Mesenchymal stem cells (MSC) have received particular attention due to their ability to inhibit inflammation caused by cytokine storm induced by COVID-19. In this way some patients have been treated successfully. The aim of this study was to evaluate the safety and describe the clinical changes after IV administration of allogeneic human umbilical cord MSC (ahUCMSC), in patients with bilateral pneumonia caused by COVID-19, complicated with severe ARDS, as compassionate treatment. This was a pilot, open-label, prospective, longitudinal study. Five patients that did not improve in their clinical conditions after 48 hours of receiving the standard medical management used by the Medical Center and with persistent PaO2/FiO2 less than 100 mmHg were enrolled. ahUCMSC were infused IV, at dose of 1x10 6 per Kg of body weight over 15 minutes. Patients were monitored after the infusion to detect adverse event. Pa02/FiO2, vital signs, D-dimer, C reactive protein and total lymphocytes were monitored for 21 days after the infusion or until the patient was discharged from the hospital. Descriptive statistics were used with means or medians and standard deviation or interquartile range according to the type of variable. The Wilcoxon's rank-sum was used for stationary samples. Adverse events occurred in three patients and were easily and quickly controlled. Immediately after the infusion of ahUCMSC, constant rise of PaO2/FiO2 was observed in all patients during the first 7 days, with statistical significance. Three patients survived and were extubated on the ninth day post-infusion. Two patients died at 13 and 15 days after infusion. The infusion of ahUCMSC in patients with severe ARDS caused by COVID-19, was safe, and demonstrated its anti-inflammatory capacity in the lungs, by improving the respiratory function expressed by PaO2 / FiO2, which allowed the survival of 3 patients, with extubation at 9 days.

Multisystem inflammatory syndrome in children (MIS-C) is a recently recognized spectrum of disease symptoms and signs associated with COVID-19 infection. As defined by the Centers for Disease Control and Prevention (CDC), MIS-C is diagnosed in individuals aged <21 years presenting with fever; laboratory evidence of inflammation; clinically severe illness requiring hospitalization; multisystem (≥2) organ involvement (dermatologic, cardiac, renal, respiratory, hematologic, gastrointestinal, or neurological); a positive test for current or recent SARS-CoV-2 infection, and no plausible alternative diagnoses.(Centers for Disease Control and Prevention (CDC), 2019) Among the clinical

Autopsy continues to be a useful tool to assess quality of clinical diagnosis. The diagnostic errors with therapeutic repercussion are bacterial infections and cardiovascular disease. Patients with a stay less than 24 hours have a higher rate of type I diagnostic errors.

La infección por SARS-CoV-2 se ha diseminado rápidamente, provocando una pandemia mundial en la cual nos vemos afectados. En el Instituto Nacional de Salud del Niño de San Borja, centro de referencia nacional de pacientes pediátricos quirúrgicos, desde el 14 de abril al 12 de agosto del 2020, se hospitalizaron 106 pacientes con infección por SARS-CoV-2, de los cuales 11 tuvieron diagnostico quemadura y dos fueron pacientes grandes quemados con diagnóstico COVID-19 por prueba molecular. Detallamos el caso de una paciente pediátrica, de siete años, gran quemada que fue atendida en unidad de cuidados intensivos, y con COVID-19 asintomática, presentó evolución y pronóstico favorable, con recuperación total de su lesión. Por otro lado, el COVID-19 se puede manifestar de forma severa produciendo un síndrome inflamatorio multisistémico que presenta manifestaciones clínicas poco comunes y que puede empeorar el pronóstico, como fue observado en nuestro otro paciente de siete meses que falleció pese a recibir manejo especializado y oportuno.

Background: The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. Methods: Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 Intensive Care Units(ICU) in Spain. The objective was to analyze patient’s factors associated with mortality risk and utilize a Machine Learning(ML) to derive clinical COVID-19 phenotypes. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. An unsupervised clustering analysis was applied to determine presence of phenotypes. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves. Results: The database included a total of 2,022 patients (mean age 64[IQR5-71] years, 1423(70.4%) male, median APACHE II score (13[IQR10-17]) and SOFA score (5[IQR3-7]) points. The ICU mortality rate was 32.6%. Of the 3 derived phenotypes, the C(severe) phenotype was the most common (857;42.5%) and was characterized by the interplay of older age (>65 years), high severity of illness and a higher likelihood of development shock. The A(mild) phenotype (537;26.7%) included older age (>65 years), fewer abnormal laboratory values and less development of complications and B (moderate) phenotype (623,30.8%) had similar characteristics of A phenotype but were more likely to present shock. Crude ICU mortality was 45.4%, 25.0% and 20.3% for the C, B and A phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications.Conclusion: The presented ML model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a “one-size-fits-all” model in practice. Funding: None