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To maintain treatment quality and patient and staff safety in the SARS-CoV-2 era, it is important to minimise clinic visits and maximise use of imaging modalities. In addition, extending treatment intervals with longer-acting agents is key to maximising safety and patients’ vision outcomes.
Correcting abnormal tear film osmolarity before cataract surgery enables more accurate measurements to be captured, reducing residual refractive error.
A recently developed tool can help ophthalmologists to assess the quality of findings from real-world studies in retinal diseases. This will help them decide which results are most robust and applicable to their practice.
How studies into myopia management can increase access to vision care
Simply slowing disease progression is no longer enough
Physician outlines latest emerging technologies to treat condition
No two corneal ulcers are alike, but if they are large and centrally located, the common denominator is that time is of the essence
Methods using a combination of non-invasive thermal treatments and meibomian gland expression seem to be particularly effective.
A new amblyopia screening system that can be used on Android devices has performed better than some of the ‘gold standard’ stereotests in recent Hungarian studies.
An interdisciplinary team at Duke University has developed a proof-of-concept machine learning model capable of detecting symptomatic Alzheimer disease using multimodal retinal imaging data.
A one-piece, hydrophobic, monofocal IOL uses the small-aperture concept to provide a good alternative to the toric IOLs currently available.
A cost-utility analysis found that concurrent phacoemulsification and minimally invasive glaucoma surgery using trabecular microbypass stents is cost-effective for treating mild to moderate open-angle glaucoma, compared with cataract surgery alone.
Three approaches to examination give a comprehensive overview
Phase 1 multicentre study data demonstrate early signs of efficacy
One of AI’s most promising applications: new diagnostic algorithms
An interdisciplinary team at Duke University has developed a proof-of-concept machine learning model capable of detecting symptomatic Alzheimer disease using multimodal retinal imaging data.
Stabilising keratoconus and improving vision using ELZA-PACE customised CXL
Ultraviolet light’s potential in ocular care extends beyond structural reinforcement to antimicrobial applications, especially for microbial keratitis
Although off-label repackaged bevacizumab syringes appear to satisfy an urgent clinical and financial need for patients with a variety of retinal disorders, they are known to be associated with considerable public health concerns due to the risks posed to patients from compounding pharmacies’ lack of compliance with a variety of FDA requirements.
Detecting mitochondrial dysfunction may give clinicians a chance to reduce the rate of cognitive decline in patients with dementia
Working smarter, not harder, to benefit patients
A recently developed tool can help ophthalmologists to assess the quality of findings from real-world studies in retinal diseases. This will help them decide which results are most robust and applicable to their practice.
Current and future options for Fuchs endothelial corneal dystrophy
Giving due consideration to preoperative marking and the surgical technique in toric IOL implantation, as well as being diligent about reviewing postoperative results, can improve patient outcomes whilst minimising the chance of errors.