A new score to predict severe respiratory failure and guide anakinra treatment in COVID-19 pneumonia: analysis of the randomized SAVE-MORE trial

Introduction: Anakinra treatment is approved for the treatment of COVID-19 pneumonia in hospitalized adults in need of oxygen and at risk for progression into severe respiratory failure (SRF) defined as circulating concentrations of the biomarker suPAR (soluble urokinase plasminogen activator receptor) >= 6 ng/mL by the EMA and has been authorized for emergency use by FDA under an EUA [1]. This is based on the results of the randomized SAVE-MORE trial where suPAR >= 6 ng/ mL was used to select patients at risk for SRF [2]. The suPAR test is not commercially available in the USA and an alternative method of patient selection was needed. Method(s): In collaboration with the US FDA, an alternative method to select patients most likely to have suPAR >= 6 ng/mL based on commonly measured patient characteristics was developed. Patients with at least 3 of the following criteria are considered likely to have suPAR >= 6 ng/ ml: age >= 75 years, severe pneumonia by WHO criteria, current/previous smoking status, Sequential Organ Failure Assessment score >= 3, neutrophil-to-lymphocyte ratio >= 7, hemoglobin <= 10.5 g/dl, history of ischemic stroke, blood urea >= 50 mg/dl and/or history of renal disease. Result(s): The positive predictive value of this new score was 95.4% in SAVE-MORE population. However, a lower sensitivity meant a small proportion of patients with suPAR >= 6 ng/ml will not be identified by the new score. The adjusted hazard ratio for survival at 60 days for patients meeting this score and who receive anakinra is 0.45 (Fig. 1). Conclusion(s): The developed score predicts accurately patients with suPAR levels >= 6 ng/mL and may be used as an alternative to guide anakinra treatment in patients with COVID-19 pneumonia. Based on these subgroup results, patients in SAVE-MORE who met the new score appeared to show beneficial efficacy results with treatment of anakinra consistent with the overall studied population.

Patients with COVID-19 versus non-COVID-19 community-acquired pneumonia

Background: SARS-CoV-2 has emerged as a novel pathogen of community-acquired pneumonia (CAP). Aims and objectives: We aimed to compare characteristics, clinical outcomes and pneumococcal identification in patients with COVID-19 vs non-COVID-19 CAP. Method(s): EGNATIA is an ongoing, prospective study of adults >=19yo hospitalized with clinical and radiographicallyconfirmed CAP in Greece. The primary objective is to estimate the proportion of CAP due to pneumococcal serotypes included in 13-valent pneumococcal conjugate vaccine (PCV13). Pneumococcus was identified using serotype-specific urinary antigen detection assays (UAD 1/2), BinaxNow and conventional cultures. Testing for SARS-CoV-2 was performed as per national guidelines. Result(s): We compared 202 patients with COVID-19 pneumonia during Apr2020-Mar2021 vs 1033 patients with nonCOVID-19 CAP during Nov2017-Oct2020. Patients with COVID-19 were younger (median age 68.8 vs 75.8 years) and had fewer comorbidities (67.8% with >=1 underlying condition vs 79.2%) than non-COVID-19 patients. Patients with COVID-19 less frequently reported past pneumonia episodes (0.5% vs 7.7%) but were more frequently nursing home residents (13.9% vs 6%). Patients with COVID-19 had less severe pneumonia presentation (CURB 65 3-5 6.4% vs 30.5%;PSI IV-V 41.1% vs 55.2%) but required mechanical ventilation more frequently (7.4% vs 1.9%) and had a longer hospital stay (mean 17.4 vs 9.6 days). In-hospital mortality was similar between the 2 groups (7.9% in COVID-19 vs 8.9% in non-COVID-19). Pneumococcus was identified less frequently in patients with COVID-19 vs non-COVID-19 CAP (4% vs 11.1%). Conclusion(s): Significant differences were identified in patients with COVID-19 vs non-COVID-19 CAP.

A hybrid approach based on dynamic trajectories to predict mortality in COVID-19 patients upon steroids administration

Since the World Health Organization (WHO) has declared Artificial Intelligence (AI) as a powerful tool in the fight against COVID-19, multiple studies have been launched aiming to shed light into risk factors for ICU admission and mortality. None of the existing studies, however, have captured the dynamic trajectories of hospitalized COVID-19 patients who receive steroids nor have explored trajectory-based mortality indicators. In this work, we present a novel, hybrid approach to address this need. Latent Growth Mixture Modelling (LGMM) was used to analyze the trajectories of patients who received steroids. The patients were then grouped into clusters based on the similarity of their dynamic trajectories. State-of-the art machine learning classifiers are trained on the original dataset with and without dynamic trajectories to assess whether their inclusion can enhance the prediction of mortality. Our results highlight the importance of trajectories for predicting mortality in patients who receive steroids yielding 4% and 5% increase in the sensitivity (0.84) and specificity (0.85). The FiO2 and percentage of neutrophils at day 5, along with the percentage of lymphocytes at day 7, were identified as the main causes for mortality in patients who receive steroids, where the SatO2 levels showed significant alterations in the dynamic trajectories. © 2022 IEEE.

Association of patient characteristics with clinical outcomes in a cohort of hospitalised patients with SARS-CoV-2 infection in a Greek referral centre for COVID-19.

Patient-important outcomes related to coronavirus disease 2019 (COVID-19) continue to drive the pandemic response across the globe. Various prognostic factors for COVID-19 severity have emerged and their replication across different clinical settings providing health services is ongoing. We aimed to describe the clinical characteristics and their association with outcomes in patients hospitalised with COVID-19 in the University Hospital of Ioannina. We assessed a cohort of 681 consecutively hospitalised patients with COVID-19 from January 2020 to December 2021. Demographic data, underlying comorbidities, clinical presentation, biochemical markers, radiologic findings, COVID-19 treatment and outcome data were collected at the first day of hospitalisation and up to 90 days. Multivariable Cox regression analyses were performed to investigate the associations between clinical characteristics (hazard ratios (HRs) per standard deviation (s.d.)) with intubation and/or mortality status. The participants' mean age was 62.8 (s.d., 16.9) years and 57% were males. The most common comorbidities were hypertension (45%), cardiovascular disease (19%) and diabetes mellitus (21%). Patients usually presented with fever (81%), cough (50%) and dyspnoea (27%), while lymphopenia and increased inflammatory markers were the most common laboratory abnormalities. Overall, 55 patients (8%) were intubated, and 86 patients (13%) died. There were statistically significant positive associations between intubation or death with age (HR: 2.59; 95% CI 1.52-4.40), lactate dehydrogenase (HR: 1.44; 95% CI 1.04-1.98), pO2/FiO2 ratio < 100 mmHg (HR: 3.52; 95% CI 1.14-10.84), and inverse association with absolute lymphocyte count (HR: 0.54; 95% CI 0.33-0.87). These data might help to identify points for improvement in the management of COVID-19 patients.

Application of a home-based exercise program combined with tele-rehabilitation in previously hospitalized patients with COVID-19: A feasibility, single-cohort interventional study

INTRODUCTION Telehealth for COVID-19 patients is still limited. We aimed to assess the clinical effects of a home-based tele-rehabilitation exercise program following hospital discharge during the first lockdown in Greece, April to July 2020. METHODS A pre-and post-intervention design was applied in two stages. Firstly, patients were instructed to use a specially designed for COVID-19, e-book during four tele-health sessions. Afterwards, a 2-month home-based program consisted of self-practice exercise and one-hour supervised tele-rehabilitation exercise sessions every 10 days, was delivered. At baseline and at the end of the program, participants were interviewed about their physical, psychological status and quality of life (QoL) during the post-hospitalization period. The IPAQ-Gr, the HADS and the SF-36 questionnaires were used, respectively, and the participants were functionally assessed via teleconferences, using the 60 sec Sit to Stand Test (60secSTS), the Short Physical Performance Battery (SPPB) and the 3 min Step Test (3MST). RESULTS Seventy-four patients, median age 52.5 (IQR: 43–61) years were included at the first stage. From those, only 22 patients, mean ± SD age 50.1 ± 13.2 years completed the 2-month exercise program. The training program was well tolerated by all 22 patients. The mean number of unsupervised exercise sessions was 18.4 ± 3.5. No adverse effects were observed either during initial and follow-up assessment via tele-communication or during home-exercise sessions. Training improved significantly (p<0.001) lower limb muscle performance [median (IQR) 60secSTS: 22 (20–26) to 31 (25–36)], anxiety [median (IQR) HADS: 9 (6–13) to 4.3 (3.2–9.6)], depression [median (IQR) HADS: 5 (3–8) to 1.8 (0.9–3.7)], QoL [mean ± SD SF-36pcs: 37.5 ± 10.3 to 52.1 ± 6, and mean ± SD SF-36mcs: 42.9 ± 11.6 to 45.5 ± 12.3]. CONCLUSIONS Tele-rehabilitation may be feasible and may improve physical and psychological status of COVID-19 patients after hospital discharge. © 2022 Kortianou E. et al.

Baseline characteristics and outcome predictors in patients hospitalized with COVID-19 in the University General Hospital of Ioannina, Greece

INTRODUCTION The novel Severe Acute Respiratory Syndrome Coronavirus-2, which causes the coronavirus disease COVID-19, is a highly infectious viral pathogen that is responsible for the ongoing pandemic. The aim of the present study was to illustrate the pre-hospitalization baseline characteristics and comorbidities of patients admitted with COVID-19 and their association with patient outcomes. METHODS This was a retrospective observational study of consecutive patients who were admitted to the COVID-19 departments of the University General Hospital of Ioannina, Greece (March 2020 - August 2021). Patients' demographic data, chronic disease medication use, and comorbidities were recorded upon their admission. RESULTS A total of 627 patients were hospitalized with mean age 62.5 years, 65.2% with at least one comorbidity, and 43.1% female. The median hospitalization duration was 11 days;554 (88.4%) of the patients were discharged and the mortality rate was 11.6%. Older age, admission during the second pandemic wave, arterial hypertension, and diabetes mellitus were associated with longer hospitalization. In multivariate analyses, cardiovascular disease was an independent predictor of hospitalization length (OR=1.834;95% CI: 1.039-3.228), whereas age (HR=1.079;95% CI: 1.045-1.115), history of malignancy (HR=1.246;95% CI: 1.002-1.595), and a diagnosis of COPD (HR=1.989;95% CI: 1.025-7.999) remained the independent mortality predictors. CONCLUSIONS Our data highlight the effect of COPD and malignancy on mortality risk in COVID-19 patients and the association of cardiovascular disease with a longer hospitalization.

Clinical and Radiologic Improvement following Tocilizumab Administration in Patients with SARS-CoV-2

Cytokine release syndrome and acute respiratory distress syndrome are the major complications of coronavirus disease 2019 (COVID-19) and tocilizumab has shown efficacy in this setting. We report on 2 severely ill patients with COVID-19 treated with tocilizumab within 7 to 10 days of onset of symptoms. Tocilizumab markedly improved their clinical condition and was associated with regression of abnormalities on chest computed tomography within 1 week of tocilizumab administration. © 2020 Wolters Kluwer Health, Inc. All rights reserved.