Screening and Establishing a Diagnosis With OCT

Closer consideration of nonglaucomatous conditions is warranted.

Sanjay Asrani, MD

Glaucoma Today

OCT imaging has been proven to be an effective screening tool for glaucoma. In one study, investigators concluded that the quantitative parameters derived from OCT images, particularly vertical cup-to-disc ratio and retinal nerve fiber layer (RNFL) thickness, demonstrated sensitivities and specificities that were “adequately robust” for community glaucoma screening.1 Another study showed a fair level of agreement regarding glaucoma referral recommendations between glaucoma specialists with access to comprehensive screening data and OCT specialists with access to only OCT data.2 In 2022, however, Chou et al3 set out to update two reviews on glaucoma screening that were designed to inform the US Preventive Services Task Force. Their conclusions, which were published in JAMA, reported “limited direct evidence on glaucoma screening, showing no association with benefits.” The authors further noted that “screening tests can identify persons with glaucoma and treatment was associated with a lower risk of [glaucomatous] progression” but that “the evidence of improvement in visual outcomes, quality of life, and function remains lacking.” These conclusions were also published by the US Preventive Services Task Force in an Agency for Healthcare Research and Quality report.4 The bar is apparently set high to prove that glaucoma screening, although effective, indeed improves visual outcomes, patient quality of life, and function. This article reviews how best to use OCT to screen patients, establish a diagnosis, and actualize the many benefits of this diagnostic modality. ESTABLISHING A DIAGNOSIS Ophthalmologists have all come to rely on OCT. However, in the past few years, I have seen many pitfalls, related not only to misdiagnosis but also to codiagnosis, wherein the presence of other ocular pathology may be overlooked in the setting of glaucoma. One early pitfall relates to examining cup-to-disc asymmetry, the hallmark of glaucoma detection. In Figure 1A, the optic cups of the right and left eyes may seem similarly sized at first glance; however, bringing the images closer together to eliminate the distance between the optic cups reveals that the optic nerve of the right eye occupies more space within the green circle than the optic nerve of the left eye (Figure 1B). Side-by-side viewing can help to magnify subtle differences between optic nerves and reveal a case of nerve size asymmetry. This finding can be confirmed by the extreme symmetry of RNFL measurements between eyes (Figure 1C).

A Place for House Calls in Optometry

Consider delivering eye care where it’s needed most.

Damaris Raymondi, OD, FAAO

Modern Optometry

As optometrists, we stand at the forefront of eye care, uniquely positioned to significantly affect our patients’ lives. I had one experience that I will never forget, and it all began when a gentleman came in for his annual eye exam. After going through my pre-testing room, he asked me if the office was wheelchair-accessible, to which I replied in the affirmative. He explained that his father is in a wheelchair and that they were just at an eye clinic where they were told he couldn’t be seen. He asked if I would see his father and I of course said yes. I could not imagine a situation where a patient would be told they could not be examined, simply due to their mobility issues. Fast-forward to the day of his father’s appointment. THE CASE A 70-year-old male patient with progressive supranuclear palsy (PSP) presented for a comprehensive eye exam with no complaints. He arrived in a wheelchair, although I was informed that most of the time he was bedbound. He was nonverbal, wearing medical safety mittens, and was fully dependent on caretakers.

Comparing AI-Generated Answers to Patients’ Eye Care Questions With Ophthalmologists’ Responses

Robert T. Chang, MD; and Neda Shamie, MD

Eyetube

Robert T. Chang, MD, joins Neda Shamie, MD, to discuss a cross-sectional study that assessed the quality of ophthalmology advice generated by a large language model chatbot (ChatGPT, OpenAI) compared to advice written by an ophthalmologist. How did the responses stack up? To access the full review, please visit the link here: https://pubmed.ncbi.nlm.nih.gov/37606922/