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PURPOSE: The objective of this study was to evaluate the relationship between research activity and National Institutes of Health (NIH) funding status of the United States (US) academic ophthalmologists. METHODS: A retrospective cross-sectional analysis of bibliometric data was conducted. The NIH Research Portfolio Online Reporting Tools Expenditures and Reports (rePORTER) website was utilized to identify ophthalmology departments in the US that received NIH funding. Affiliated faculty from these institutions were then identified using NIH rePORTER and institutional websites. H-index was calculated using the Scopus database, and the NIH iCite tool was used to determine the Relative Citation Ratio (RCR). The h-index and w-RCR quantified research productivity, while m-RCR measured research impact. RESULTS: Data on 2688 faculty members from 66 departments we re identified, of which 21% were NIH-funded. Faculty members who received NIH-funding had significantly greater research productivity and impact as measured by h-index (32.5 vs 16.6; p < .001), m-RCR (2.2 vs 1.6; p < .001), and w-RCR (147.2 vs 70.1; p < .001) than their non-funded peers. When stratified by academic rank, NIH-funded faculty still had significantly higher h-index (16.1 vs 7.9; p < .001), m-RCR (2.2 vs 1.4; p < .001), and w-RCR (63.2 vs 61.8; p < .001) than non-funded peers. A similar trend was observed among non-tenured faculty members. CONCLUSION: NIH funding is associated with higher research productivity and impact among US academic ophthalmologists as measured by h-index and RCR, which suggests that NIH funding may be a critical factor in enhancing scholarly contributions of ophthalmologists. These findings underscore the importance of continued investment in NIH funding to foster high-impact research within the field of ophthalmology.
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PURPOSE: Artificial intelligence (AI) is often trained on images without ocular co-morbidities, limiting its generalizability. This study aims to evaluate the accuracy of a convolutional neural network (CNN) applied to color fundus photos (CFPs) with simulated cataracts (SCs) in detecting diabetic retinopathy (DR). METHODS: A database of 3662 CFPs (from Asia Pacific Tele-Ophthalmology Society (APTOS) 2019) was used. Using transfer learning, a CNN was trained to classify the training images as either DR or non-DR. The CNN was then applied to classify the testing images after an SC was applied, using varying degrees of Gaussian blur. RESULTS: Accuracy without SC was 97.0%, sensitivity (Sn) 95.7%, specificity (Sp) 98.3%. For mild SC, accuracy was 93.1%, Sn 91.8%, Sp 94.3%. For moderate SC, accuracy was 62.8%, Sn 31.4%, Sp 95.2%. For severe SC, accuracy was 53.5%, Sn 11.8%, Sp 96.5%. CONCLUSION: SCs significantly impaired AI accuracy. To prepare AI for clinical use, cataracts and other real-world clinical challenges affecting image quality must be accounted for.
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Catarata , Diabetes Mellitus , Retinopatía Diabética , Humanos , Inteligencia Artificial , Retinopatía Diabética/diagnóstico , Fondo de Ojo , Redes Neurales de la Computación , Catarata/complicaciones , Catarata/diagnósticoRESUMEN
A 35-year-old Hispanic man presented with fever, chills, dysuria, diarrhoea, scleral icterus, tachycardia and tachypnea. He was found to be COVID-19 positive, CT of the pelvis revealed prostatic abscess, and urine culture grew Klebsiella pneumoniae Additionally, he was found to have diabetes and cirrhosis. During treatment, the patient developed vision loss, and was diagnosed with endogenous Klebsiella endophthalmitis. The patient was treated with intravenous antibiotics, pars plana vitrectomy, intravitreal antibiotics and cystoscopy/suprapubic catheter placement. On follow-up, the patient has had the suprapubic catheter removed, and successfully passed a voiding trial, but suffers permanent vision loss in both eyes.
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COVID-19 , Diabetes Mellitus , Endoftalmitis , Infecciones por Klebsiella , Prostatitis , Adulto , Antibacterianos/uso terapéutico , Ceguera , COVID-19/complicaciones , Diabetes Mellitus/virología , Endoftalmitis/complicaciones , Endoftalmitis/diagnóstico , Endoftalmitis/terapia , Humanos , Infecciones por Klebsiella/complicaciones , Infecciones por Klebsiella/diagnóstico , Infecciones por Klebsiella/tratamiento farmacológico , Klebsiella pneumoniae , Cirrosis Hepática/complicaciones , Cirrosis Hepática/virología , Masculino , Prostatitis/complicaciones , Prostatitis/microbiología , SARS-CoV-2 , VitrectomíaRESUMEN
The ability of the adrenocorticotropic hormone (ACTH) to induce steroidogenesis and upregulate anti-inflammatory processes has long been known. More recently, however, extrasteroidal mechanisms, through which ACTH exerts anti-inflammatory processes, have been described. This has renewed hope that ACTH can combat inflammatory conditions even when resistant to steroids. This review article summarizes the literature on the use of ACTH in ocular disease. Unfortunately, much of the data regarding the clinical utility of ACTH are outdated, with many studies published in the 1950s and 1960s. Many of these older studies are inconsistent or incomplete with their reporting, making it difficult to ascertain the meaning of the outcomes. Despite the limitations, 2 important trends are evident. First, when used to treat an inflammatory disease, ACTH can be effective at decreasing or eliminating ocular inflammation, even in a refractory disease resistant to multiple treatment modalities. Second, adverse effects of ACTH are rare and are most likely to be reported with relatively high doses of ACTH therapy. Taken as a whole, these studies offer initial promising data that ACTH may be a safe and effective alternative in refractory ocular inflammatory disease. However, they highlight an important lack of prospective data to more rigorously understand the true safety and efficacy of this therapy.