Sars-Cov 2 versus Flu: ECMO-associated bloodstream infections.

SARS-CoV-2 and flu may lead to severe acute respiratory distress syndrome (ARDS) requiring extracorporeal membrane oxygenation (ECMO). The aim of the present study is to compare the incidence of bloodstream infections (BSIs) and outcome in patients with flu and SARS-CoV-2 infection hospitalized in ICU and undergoing ECMO. This study is a retrospective analysis of the San Matteo COVID-19 Registry (SMACORE) cohort. The study was conducted from January 2018 to April 2020. Demographic data and microbiological data were recorded during hospitalization. BSIs occurring during ECMO were analyzed. Eighteen patients treated with ECMO, 22 subjects with SARS-CoV-2 infection and 7 with flu, median age 61years for SARS-CoV-2 and 50 for flu (p=NS). Median ECMO duration was similar in the two pathologies. Median time to bloodstream infection from ECMO initiation was similar. Bloodstream infection incidence rate was 2.65 per 100 patients/days for flu and 2.2 per 100 patients/days for SARS-CoV-2. Global infection rate was 5 per 100 patients/days for SARS-CoV-2 patients and 5.3 per 100 patients/days for flu. Mortality during ECMO was 40.9% (5 out of 22 patients) for SARS-CoV-2 infection while none died among flu patients. ECMO-associated mortality was higher in SARS-CoV-2 infection compared with flu infection.

The obesity paradox: Analysis from the SMAtteo COvid-19 REgistry (SMACORE) cohort.

BACKGROUND AND AIMS: Obesity has been suggested as a possible risk factor for a more severe course of COVID-19; however, conclusive evidence is lacking and few studies have investigated the role of BMI as a risk factor for admission to intensive care unit (ICU) and mortality. We retrospectively analyzed a COVID-19 cohort recruited during the first 40 days of the epidemic in Italy. We examined the association between obesity and 30-day mortality, admission to ICU, mortality and length of hospital stay in patients with COVID-19. METHODS AND RESULTS: Demographic, clinical and outcome data were retrospectively analyzed in 331 patients with COVID-19 admitted to hospital between 21 February and 31 March 2020. The predictive effect of obesity on mortality was assessed using a Cox proportional-hazard regression model, its effect on ICU admission and mortality in the ICU using logistic regressions, and its effect on length of hospital stay using a linear regression. Seventy-four of 331 patients had a BMI ≥30 kg/m2. Among obese patients, 21 (28.4%) required admission in ICU and 25 died (33.8%). After controlling for sex, age, comorbidities and clinical data, obesity was not significantly associated with mortality, mortality in ICU and length of hospital stay. The effect of obesity on ICU admission remained significant after controlling for sex, age, interstitial lung disease, heart disease and serum C-reactive protein. CONCLUSIONS: Obese patients with COVID-19 were more likely to be admitted to ICU than non-obese patients. However, there were no significant differences in mortality between the two groups.

Dynamic NLR and PLR in Predicting COVID-19 Severity: A Retrospective Cohort Study.

INTRODUCTION: The hyperinflammation phase of severe SARS-CoV-2 is characterised by complete blood count alterations. In this context, the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR) can be used as prognostic factors. We studied NLR and PLR trends at different timepoints and computed optimal cutoffs to predict four outcomes: use of continuous positive airways pressure (CPAP), intensive care unit (ICU) admission, invasive ventilation and death. METHODS: We retrospectively included all adult patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia admitted from 23 January 2020 to 18 May 2021. Analyses included non-parametric tests to study the ability of NLR and PLR to distinguish the patients' outcomes at each timepoint. Receiver operating characteristic (ROC) curves were built for NLR and PLR at each timepoint (minus discharge) to identify cutoffs to distinguish severe and non-severe disease. Their statistical significance was assessed with the chi-square test. Collection of data under the SMACORE database was approved with protocol number 20200046877. RESULTS: We included 2169 patients. NLR and PLR were higher in severe coronavirus disease 2019 (COVID-19). Both ratios were able to distinguish the outcomes at each timepoint. For NLR, the areas under the receiver operating characteristic curve (AUROC) ranged between 0.59 and 0.81, and for PLR between 0.53 and 0.67. From each ROC curve we computed an optimal cutoff value. CONCLUSION: NLR and PLR cutoffs are able to distinguish severity grades and mortality at different timepoints during the course of disease, and, as such, they allow a tailored approach. Future prospects include validating our cutoffs in a prospective cohort and comparing their performance against other COVID-19 scores.