External validation of prognostic scores for Covid-19: a multicentre cohort study of patients hospitalized in Greater Paris University Hospitals

International audienceThe Coronavirus disease 2019 (Covid-19) has led to an unparalleled influx of patients. Prognostic scores could help optimizing healthcare delivery, but most of them have not been comprehensively validated. We aim to externally validate existing prognostic scores for Covid-19. Methods We used "Covid-19 EvidenceAlerts" (McMaster University) to retrieve high-quality prognostic scores predicting death or intensive care unit (ICU) transfer from routinely collected data. We studied their accuracy in a retrospective multicentre cohort of adult patients hospitalized for Covid-19 from January 2020 to April 2021 in the Greater Paris University Hospitals. Areas under the receiver operating characteristic curves (AUC) were computed for the prediction of the original outcome, 30-day in-hospital mortality and the composite of 30-day in-hospital mortality or ICU transfer. Results We included 14,343 consecutive patients, 2,583 (18%) died and 5,067 (35%) died or were transferred to the ICU. We examined 274 studies and found 32 scores meeting the inclusion criteria: 19 had a significantly lower AUC in our cohort than in previously published validation studies for the original outcome; 25 performed better to predict in-hospital mortality than the composite of in-hospital mortality or ICU transfer; 7 had an AUC >0.75 to predict in-hospital mortality; 2 had an AUC >0.70 to predict the composite outcome. Conclusion Seven prognostic scores were fairly accurate to predict death in hospitalized Covid-19 patients. The 4C Mortality Score and the ABCS stand out because they performed as well in our cohort and their initial validation cohort, during the first epidemic wave and subsequent waves, and in younger and older patients

The Xenopus tadpole: an in vivo model to screen drugs favoring remyelination

International audienceBackground:In multiple sclerosis, development of screening tools for remyelination-promoting molecules is timely.Objective:A Xenopus transgenic line allowing conditional ablation of myelinating oligodendrocytes has been adapted for in vivo screening of remyelination-favoring molecules.Methods:In this transgenic, the green fluorescent protein reporter is fused to E. coli nitroreductase and expressed specifically in myelinating oligodendrocytes. Nitroreductase converts the innocuous pro-drug metronidazole to a cytotoxin. Spontaneous remyelination occurs after metronidazole-induced demyelinating responses. As tadpoles are transparent, these events can be monitored in vivo and quantified. At the end of metronidazole-induced demyelination, tadpoles were screened in water containing the compounds tested. After 72 h, remyelination was assayed by counting numbers of oligodendrocytes per optic nerve.Results:Among a battery of molecules tested, siponimod, a dual agonist of sphingosine-1-phosphate receptor 1 and 5, was among the most efficient favoring remyelination. Crispr/cas9 gene editing showed that the promyelinating effect of siponimod involves the sphingosine-1-phosphate receptor 5.Conclusion:This Xenopus transgenic line constitutes a simple in vivo screening platform for myelin repair therapeutics. We validated several known promyelinating compounds and demonstrated that the strong remyelinating efficacy of siponimod implicates the sphingosine-1-phosphate receptor 5

External validation of prognostic scores for COVID-19: a multicenter cohort study of patients hospitalized in Greater Paris University Hospitals

International audiencePurposeThe Coronavirus disease 2019 (COVID-19) has led to an unparalleled influx of patients. Prognostic scores could help optimizing healthcare delivery, but most of them have not been comprehensively validated. We aim to externally validate existing prognostic scores for COVID-19.MethodsWe used “COVID-19 Evidence Alerts” (McMaster University) to retrieve high-quality prognostic scores predicting death or intensive care unit (ICU) transfer from routinely collected data. We studied their accuracy in a retrospective multicenter cohort of adult patients hospitalized for COVID-19 from January 2020 to April 2021 in the Greater Paris University Hospitals. Areas under the receiver operating characteristic curves (AUC) were computed for the prediction of the original outcome, 30-day in-hospital mortality and the composite of 30-day in-hospital mortality or ICU transfer.ResultsWe included 14,343 consecutive patients, 2583 (18%) died and 5067 (35%) died or were transferred to the ICU. We examined 274 studies and found 32 scores meeting the inclusion criteria: 19 had a significantly lower AUC in our cohort than in previously published validation studies for the original outcome; 25 performed better to predict in-hospital mortality than the composite of in-hospital mortality or ICU transfer; 7 had an AUC > 0.75 to predict in-hospital mortality; 2 had an AUC > 0.70 to predict the composite outcome.ConclusionSeven prognostic scores were fairly accurate to predict death in hospitalized COVID-19 patients. The 4C Mortality Score and the ABCS stand out because they performed as well in our cohort and their initial validation cohort, during the first epidemic wave and subsequent waves, and in younger and older patients