Nationwide genetic analysis of more than 600 families with inherited eye diseases in Argentina.

This study corresponds to the first large-scale genetic analysis of inherited eye diseases (IED) in Argentina and describes the comprehensive genetic profile of a large cohort of patients. Medical records of 22 ophthalmology and genetics services throughout 13 Argentinian provinces were analyzed retrospectively. Patients with a clinical diagnosis of an ophthalmic genetic disease and a history of genetic testing were included. Medical, ophthalmological and family history was collected. A total of 773 patients from 637 families were included, with 98% having inherited retinal disease. The most common phenotype was retinitis pigmentosa (RP, 62%). Causative variants were detected in 379 (59%) patients. USH2A, RPGR, and ABCA4 were the most common disease-associated genes. USH2A was the most frequent gene associated with RP, RDH12 early-onset severe retinal dystrophy, ABCA4 Stargardt disease, PROM1 cone-rod dystrophy, and BEST1 macular dystrophy. The most frequent variants were RPGR c.1345 C > T, p.(Arg449*) and USH2A c.15089 C > A, p.(Ser5030*). The study revealed 156/448 (35%) previously unreported pathogenic/likely pathogenic variants and 8 possible founder mutations. We present the genetic landscape of IED in Argentina and the largest cohort in South America. This data will serve as a reference for future genetic studies, aid diagnosis, inform counseling, and assist in addressing the largely unmet need for clinical trials to be conducted in the region.

COVID-19 Infection Process in Italy and Spain: Are Data Talking? Evidence From ARMA and Vector Autoregression Models.

COVID-19 (coronavirus disease 2019) has spread successfully worldwide in a matter of weeks. After the example of China, all the affected countries are taking hard-confinement measures to control the infection and to gain some time to reduce the significant amount of cases that arrive at the hospital. Although the measures in China reduced the percentages of new cases, this is not seen in other countries that have taken similar measures, such as Italy and Spain. After the first weeks, the worry was whether or not the healthcare system would collapse rather than its response to the patient's needs who are infected and require hospitalization. Using China as a mirror of what could happen in our countries and with the data available, we calculated a model that forecasts the peak of the curve of infection, hospitalization, and ICU bed numbers. We aimed to review the patterns of spread of the virus in the two countries and their regions, looking for similarities that reflect the existence of a typical path in this expansive virulence and the effects of the intervention of the authorities with drastic isolation measures, to contain the outbreak. A model based on Autorregressive and moving average models (ARMA) methodology and including Chinese disease pattern as a proxy, predicts the contagious pattern robustly. Based on the prediction, the hospitalization and intensive care unit (ICU) requirements were also calculated. Results suggest a reduction in the speed of contagion during April in both countries, earlier in Spain than in Italy. The forecast advanced a significant increase in the ICU needs for Spain surpassing 8,000 units by the end of April, but for Italy, ICU needs would decrease in the same period, according to the model. We present the following predictions to inform political leaders because they have the responsibility to maintain the national health systems away from collapsing. We are confident these data could help them into decision-taking and place the capitals (from hospital beds to human resources) into the right place.

Comparing the Prevalence of Polypharmacy and Potential Drug-Drug Interactions in Nursing Homes and in the Community Dwelling Elderly of Emilia Romagna Region.

Backround: We aimed at assessing the prevalence of polypharmacy and potential drug-drug interactions (DDIs) with clinical relevance in elderly patient on Emilia Romagna area. Both outpatients and residents in nursing homes were assessed, with only partially overlapping strategies. Methods: We defined a list of 190 pairs of potentially interacting drugs, based on literature appraisal and availability of therapeutic alternatives. January-June 2018 data on drug use in patients over 65 years-old were collected from nine Local Health Authorities of Emilia Romagna: data on community-dwelling subjects were extracted from archives of reimbursed prescriptions, while drug use in a sample of nursing homes was recorded from clinical charts in one index day within the same semester. The frequency of polypharmacy (at least five or at least 10 concurrent drugs) and of each DDI was calculated. Results: In line with different rates of polypharmacy (80% vs 16%), the risk of exposure to at least one interaction was 53.7% in nursing homes and 26.4% in outpatients. Among DDIs, in nursing homes antidepressants-anxiolytics (11.9%) ranked first, followed by antidepressants-aspirin (7.4%). In outpatients, ACE-inhibitors-non-steroidal anti-inflammatory drugs (NSAIDs) reached 7.2% followed by the calcium channel blockers-α-blockers (2.4%). Discussion: Polypharmacy and risk of DDIs appeared very different in the two settings, due to both technical and clinical reasons. In order to reduce use of benzodiazepines, NSAIDs, antidepressants and relevant DDIs, 1) defining alternative options for pain relief in elderly outpatients, and 2) implementing non-pharmacological management of insomnia and anxiety in nursing homes should be prioritized.