Background: Frozen shoulder (FS) is a common fibroproliferative condition characterised by pain and mobility loss, often associated with systemic diseases such as diabetes mellitus (DM). This study aims to determine the prevalence of FS amongst diabetic patients in Makkah, Saudi Arabia. Methodology: This study is a web-based, descriptive and cross-sectional study. The data were obtained through an online questionnaire directed at patients with DM in Makkah City, Saudi Arabia. Results: A total of 385 responses were collected, but only 378 met the inclusion criteria. Amongst the participants, 35.7% were 41–50 years old and 53.2% were women. Most of the participants (84.1%) had type 2 DM for 11–15 years and more than half (58.5%) were taking insulin for DM management. Amongst the participants, 9.8% were diagnosed with FS disease, 25.1% reported having difficulty with shoulder movement and 38.1% reported having shoulder pain. Although FS was more prevalent amongst individuals aged 41–50 years, no significant correlation was observed with age or other variables ( P > 0.05). Conversely, difficulty with shoulder movement and shoulder pain were significantly more frequent in patients aged 51–60 years and those with a diabetes duration of over 20 years ( P < 0.05). Conclusion: This study identifies a significant presence of shoulder morbidity amongst diabetic patients in Makkah, particularly those with advanced age and long-term type 2 diabetes. These findings underscore the need for integrating musculoskeletal screening into routine diabetic care to facilitate early intervention. Future research should focus on longitudinal designs and biochemical markers to better understand the progression and predictors of adhesive capsulitis in this high-risk population.

Introduction: Robotic-assisted total knee replacement (RA-TKR) has established a new standard for surgical precision. However, the translation of this mechanical accuracy into consistently superior long-term clinical outcomes remains debated. This has shifted focus toward the integration of artificial intelligence (AI) and machine learning (ML), not as separate tools, but as synergistic partners to robotics. Aim: This narrative review proposes a conceptual framework for an AI-driven robotic ecosystem in total knee arthroplasty. We examine the evidence supporting the independent contributions of robotic precision and AI-based analytics and explore how their integration may support a data-informed, adaptive surgical workflow. Materials and methods: A structured narrative review of peer-reviewed literature on RA-TKR and AI/ML applications in orthopedics was conducted. Evidence was synthesized to support the proposed ecosystem framework. Results: The evidence confirms that robotic platforms consistently improve implant alignment and reduce outliers, though their impact on long-term patient-reported outcomes is less clear. In parallel, AI/ML applications demonstrate significant capabilities across the surgical workflow, including predictive analytics for preoperative planning, real-time intraoperative guidance, and personalized postoperative outcome forecasting. Our synthesis reveals that the synergy of these technologies creates a feedback loop where surgical and outcomes data continuously refine predictive models. Conclusion: The future of knee arthroplasty is likely to depend not solely on enhanced mechanical precision but on the judicious integration of robotics with data-driven intelligence. An AI-driven robotic ecosystem offers a promising conceptual model for advancing personalized, predictive care; however, its clinical value and economic sustainability require validation through robust prospective studies.

Background: Food allergy (FA) is an increasing public health concern with significant implications for child health and quality of life. Early introduction of allergenic foods has been shown to reduce the risk of food allergy development; however, maternal awareness and adherence to these recommendations remain inconsistent. This study aimed to assess maternal awareness and practices regarding the timing of allergenic food introduction among mothers residing in Makkah, Saudi Arabia. Methods: A descriptive cross-sectional study was conducted between November 2023 and March 2024 involving parents of children aged younger than 48 monthsin the Makkah region. Data were collected via a self-administered electronic questionnaire distributed through social media platforms. Results: A total of 391 parents participated. Parent-reported food allergy was identified in 11.3% of children, while 14.6% had eczema. Early introduction (<12 months) was more common for egg (43.3%) and wheat (71.1%) compared to peanut (28.9%), tree nuts (30.9%), sesame (30.9%), and seafood (28.9%). A considerable proportion of children had not been introduced to key allergenic foods even after 36 months, particularly peanuts (45.3%) and sesame (42.2%). Children with eczema were significantly more likely to have early introduction of egg (p = 0.035), tree nuts (p = 0.046), and seafood (p = 0.031). Similarly, children with a family history of food allergy had higher early introduction rates of tree nuts (55.3% vs. 44.0%, p = 0.043) and seafood (62.3% vs. 49.1%, p = 0.019). Only 25.8% of mothers were aware that early introduction might prevent food allergies, and just 22% reported receiving professional advice to introduce allergenic foods early. Conclusions: Maternal awareness regarding the timely introduction of allergenic foods in Makkah remains limited, with delayed introduction persisting beyond 36 months for several high-risk allergens. These findings underscore the need for targeted educational interventions and improved counseling by healthcare providers.