Machine learning-based scoring system to predict in-hospital outcomes in patients hospitalized with COVID-19

BackgroundThe evolution of patients hospitalized with coronavirus disease 2019 (COVID-19) is still hard to predict, even after several months of dealing with the pandemic.AimsTo develop and validate a score to predict outcomes in patients hospitalized with COVID-19.MethodsAll consecutive adults hospitalized for COVID-19 from February to April 2020 were included in a nationwide observational study. Primary composite outcome was transfer to an intensive care unit from an emergency department or conventional ward, or in-hospital death. A score that estimates the risk of experiencing the primary outcome was constructed from a derivation cohort using stacked LASSO (Least Absolute Shrinkage and Selection Operator), and was tested in a validation cohort.ResultsAmong 2873 patients analysed (57.9% men; 66.6 ± 17.0 years), the primary outcome occurred in 838 (29.2%) patients: 551 (19.2%) were transferred to an intensive care unit; and 287 (10.0%) died in-hospital without transfer to an intensive care unit. Using stacked LASSO, we identified 11 variables independently associated with the primary outcome in multivariable analysis in the derivation cohort (n = 2313), including demographics (sex), triage vitals (body temperature, dyspnoea, respiratory rate, fraction of inspired oxygen, blood oxygen saturation) and biological variables (pH, platelets, C-reactive protein, aspartate aminotransferase, estimated glomerular filtration rate). The Critical COVID-19 France (CCF) risk score was then developed, and displayed accurate calibration and discrimination in the derivation cohort, with C-statistics of 0.78 (95% confidence interval 0.75–0.80). The CCF risk score performed significantly better (i.e. higher C-statistics) than the usual critical care risk scores.ConclusionsThe CCF risk score was built using data collected routinely at hospital admission to predict outcomes in patients with COVID-19. This score holds promise to improve early triage of patients and allocation of healthcare resources.     

Acute effect of propranolol on splanchnic circulation in normal and portal hypertensive rats

Propranolol decreases portal venous pressure in patients with cirrhosis but no method is available in man to study the effect of this beta-blocker on splanchnic organ blood flow. Because in rats, the microsphere method allows evaluation of regional blood flow, the acute effect of propranolol on both splanchnic and systemic circulations was studied in normal rats and in rats with portal hypertension due to portal vein stenosis. Portal venous pressure significantly decreased during propranolol administration in normal (5.6 +/- 1.0-4.7 +/- 1.1 mm Hg; mean +/- SD) as well as in portal hypertensive rats (11.7 +/- 2.3-10.3 +/- 1.8 mm Hg). Propranolol slightly decreased cardiac output and arterial pressure in all rats. Portal tributary blood flow was significantly reduced by propranolol in normal rats (17.4 +/- 3.0-11.3 +/- 2.2 ml/min) and in portal hypertensive rats (23.7 +/- 5.0-16.6 +/- 3.3 ml/min). Accordingly vascular resistance of the different organs in the portal venous territory increased in these rats receiving propranolol. The percentage of the decrease in portal tributary blood flow was significantly more marked than the percentage of reduction in cardiac output in portal hypertensive rats but, in normal rats, these percentages were parallel. Hepatic arterial blood flow did not change or slightly increased and, consequently, hepatic arterial vascular resistance decreased. These findings further clarify the marked effects of propranolol on splanchnic circulation.     

Likely Introduction Date of Schmallenberg Virus into France According to Monthly Serological Surveys in Cattle

To estimate the date of introduction of Schmallenberg virus (SBV) into France, the prevalence of antibodies against the virus was determined monthly in cattle from two northern departments from August 2011 to April 2012. Seropositive cattle were detected from October 2011 in both departments with a prevalence of 55.6% in the westernmost department (Meurthe‐et‐Moselle) and of 12.7% in the easternmost department (Manche). Schmallenberg virus seroprevalence then increased rapidly to high levels.     

Craniofacial bone atrophy in Parry Romberg syndrome demonstrated using a Bayesian hierarchical model

PurposeParry Romberg syndrome (PRS) is a condition characterized by progressive hemifacial atrophy, predominantly affecting the soft tissues. Associated bone retraction is a common clinical feature of PRS but has never been assessed. Here we used 3D imaging and Bayesian statistics in order to demonstrate and quantify bone atrophy in PRS.Materials and methodsTen non-operated patients with PRS (4/10 males) and 12 age-matched controls (7/12 males) were included into the study. The average age at CT-scan was 9.67 ± 4.13 years for PRS patients and 12.5 ± 4.37 years for controls. Soft and hard tissue atrophy levels were quantified using computed tomography scans, based on the distances between surfaces of the affected side and the non-affected contralateral side, both for the skin and the bone. We used a hierarchical Bayesian model with clinical priors in order to assess the relationship between hard and soft tissue atrophies.ResultsPRS patients had significant hard tissue atrophy, and atrophy extents were similar for soft and hard tissues. There was a trend for a correlation between the extent of hard tissue retraction and the extent of soft tissue retraction, and we could not demonstrate that the relationship between hard and soft tissue retractions was different in PRS and controls.ConclusionOur results indicated that bone atrophy was most probably a primary process rather than a phenomenon secondary to soft tissue retraction. We have provided the first assessment of bone atrophy in PRS patients using Bayesian statistics.