Autonomous Artificial Intelligence Increases Access and Health Equity in Underserved Populations with Diabetes.

Diabetic eye disease (DED) is a leading cause of blindness in the world. Early detection and treatment of DED have been shown to be both sight-saving and cost-effective. As such, annual testing for DED is recommended for adults with diabetes and is a Healthcare Effectiveness Data and Information Set (HEDIS) measure. However, adherence to this guideline has historically been low, and access to this sight-saving intervention has particularly been limited for specific populations, such as Black or African American patients. In 2018, the US Food and Drug Agency (FDA) De Novo cleared autonomous artificial intelligence (AI) for diagnosing DED in a primary care setting. In 2020, Johns Hopkins Medicine (JHM), an integrated healthcare system with over 30 primary care sites, began deploying autonomous AI for DED testing in some of its primary care clinics. In this retrospective study, we aimed to determine whether autonomous AI implementation was associated with increased adherence to annual DED testing, and whether this was different for specific populations. JHM primary care sites were categorized as "non-AI" sites (sites with no autonomous AI deployment over the study period and where patients are referred to eyecare for DED testing) or "AI-switched" sites (sites that did not have autonomous AI testing in 2019 but did by 2021). We conducted a difference-in-difference analysis using a logistic regression model to compare change in adherence rates from 2019 to 2021 between non-AI and AI-switched sites. Our study included all adult patients with diabetes managed within our health system (17,674 patients for the 2019 cohort and 17,590 patients for the 2021 cohort) and has three major findings. First, after controlling for a wide range of potential confounders, our regression analysis demonstrated that the odds ratio of adherence at AI-switched sites was 36% higher than that of non-AI sites, suggesting that there was a higher increase in DED testing between 2019 and 2021 at AI-switched sites than at non-AI sites. Second, our data suggested autonomous AI improved access for historically disadvantaged populations. The adherence rate for Black/African Americans increased by 11.9% within AI-switched sites whereas it decreased by 1.2% within non-AI sites over the same time frame. Third, the data suggest that autonomous AI improved health equity by closing care gaps. For example, in 2019, a large adherence rate gap existed between Asian Americans and Black/African Americans (61.1% vs. 45.5%). This 15.6% gap shrank to 3.5% by 2021. In summary, our real-world deployment results in a large integrated healthcare system suggest that autonomous AI improves adherence to a HEDIS measure, patient access, and health equity for patients with diabetes - particularly in historically disadvantaged patient groups. While our findings are encouraging, they will need to be replicated and validated in a prospective manner across more diverse settings.

Universities of Chinese Medicine Enter the Global Stage of Best Universities Rankings in 2020.

Objective: Chinese Medicine (known as acupuncture and Oriental Medicine (AOM) in the United States), has spread far and been utilized in more than 183 countries or regions. It has played an important role in the health care systems of many countries. Licensed acupuncturists' contribution to the U.S. market alone is more than 3.5 billion dollars. The aim of the current study was to determine the ranking status of Chinese Medicine schools on the global or international level in 2020. Materials and Methods: Databases of PubMed.gov, wanfangdata.com.cn, cnki.net, and google.com were searched, using the keywords: university or college or school, Chinese Medicine or acupuncture and Oriental Medicine, global ranking or international ranking, 2020 both in English and Chinese. If the ranking did not show up in the results directly, the authors moved on to find global or international higher education (universities or colleges) ranking agencies or institutions. Then the authors used the websites of ranking agencies or institutions to conduct more research, using the keywords: 2020, Chinese Medicine, or acupuncture and Oriental Medicine. Results: U.S. News & World Report is the only recognized authority that reported the ranking status of universities of Chinese Medicine in its 2020 edition, in which the best global universities were ranked. A total of 1500 universities in 81 countries and regions were included. Based on the overall academic strength of each university, Shanghai University of Traditional Chinese Medicine, Nanjing University of Chinese Medicine, and Guangzhou University of Chinese Medicine were ranked as numbers 1376, 1390 and 1440, respectively. In clinical medicine, 750 universities were ranked among the strongest in the world; Nanjing University of Chinese Medicine, Shanghai University of Traditional Chinese Medicine, and Guangzhou University of Chinese Medicine were ranked as 688th, 734th, and 738th, respectively. In pharmacology and toxicology, 250 universities were among the strongest in the world; Shanghai University of Traditional Chinese Medicine and Nanjing University of Chinese Medicine were ranked as 153rd and 209th, respectively. In oncology, 250 universities were ranked as strongest in the world; Nanjing University of Chinese Medicine was ranked as 243rd in the world. Conclusions: Chinese Medicine schools are more accepted and more highly ranked than they had been in the past.

Lack of Interactions Between an Antisense Oligonucleotide with 2'-O-(2-Methoxyethyl) Modifications and Major Drug Transporters.

ISIS 141923 is a model compound of 2'-O-(2-methoxyethyl) (2'-MOE) modified antisense oligonucleotides (ASOs). The purpose of this study is to determine whether ISIS 141923 is a substrate or an inhibitor against a panel of nine major uptake or efflux drug transporters, namely breast cancer resistance protein (BCRP), P-glycoprotein (P-gp), organic anion transporter (OAT)1, OAT3, organic cation transporter (OCT)1, OCT2, organic anion transporting polypeptide 1B (OATP1B)1, OATP1B3, and bile salt export pump (BSEP), in vitro. The uptake test system for transporters in the solute carrier (SLC) family (OAT1, OAT3, OCT1, OCT2, OATP1B1, and OATP1B3) was studied in Madin-Darby canine kidney (MDCK)-II cells transfected to express the transporters of interest. BCRP was studied using carcinoma colon-2 (Caco-2) cells with endogenously expressed BCRP. P-gp transporter was studied in MDCK-multi-drug resistance 1 (MDR1) cells, while BSEP was studied using Spodoptera frugiperda 9 (Sf9) membrane vesicles containing human BSEP. The ISIS 141293 concentrations evaluated were 10 and 100 µM for the substrate and inhibition study, respectively. Cellular uptake of ISIS 141923 was analyzed using a high performance liquid chromatography-mass spectrometry method, while concentrations of known substrates (used as positive controls) of each transporters evaluated were determined by radiometric detection. At 10 µM ISIS 141923, there was no significant transporter-mediated uptake of ISIS 141923 (P > 0.05) in the SLC family, and the efflux ratios were not above 2.0 for either BCRP or P-gp. Therefore, no transporter-mediated uptake of ISIS 141923 was observed by any of the nine transporters studied. At 100 µM ISIS 141923, the % inhibition was in the range of -16.0% to 19.0% for the nine transporters evaluated. Therefore, ISIS 141923 is not considered as an inhibitor of the nine transporters studied. Overall, the results from this study suggest that it is unlikely that ISIS 141923 or similar 2'-MOE ASOs would interact with small molecule drugs either as a victim (substrate) or perpetrator (inhibitor) of major transporters in humans. The results from available clinical drug-drug interaction studies conducted with this class of compounds to date are also supportive of this conclusion.