ABSTRACT
Background In patients with COVID-19 and baseline soluble urokinase plasminogen receptor plasma (suPAR) levels [≥] 6ng/mL, early administration of anakinra, a recombinant interleukin-1 receptor antagonist, may prevent disease progression and death. In case of suPAR testing unavailability, the Severe COvid Prediction Estimate (SCOPE) score may be used as an alternative in guiding treatment decisions. Methods We conducted a monocenter, retrospective cohort study, including patients with SARS-CoV2 infection and respiratory failure. Patients treated with anakinra (anakinra group, AG) were compared to two control groups of patients who did not receive anakinra, respectively with [≥] 6 ng/mL (CG1) and < 6 ng/mL (CG2) baseline suPAR levels. Controls were paired by age, sex, date of admission and vaccination status. Primary endpoint of the study was disease progression at day 14 from admission, as defined by patient distribution on a simplified version of the 11-point World Health Organization Clinical Progression Scale (WHO-CPS). Results Between July, 2021 and January, 2022, 153 patients were included, among which 56 were treated with off-label anakinra, 49 retrospectively fulfilled prescriptive criteria for anakinra and were assigned to CG1, and 48 presented with suPAR levels < 6ng/mL and were assigned to CG2. At day 14, when comparing to CG1, patients who received anakinra had significantly reduced odds of progressing towards worse clinical outcome both in ordinal regression analysis (OR 0.25, 95% CI 0.11-0.54, p<0.001) and in multivariable analysis (OR 0.19, 95% CI 0.03-0.82, p=0.037), and these results were confirmed even when controlling for age, sex, BMI and vaccinal status. Sensitivities of baseline suPAR and SCOPE score in predicting progression towards severe disease or death at day 14 were similar (83% vs 100%, p=0.59). Conclusion This real-word, retrospective cohort study confirmed the safety and the efficacy of suPAR-guided, early use of anakinra in hospitalized COVID-19 patients with respiratory failure.
Subject(s)
Severe Acute Respiratory Syndrome , Death , COVID-19 , Respiratory InsufficiencyABSTRACT
BackgroundThe COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters, potentially available at home, to help identifying patients with COVID-19 who are at higher risk of death.MethodsThe training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020 to November 5, 2020. Afterwards, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020 to February 5 2021. The primary outcome was in-hospital mortality.The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of 5-fold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48 hours after the baseline measurement was plotted against its baseline value.ResultsAmong the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the 5-fold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n=1463) in which the mortality rate was 22.6 %. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk score group), the mortality rate was 1.6%, 17.8% in the second and third quartile (high-risk score group) and 53.5% in the fourth quartile (very high-risk score group). The three risk score groups showed good discrimination for the P/F value at admission, and a positive correlation was found for the low-risk class to P/F at 48 hours after admission (adjusted R-squared= 0.48).ConclusionsWe developed a predictive model of death for people with SARS-CoV-2 infection by including only easy-to-obtain variables (abnormal blood count, BUN, C-reactive protein, sodium and lower SpO2). It demonstrated good accuracy and high power of discrimination. The simplicity of the model makes the risk prediction applicable for patients at home, in the Emergency Department, or during hospitalization.
Subject(s)
COVID-19ABSTRACT
IntroductionAntibody response play a fundamental role in the natural history of infectious disease. A better understanding of the immune response in patients with SARS-CoV-2 infection could be important for identifying patients at greater risk of developing a more severe form of disease and with a worse prognosis. MethodsWe performed a cross-sectional analysis to determine the presence and the levels of both anti-SARS-CoV-2 IgG and IgA in a cohort of hospitalized patients with confirmed infection at different times in the natural history of the disease. Patients enrolled when admitted at the emergency department were prospectively followed up during hospital stay. ResultsOverall, 131 patients were considered with a total of 237 samples processed. Cross-sectional analysis showed that seroconversion for IgA seems to occur between days 5 and 15 while IgG response seems to occur slightly later, peaking at day 20 after symptoms onset. Both IgA and IgG were maintained beyond two months. Severe patients showed a higher IgA response compared with mild patients when analyzing optical density (8.3 versus 5.6, p < 0.001). Prospective analysis conducted on 55 patients confirmed that IgA appear slightly earlier than IgG. After stratifying for the severity of disease, both the IgA and IgG response was more vigorous in severe cases. Moreover, while IgG tended to stabilize, there was a relevant decline after the first month of IgA levels in mild cases. ConclusionIgA and IgG antibody response is closely related although seroconversion for IgA occurs earlier. Both IgA and IgG are maintained beyond two months. Severe patients showed a more vigorous IgA and IgG response. IgA levels seem to decline after one month since the onset of symptoms in mild cases.
Subject(s)
COVID-19ABSTRACT
In the face of the rapid evolution of the COVID-19 pandemic, healthcare professionals on the frontline are in urgent need of frequent updates in the accomplishment of their practice. Hence, clinicians started to search for prompt, valid information on sources parallel to academic journals publications. Aim of this work is to investigate the extent of this phenomenon. We administered an anonymous online cross-sectional survey to 645 Italian clinicians. 369 questionnaires were returned. 19,5% (n=72) of respondents were younger than 30 years-old; 49,3% (n=182) worked in Infectious Diseases, Internal Medicine or Respiratory Medicine departments, 11.5% (n=42) in Intensive Care Unit and 7.4% (n=27) were general practitioner. 70% (n=261) of respondents reported that their use of social media to seek medical information increased during the pandemic. 39.3% (n = 145) consistently consulted Facebook groups and 53.1% (n = 196) Whatsapp chats. 47% (n = 174) of respondents reported that information shared on social media had a consistent impact on their daily practice. In the present study, we found no difference in social media usage between age groups or medical specialties. Given the urgent need for scientific update in face of the present health emergency, these findings may help understanding how clinicians access new evidences and implement them in their daily practice.
Subject(s)
COVID-19 , Communicable DiseasesABSTRACT
Importance: Interleukin-6 signal blockade has shown preliminary beneficial effects in treating aberrant host inflammatory response against SARS-CoV-2 leading to severe respiratory distress. Objective: to describe the effect of off-label intravenous use of Sarilumab in patients with severe SARS-CoV-2-related pneumonia. Design: Observational clinical cohort study. Setting: Fondazione Policlinico Universitario A. Gemelli IRCCS as Italian Covid reference center. Participants: Patients with laboratory-confirmed SARS-CoV-2 infection and respiratory distress with PaO2/FiO2 ratio<300 treated with Sarilumab between March 23rd - April 4th, 2020. Date of final follow-up was April 18, 2020. Main outcomes and measures: We describe the clinical outcomes of 53 patients with SARS-CoV-2 severe pneumonia treated with intravenous Sarilumab in terms of pulmonary function improvement or Intensive Care Unit (ICU) admission rate in medical wards setting and of live discharge rate in ICU treated patients as well as in terms of safety. Each patient received Sarilumab 400 mg administered intravenously on day 1, with eventual additional infusion based on clinical judgement, and was followed for at least 14 days, unless previously discharged or dead. No gluco-corticosteroids were used at baseline. Results: Of the 53 SARS-CoV-2pos patients receiving Sarilumab, 39 (73.6%) were treated in medical wards (66.7% with a single infusion) while 14 (26.4%) in ICU (92.6% with a second infusion). The median PaO2/FiO2 of patients in the Medical Ward was 146(IQR:120-212) while the median PaO2/FiO2 of patients in ICU was 112(IQR:100-141.5), respectively. Within the medical wards, 7(17.9%) required ICU admission, 4 of whom were re-admitted to the ward within 5-8 days. At 19 days median follow-up, 89.7% of medical inpatients significantly improved (46.1% after 24 hours, 61.5% after 3 days), 70.6% were discharged from the hospital and 85.7% no longer needed oxygen therapy. Within patients receiving Sarilumab in ICU, 64.2% were discharged from ICU to the ward and 35.8% were still alive at the last follow-up. Overall mortality rate was 5.7% after Sarilumab administration: 1(2.5%) patient died in the Medical Ward whilst 2(14.2%) patients died in ICU, respectively. Conclusions and relevance: IL6-R inhibition appears to be a potential treatment strategy for severe SARS-CoV-2 pneumonia and intravenous Sarilumab seems a promising treatment approach showing, in the short term, an important clinical benefit and good safety.