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Hereditary hemorrhagic telangiectasia is an inherited disease related to an alteration in angiogenesis, manifesting as cutaneous telangiectasias and epistaxis. As complications, it presents vascular malformations in organs such as the lung, liver, digestive tract, and brain. Currently, diagnosis can be made using the Curaçao criteria or by identifying the affected gene. In recent years, there has been an advance in the understanding of the pathophysiology of the disease, which has allowed the use of new therapeutic strategies to improve the quality of life of patients. This article reviews some of the main and most current evidence on the pathophysiology, clinical manifestations, diagnostic approach, screening for complications, and therapeutic options, both pharmacological and surgical.

SUMMARYOBJECTIVETo develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of COVID-19, to identify patients at risk of critical outcomes.DESIGNNational multicenter cohort study.SETTINGData from the SEMI (Sociedad Española de Medicina Interna) COVID-19 Registry, a nationwide cohort of consecutive COVID-19 patients presenting in 132 centers between March 23 and May 21, 2020. Model development used data from hospitals with ≥300 beds, and validation used those from hospitals with <300 beds.PARTICIPANTSAdults (age ≥18 years) presenting with COVID-19 diagnosis.MAIN OUTCOME MEASUREComposite of in-hospital death, mechanical ventilation or admission to intensive care unit.RESULTSThere were 10,433 patients, 7,850 (main outcome rate 25.1%) in the model development cohort and 2,583 (main outcome rate 27.0%) in the validation cohort. The clinical variables in the final model were: age, cardiovascular disease, moderate or severe chronic kidney disease, dyspnea, tachypnea, confusion, systolic blood pressure, and SpO2 ≤93% or supplementary oxygen requirement at presentation. The model developed had C-statistic of 0.823 (95% confidence interval [CI] 0.813 to 0.834) and calibration slope of 0.995. The external validation had C-statistic of 0.792 (95% CI, 0.772 to 0.812) and calibration slope of 0.872. The model showed positive net benefit in terms of hospitalizations avoided for the predicted probability thresholds between 3% and 79%.CONCLUSIONSAmong patients presenting with COVID-19, easily-obtained basic clinical information had good discrimination for identifying patients at risk of critical outcomes, and the model showed good generalizability. A model-based online prediction calculator provided with this paper would facilitate triage of patients during the pandemic.