Background: Observational studies have suggested that accelerated surgery is associated with improved outcomes in patients with a hip fracture. The HIP ATTACK trial assessed whether accelerated surgery could reduce mortality and major complications. Methods:We randomised 2970 patients from 69 hospitals in 17 countries. Patients with a hip fracture that required surgery and were ≥45 years of age were eligible. Patients were randomly assigned to accelerated surgery (goal of surgery within 6 hours of diagnosis; 1487 patients) or standard care (1483 patients). The co-primary outcomes were 1.) mortality, and 2.) a composite of major complications (i.e., mortality and non-fatal myocardial infarction, stroke, venous thromboembolism, sepsis, pneumonia, life-threatening bleeding, and major bleeding) at 90 days after randomisation. Outcome adjudicators were masked to treatment allocation, and patients were analysed according to the intention-to-treat principle; ClinicalTrials.gov, NCT02027896. Findings:The median time from hip fracture diagnosis to surgery was 6 hours (interquartile range [IQR] 4-9) in the accelerated-surgery group and 24 hours (IQR 10-42) in the standard-care group, p<0.0001. Death occurred in 140 patients (9%) assigned to accelerated surgery and 154 patients (10%) assigned to standard care; hazard ratio (HR) 0.91, 95% CI 0.72-1.14; absolute risk reduction (ARR) 1%, 95% CI -1-3%; p=0.40. The primary composite outcome occurred in 321 patients (22%) randomised to accelerated surgery and 331 patients (22%) randomised to standard care; HR 0.97, 95% CI 0.83-1.13; ARR 1%, 95% CI -2-3%; p=0.71.Interpretation: Among patients with a hip fracture, accelerated surgery did not significantly lower the risk of mortality or a composite of major complications compared to standard care.

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The rise of artificial intelligence (AI) has brought breakthroughs in many areas of medicine. In ophthalmology, AI has delivered robust results in the screening and detection of diabetic retinopathy, age-related macular degeneration, glaucoma, and retinopathy of prematurity. Cataract management is another field that can benefit from greater AI application. Cataract  is the leading cause of reversible visual impairment with a rising global clinical burden. Improved diagnosis, monitoring, and surgical management are necessary to address this challenge. In addition, patients in large developing countries often suffer from limited access to tertiary care, a problem further exacerbated by the ongoing COVID-19 pandemic. AI on the other hand, can help transform cataract management by improving automation, efficacy and overcoming geographical barriers. First, AI can be applied as a telediagnostic platform to screen and diagnose patients with cataract using slit-lamp and fundus photographs. This utilizes a deep-learning, convolutional neural network (CNN) to detect and classify referable cataracts appropriately. Second, some of the latest intraocular lens formulas have used AI to enhance prediction accuracy, achieving superior postoperative refractive results compared to traditional formulas. Third, AI can be used to augment cataract surgical skill training by identifying different phases of cataract surgery on video and to optimize operating theater workflows by accurately predicting the duration of surgical procedures. Fourth, some AI CNN models are able to effectively predict the progression of posterior capsule opacification and eventual need for YAG laser capsulotomy. These advances in AI could transform cataract management and enable delivery of efficient ophthalmic services. The key challenges include ethical management of data, ensuring data security and privacy, demonstrating clinically acceptable performance, improving the generalizability of AI models across heterogeneous populations, and improving the trust of end-users.

A significant proportion of the variation in iris area, curvature, and thickness was not explained by other ocular and demographic parameters. Iris curvature was associated strongly with angle width, and of all parameters investigated, AOD750 was most highly correlated with iris curvature.

Contact lens is a major risk factor for microbial keratitis among contact lens wearers. Chemical strategies that can prevent microbial adhesion and biofilm formation are required to improve a wearer’s hygiene and safety. Taking advantage of the material-independent properties of a polydopamine (pDA) coating, we investigated the role of covalent/noncovalent interactions of the antimicrobials and pDA in conferring long-term antimicrobial activities. The developed antimicrobial contact lenses not only retain their antibacterial efficiency against different bacterial strains for 2 weeks but also inhibit microbial adhesion and biofilm formation on the lens surfaces. The designed antimicrobial coatings were found to be safe for ocular cell lines. Moreover, the antimicrobial coatings did not affect the functional and surface properties of coated contact lenses. This methodology can be used to protect the contact lenses from microbial contamination for prolonged periods and has the potential to be extended for designing antimicrobial coatings for other medical devices as well.