore, create social and surveillance discomfort for the wearer. Wearers' attempts to reduce this discomfort by modifying their behavior or abandoning the device threatens the validity of observations of authentic behaviors. We discuss design implications and provide recommendations to help reduce social presence and stigma in order to improve the validity of observations with cameras in the wild.

Is More Always Better?: Discovering Incentivized mHealth Intervention Engagement Related to Health Behavior Trends.

Behavioral medicine is devoting increasing attention to the topic of participant engagement and its role in effective mobile health (mHealth) behavioral interventions. Several definitions of the term "engagement" have been proposed and discussed, especially in the context of digital health behavioral interventions. We consider that engagement refers to specific interaction and use patterns with the mHealth tools such as smartphone applications for intervention, whereas adherence refers to compliance with the directives of the health intervention, independent of the mHealth tools. Through our analysis of participant interaction and self-reported behavioral data in a college student health study with incentives, we demonstrate an example of measuring "effective engagement" as engagement behaviors that can be linked to the goals of the desired intervention. We demonstrate how clustering of one year of weekly health behavior self-reports generate four interpretable clusters related to participants' adherence to the desired health behaviors: healthy and steady, unhealthy and steady, decliners, and improvers. Based on the intervention goals of this study (health promotion and behavioral change), we show that not all app usage metrics are indicative of the desired outcomes that create effective engagement. As such, mHealth intervention design might consider eliciting not just more engagement or use overall, but rather, effective engagement defined by use patterns related to the desired behavioral outcome.

Idiopathic hypoparathyroidism with extensive intracranial calcification in children: First report from Saudi Arabia.

RATIONALE: Pediatric idiopathic hypoparathyroidism with extensive intracranial calcifications outside the basal ganglia (BG) is extremely rare with less than 10 cases worldwide. PATIENT CONCERNS: An 11-year-old Saudi male child presented with tetany with otherwise normal neurological and other body system examination diagnoses severe hypocalcemia for differential diagnosis. INTERVENTIONS: Further investigations revealed hyperphosphatemia and undetectable serum intact parathyroid hormone. Brain computed tomography revealed BG and extensive brain calcifications. He has no dysmorphic features, vitiligo, mucocuataneous manifestations, or hair loss. He had normal hemoglobin, electroencephalogram, and skeletal survey, with negative autoantibodies to alpha and omega interferons and negative genetic testing for Glial Cell Missing 2 (GCM2) and calcium-sensing receptors (CaSRs) excluding known causes of hypoparathyroidism. OUTCOMES: This case presents a rare entity of idiopathic hypoparathyroidism with extensive intracranial calcification, not only in BG but also outside the extrapyramidal system with normal mentality, development, pubertal achievement, and neurological examination. To our knowledge, this is the first report from Saudi Arabia in pediatrics. LESSONS: Idiopathic hypoparathyroidism is a diagnosis of exclusion after ruling out all known causes of hypoparathyroidism. It is associated with BG calcifications, but extensive intracranial calcifications outside the BG are extremely rare.