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Introduction : There is limited information describing features and outcomes of patients requiring Intermediate Respiratory Care Unit (IRCU) hospitalization for COVID19 disease and as of yet, no mechanical or medical treatments have clearly demonstrated efficacy in IRCU. Methods : Demographics and clinical variables on admission, as well as medical and mechanical therapeutic interventions, were extracted from Electronic Clinical Records in 274 SARS-CoV-2 infected patients attending a third level hospital IRCU. Using multivariate logistic regression analysis, variables that best discriminated mortality were obtained. Principal components analysis and a neural network (NN) algorithm were applied. Results : In relation to respiratory support, high-flow oxygen therapy and weaning procedures were associated with survival as were CPAP and non-invasive ventilation with low levels of support among the most severely affected. The IRCU achieved a survival rate of 87.6%, avoided 178 ICU admissions, successfully referred 35% to the ICU, and of these, 94% later survived the weaning phase. Higher mortality incidence was associated with cardiac and respiratory diseases and fever, heart rhythm and blood pressure disturbances. Following analysis of specific therapeutic options Corticoids and Anticoagulants were associated with better outcomes. Conclusions : The IRCU prevented the collapse of the ICU, allowed for recovered ICU patients to be quickly released from their unit, thus freeing up critical care beds and permitting them to function more effectively and in terms of mortality, achieved good results, that did not worsen due to a possible delay in intubation. In addition, we have generated an open-access NN capable of identifying severity predictors of SARS-CoV-2.