The VEGF protein (Vascular Endothelial Growth Factor) was identified in the '80s as a factor which induces proliferation of blood vessels in the body in general and in the retina in particular. Proliferative processes in retinal blood vessels, vascular permeability and induced edema which follows, frequently cause blindness in the diseases of the macula: AMD (Age-related Macular Degeneration) diabetes and retinal vascular occlusions. Since 2006, through treatment using anti-VEGF drugs--Avastin (Bevacizumab) and Lucentis (Ranibizumab) and Eylea (Aflibercept)--blindness in many patients in Israel and elsewhere was prevented. This paper reviews the treatment with anti-VEGF intraocular injections in the above mentioned diseases with reference to the growing activity at the Assuta Eye Institute.
AbstractPurpose - To evaluate AI-based chat bots ability to accurately answer common patient's questions in the field of ophthalmology. Methods - An experienced ophthalmologist curated a set of 20 representative questions and responses were sought from two AI generative models: OpenAI's ChatGPT and Google's Bard (Gemini Pro). Eight expert ophthalmologists from different sub-specialties assessed each response, blinded to the source, and ranked them by three metrics – accuracy, comprehensiveness, and clarity, on a 1-5 scale. Results - For accuracy, ChatGPT scored a median of 4.0, whereas Bard scored a median of 3.0. In terms of comprehensiveness, ChatGPT achieved a median score of 4.5, compared to Bard which scored a median of 3.0. Regarding clarity, ChatGPT maintained a higher score with a median of 5.0, compared to Bard's median score of 4.0. All comparisons were statistically significant (p<0.001). Conclusion - AI-based chat bots can provide relatively accurate and clear responses for addressing common ophthalmological inquiries. ChatGPT surpassed Bard in all measured metrics. While these AI models exhibit promise, further research is indicated to improve their performance and allow them to be used as a reliable medical tool.
Evaluation and follow-up of infants with cholelithiasis and pseudolithiasis in a pediatric ward.Prospective study from April 1990 to October 2003 identified hospitalized infants younger than 2 years with ultrasonographic findings of cholelithiasis, choledocholithiasis or pseudolithiasis. Associated abnormalities or contributory factors were recorded and patients were followed for from 6 months to 13 years (mean, 4 years).Thirty-four patients were diagnosed between the age of 3 weeks and 24 months. Thirteen (38%) had been treated with third-generation cephalosporins. Other associated factors were dehydration in 10 (29%), urinary tract infection in two (6%) and one each for cholestatic liver disease, total parenteral nutrition, immunoglobulin A deficiency and prematurity. Six infants (17%) had no known risk factor. Six additional patients were diagnosed by antenatal ultrasound.Cholelithiasis in infants hospitalized for a variety of common pediatric conditions is not rare. Dehydration and treatment with third-generation cephalosporins are important associated factors. The classic risk factors of hemolysis and previous gastrointestinal surgery, were not found in our group. The overall prognosis was good. Pseudolithiasis disappeared in all infants. Of the 21 infants with cholelithiasis, only two developed cholecystitis. In nine infants, spontaneous resolution occurred. In the absence of other clinical or imaging evidence of biliary tract disease, conservative management is advised.
To investigate the effect of phacovitrectomy on the post-operative anterior chamber depth (ACD) and refractive outcomes, and to analyze the potential differences between vitreous filling with BSS, air and gas.Patients who underwent phacovitrectomy were included in this study and invited for repeated post-operative examination including refraction and biometry at least 3 months after the surgery. Data retrieved included demographic information, indication for phacovitrectomy, surgical details, type of vitreous filling (BSS, air or gas), pre-operative and post-operative biometric data including K-readings, axial length (AL), and ACD, as well as spherical equivalent (SE) values of the target and final refraction.Forty-three eyes of 43 patients were included in this study, including 10 eyes filled with BSS, 18 with air and 15 with gas. The mean difference between the final measured spherical equivalent (SE) and the SE of the intended target refraction was 0.61±0.68 D (p = 0.019). Only 58.1% of eyes had a final SE within ±0.5D of the target refraction. Following surgery, AL remained unchanged, while mean pre-operative ACD increased significantly from 3.11±0.34 mm to 4.77±0.47 mm (p < 0.001). There was no difference in refractive error between the vitreous fillings and no correlation with AL or ACD.Phacovitrectomy is associated with lower accuracy of post-operative refraction compared to cataract surgery. This may be attributed to a significant change in ACD, influencing the effective lens position of the IOL, and may require adjustment of the pre-operative calculations.
Abstract Purpose To evaluate AI-based chat bots ability to accurately answer common patient’s questions in the field of ophthalmology. Methods An experienced ophthalmologist curated a set of 20 representative questions and responses were sought from two AI generative models: OpenAI’s ChatGPT and Google’s Bard (Gemini Pro). Eight expert ophthalmologists from different sub-specialties assessed each response, blinded to the source, and ranked them by three metrics—accuracy, comprehensiveness, and clarity, on a 1–5 scale. Results For accuracy, ChatGPT scored a median of 4.0, whereas Bard scored a median of 3.0. In terms of comprehensiveness, ChatGPT achieved a median score of 4.5, compared to Bard which scored a median of 3.0. Regarding clarity, ChatGPT maintained a higher score with a median of 5.0, compared to Bard’s median score of 4.0. All comparisons were statistically significant ( p < 0.001). Conclusion AI-based chat bots can provide relatively accurate and clear responses for addressing common ophthalmological inquiries. ChatGPT surpassed Bard in all measured metrics. While these AI models exhibit promise, further research is indicated to improve their performance and allow them to be used as a reliable medical tool.
To evaluate the visual acuity results of monthly ranibizumab injections compared with a variable-dosing schedule for the treatment of neovascular age-related macular degeneration.A retrospective study that compared two cohorts of consecutive patients. All patients were treatment naive, with baseline visual acuity of 20/400 or better, and completed 12 months of therapy. In the first group all patients received monthly injections. In the other group, after 3 monthly loading doses, a variable-dosing schedule was used, based on a monthly clinical assessment and optical coherence tomography.Fifty-six consecutive patients (60 eyes) were included. At 12 months the median number of injections were 12 and 8, respectively, and the mean change in Snellen visual acuity was an improvement of 0.27 logarithm of the minimum angle of resolution in the monthly treated group versus 0.21 logarithm of the minimum angle of resolution improvement in the variable-dosing group (P = 0.53). In the monthly treated group 96.8% of eyes lost <0.3 logarithm of the minimum angle of resolution versus 96.6% of eyes in the variable-dosing group (P = 1.0).We were able to show that in our clinical setting patients achieved similar visual acuity results with either monthly injections or with a variable-dosing protocol. There was a trend toward better results with monthly treatment.
