Application of machine learning approach in emergency department to support clinical decision making for SARS-CoV-2 infected patients

Abstract To support physicians in clinical decision process on patients affected by Coronavirus Disease 2019 (COVID-19) in areas with a low vaccination rate, we devised and evaluated the performances of several machine learning (ML) classifiers fed with readily available clinical and laboratory data. Our observational retrospective study collected data from a cohort of 779 COVID-19 patients presenting to three hospitals of the Lazio-Abruzzo area (Italy). Based on a different selection of clinical and respiratory (ROX index and PaO2/FiO2 ratio) variables, we devised an AI-driven tool to predict safe discharge from ED, disease severity and mortality during hospitalization. To predict safe discharge our best classifier is an RF integrated with ROX index that reached AUC of 0.96. To predict disease severity the best classifier was an RF integrated with ROX index that reached an AUC of 0.91. For mortality prediction the best classifier was an RF integrated with ROX index, that reached an AUC of 0.91. The results obtained thanks to our algorithms are consistent with the scientific literature an accomplish significant performances to forecast safe discharge from ED and severe clinical course of COVID-19

Modeling the contribution of male testosterone levels to the duration of positive COVID testing among hospitalized male COVID-19 patients

Background: A growing body of evidence is emerging suggesting testosterone can affect all cells involved in the immune response to both bacterial and viral infections, and the testosterone effect on the immune response could explain the greater susceptibility of men to infections including COVID-19. We aimed to explore the predictive role of male serum total testosterone (TT) levels on the time till viral negativity testing among hospitalized COVID-19 patients. Methods: The univariate effect of risk factors for the duration of COVID-19 viral positivity was evaluated using the log-rank test and Kaplan-Meier estimates. A multivariable Cox regression model was developed to test the role of TT levels and the subsequent odds for shorter viral positivity intervals. Results: Increasing serum TT levels and the need for an oxygen administration strategy were independently predictive for respectively reduced and increased days to negativization (Hazard Ratio [HR]: 1.39, 95% CI: 0.95-2.03 and HR: 0.19, 95% CI: 0.03-1.18). Conclusion: Baseline higher TT levels for male COVID-19 patients at hospital admission are associated with shorter durations of positive COVID-19 testing and thus viral clearance. Our preliminary findings might play a relevant to help pandemic control strategies if these will be verified in future larger multicentric and possibly randomized trials

Multiple sclerosis-disease modifying therapies affect humoral and T-cell response to mRNA COVID-19 vaccine

The mRNA vaccines help protect from COVID-19 severity, however multiple sclerosis (MS) disease modifying therapies (DMTs) might affect the development of humoral and T-cell specific response to vaccination

Blood biomarkers from the emergency department disclose severe omicron covid-19-associated outcomes

Background: Since its outbreak, Coronavirus disease 2019 (COVID-19), a life-threatening respiratory illness, has rapidly become a public health emergency with a devastating social impact. Lately, the Omicron strain is considered the main variant of concern. Routine blood biomarkers are, indeed, essential for stratifying patients at risk of severe outcomes, and a huge amount of data is available in the literature, mainly for the previous variants. However, only a few studies are available on early routine biochemical blood biomarkers for Omicron-afflicted patients. Thus, the aim and novelty of this study were to identify routine blood biomarkers detected at the emergency room for the early prediction of severe morbidity and/or mortality. Methods: 449 COVID-19 patients from Sapienza University Hospital of Rome were divided into four groups: (1) the emergency group (patients with mild forms who were quickly discharged); (2) the hospital ward group (patients that after the admission in the emergency department were hospitalized in a COVID-19 ward); (3) the intensive care unit (ICU) group (patients that after the admission in the emergency department required intensive assistance); (4) the deceased group (patients that after the admission in the emergency department had a fatal outcome). Results: ANOVA and ROC data showed that high-sensitivity troponin-T (TnT), fibrinogen, glycemia, C-reactive protein, lactate dehydrogenase, albumin, D-dimer myoglobin, and ferritin for both men and women may predict lethal outcomes already at the level of the emergency department. Conclusions: Compared to previous Delta COVID-19 parallel emergency patterns of prediction, Omicron-induced changes in TnT may be considered other early predictors of severe outcomes

High Risk of Secondary Infections Following Thrombotic Complications in Patients With COVID-19

Background. This study’s primary aim was to evaluate the impact of thrombotic complications on the development of secondary infections. The secondary aim was to compare the etiology of secondary infections in patients with and without thrombotic complications. Methods. This was a cohort study (NCT04318366) of coronavirus disease 2019 (COVID-19) patients hospitalized at IRCCS San Raffaele Hospital between February 25 and June 30, 2020. Incidence rates (IRs) were calculated by univariable Poisson regression as the number of cases per 1000 person-days of follow-up (PDFU) with 95% confidence intervals. The cumulative incidence functions of secondary infections according to thrombotic complications were compared with Gray’s method accounting for competing risk of death. A multivariable Fine-Gray model was applied to assess factors associated with risk of secondary infections. Results. Overall, 109/904 patients had 176 secondary infections (IR, 10.0; 95% CI, 8.8–11.5; per 1000-PDFU). The IRs of secondary infections among patients with or without thrombotic complications were 15.0 (95% CI, 10.7–21.0) and 9.3 (95% CI, 7.9–11.0) per 1000-PDFU, respectively (P = .017). At multivariable analysis, thrombotic complications were associated with the development of secondary infections (subdistribution hazard ratio, 1.788; 95% CI, 1.018–3.140; P = .043). The etiology of secondary infections was similar in patients with and without thrombotic complications. Conclusions. In patients with COVID-19, thrombotic complications were associated with a high risk of secondary infections

Liver involvement in a large cohort of patients with hereditary hemorrhagic telangiectasia: Echo-color-Doppler vs multislice computed tomography study

Background/Aims: Hepatic arterio-venous malformations (HAVMs) have been found in 74% of hereditary hemorrhagic telangiectasia (HHT) patients with multislice CT (MSCT). This single-blind study aimed to compare the diagnostic accuracy of echo-color-Doppler with MSCT and identify the most sensitive ultrasound criteria indicating hepatic shunts. Methods: One hundred and fifty-three HHT patients were systematically screened for HAVMs by biological tests, abdominal MSCT and echo-color-Doppler. Twenty-five normal subjects and 15 cirrhotic patients were also included as control groups. Both intrahepatic ("color spots" and hypervascularization) and extrahepatic parameters (diameter, flow velocity and tortuosity of hepatic artery and diameter and flow velocity of portal/hepatic vein) were utilized. "Color-spots" are defined as subcapsular vascular spots with a high-velocity arterial blood flow and low resistivity index and can identify extremely small HAVMs. Results: CT was positive in 128/153 (84%) patients and Doppler color spots were found in 131/153 (86%) patients. The sensitivity, specificity and diagnostic accuracy of "color spots" compared to MSCT were 95.3%, 68.0% and 91.8%, respectively. The "color-spot" showed a greater correlation to CT (V-index = 0.655; p < 0.0001) than extrahepatic criteria (V = 0.317). In 20/29 (69%) subjects, echo-color-Doppler, confirmed by CT, identified the third criterion for definite HHT diagnosis. Conclusions: Intrahepatic criteria was superior to extrahepatic criteria for identification of HAVMs. A new Doppler parameter ("color-spots") with an optimal accuracy for detecting HAVMs is proposed for easy periodic screening of HHT patients. (C) 2008 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved

Early IgG / IgA response in hospitalized COVID-19 patients is associated with a less severe disease

We determined the kinetics of anti-SARS-CoV-2 antibody response in fifteen hospitalized COVID-19 patients. Patients were divided into mild/moderate (mild, n=1; moderate, n=4) or severe (n=10) and virus-specific anti-Nucleocapsid IgM, anti-Spike IgG and anti-Spike IgA were measured in serial serum samples collected 0-15 days after hospital admission. Surrogate neutralization assays were performed by testing inhibition of ACE-2 binding to Spike. In three patients (2 severe and 1 moderate case), serum antibodies and T-cell memory were monitored six months after baseline. Although IgM response tended to appear first, patients affected by less severe disease were more prone to an early IgG/IgA response. Neutralization of Spike binding to ACE2 correlated with anti-Spike IgG and IgA. IgG and IgA antibody response persisted at the six months follow-up. A recall T-cell response to the Spike antigen was observed in two out of three patients, not related to disease severity

Tocilizumab effects in COVID-19 pneumonia: role of CT texture analysis in quantitative assessment of response to therapy

Purpose: To evaluate CT and laboratory changes in COVID-19 patients treated with tocilizumab, compared to a control group, throughout a combined semiquantitative and texture analysis of images. Materials and methods: From March 11 to April 20, 2020, 57 SARS-CoV-2 positive patients were retrospectively compared: group T (n = 30) receiving tocilizumab and group non-T (n = 27) undergoing only antivirals/antimalarials. Chest-CT and laboratory findings were analyzed before and after treatment. CT evaluation included both semiquantitative scoring and texture analysis of all parenchymal lesions. Survival and recovery analyses were also provided with Kaplan-Meier method. Results: In group T, no significant differences were found for CT score after treatment, while several texture features significantly changed, including mean attenuation (p &lt; 0.0001), skewness (p &lt; 0.0001), entropy (p = 0.0146) and higher-order parameters, suggesting considerable fading of parenchymal lesions. PaO2/FiO2 mean value significantly increased after treatment, from 240 ± 93 to 363 ± 107 (p = 0.0003), with parallel decrease in inflammatory biomarkers (CRP, D-dimer and LDH). In group non-T, CT scoring, texture and laboratory parameters showed significant worsening at follow-up. Findings were clinically associated with opposite trends between two groups, with reduction of severe cases in group T (from 21/30 to 5/30; p &lt; 0.0001) as compared to a significant worsening in group non-T (severe cases increasing from 6/27 to 14/27; p = 0.0473). Probability of discharge was significantly higher in group T (p &lt; 0.0001), as well as survival rate, although not statistically significant. Conclusions: Our results suggest the potential role of CT texture analysis for assessing response to treatment in COVID-19 pneumonia, using Tocilizumab, as compared to semiquantitative evaluation, providing insight into the intrinsic parenchymal changes

Interplay between male testosterone levels and the risk for subsequent invasive respiratory assistance among COVID-19 patients at hospital admission

testosterone serum levels as predictors of severe respiratory progression in COVID-19 patient