Predictors of poor outcome in tocilizumab treated patients with Sars-CoV-2 related severe respiratory failure: A multicentre real world study.

INTRODUCTION: Despite Tocilizumab is now recognized as a concrete therapeutic option in patients with severe SARS-CoV-2 related respiratory failure, literature lacks about factors influencing the response to it in this context. Therefore, the aim of our study was to provide evidence about predictors of poor outcome in Tocilizumab treated patients in the real-world practice. MATERIALS AND METHODS: We retrospectively analyzed clinical, laboratory and chest computer tomography (CCT) data of patients firstly admitted in non Intensive Care Units (ICU) and suffering from severe respiratory failure, who were treated with the IL-6 antagonist Tocilizumab. We compared patients who died and/or required admission to ICU with oro-tracheal intubation (OTI) with those who did not. RESULTS: Two hundreds and eighty-seven patients (29.9% females) with mean age ± SD 64.1 ± 12.6 years were the study population. In-hospital mortality was 18.8%, while the composite endpoint in-hospital mortality and/or ICU admission with OTI occurred in 23.7%. At univariate analysis, patients who died and/or were admitted to ICU with OTI were significantly older and co-morbid, had significantly higher values of creatinine, C-reactive protein (CRP) and procalcitonin and lower lymphocytes count, PaO2/FiO2 ratio (P/F) and room air pulsossimetry oxygen saturation (RAO2S) at hospital admission. Computed tomography ground glass opacities (CT-GGO) involving the pulmonary surface ≥ 50% were found in 55.4% of patients who died and/or were admitted to ICU with OTI and in 21.5% of patients who did not (p=0.0001). At multivariate analysis, age ≥ 65 years (OR 17.3, 95% CI: 3.7-81.0), procalcitonin ≥ 0.14 (OR 9.9, 95%CI: 1.7-56.1), RAO2S ≤ 90% (OR 4.6, 95%CI: 1.2-17.0) and CCT-GGO involvement ≥ 50% (OR 5.1, 95%CI: 1.2-21.0) were independent risk factors associated with death and/or ICU admission with OTI. CONCLUSION: Tocilizumab has shown to improve outcome in patients with severe respiratory failure associated to SARS-CoV-2 related pneumonia. In our multicentre study focusing on Tocilizumab treated severe COVID-19 patients, age ≥ 65 years, procalcitonin ≥ 0.14 ng/mL, RAO2S ≤ 90% and CCT-GGO involvement ≥ 50% were independent factors associated with poor outcome.

The incremental value of computed tomography of COVID-19 pneumonia in predicting ICU admission.

Triage is crucial for patient's management and estimation of the required intensive care unit (ICU) beds is fundamental for health systems during the COVID-19 pandemic. We assessed whether chest computed tomography (CT) of COVID-19 pneumonia has an incremental role in predicting patient's admission to ICU. We performed volumetric and texture analysis of the areas of the affected lung in CT of 115 outpatients with COVID-19 infection presenting to the emergency room with dyspnea and unresponsive hypoxyemia. Admission blood laboratory including lymphocyte count, serum lactate dehydrogenase, D-dimer and C-reactive protein and the ratio between the arterial partial pressure of oxygen and inspired oxygen were collected. By calculating the areas under the receiver-operating characteristic curves (AUC), we compared the performance of blood laboratory-arterial gas analyses features alone and combined with the CT features in two hybrid models (Hybrid radiological and Hybrid radiomics)for predicting ICU admission. Following a machine learning approach, 63 patients were allocated to the training and 52 to the validation set. Twenty-nine (25%) of patients were admitted to ICU. The Hybrid radiological model comprising the lung %consolidation performed significantly (p = 0.04) better in predicting ICU admission in the validation (AUC = 0.82; 95% confidence interval 0.73-0.97) set than the blood laboratory-arterial gas analyses features alone (AUC = 0.71; 95% confidence interval 0.56-0.86). A risk calculator for ICU admission was derived and is available at: https://github.com/cgplab/covidapp . The volume of the consolidated lung in CT of patients with COVID-19 pneumonia has a mild but significant incremental value in predicting ICU admission.