The impact of body composition on mortality of COVID-19 hospitalized patients: A prospective study on abdominal fat, obesity paradox and sarcopenia.

BACKGROUND & AIMS: Obesity has been described as a predisposing risk factor to severe forms of COVID-19, but conflicting results are emerging on its real impact on the mortality of COVID-19. We aimed to compare clinical outcomes and mortality among COVID-19 patients according to obesity, metabolic syndrome and adiposity distribution. METHODS: We conducted a prospective observational study of all consecutive adult patients with a confirmed diagnosis of SARS-CoV-2 infection admitted to the Infectious Diseases Clinic at Udine Hospital, Italy, from January 2021 to February 2021. At admission, the study population was submitted to specific anthropometric, laboratory and bioimpedance analysis (BIA) measurements and divided into five groups according to: 1) BMI < or >30 kg/m2; 2) waist circumference (WC) < or >98 cm for women, < or >102 cm for men; 3) presence or absence of metabolic syndrome (MS); 4) visceral adipose tissue (VAT) distribution; and 5) presence or absence of sarcopenia (SP) both based on BIA. We then compared clinical outcomes (ventilatory support, intensive care unit (ICU) admission, ICU length of stay, total hospital length of stay and mortality), immune and inflammatory makers and infectious and non-infectious acute complications within the five groups. RESULTS: A total of 195 patients were enrolled in the study. The mean age of patients was 71 years (IQR 61-80) and 64.6% (126) were male. The most common comorbidities were hypertension (55.9%) and MS (55.4%). Overall mortality was 19.5%. Abdominal adiposity, measured both with WC and with BIA, and SP were significantly associated with need for increased ventilator support (p = 0.013 for WC; p = 0.037, 0.027 and 0.009 for VAT; p = 0.004 and 0.036 for FMI; and p = 0.051 for SP), but not with ICU admission (WC p = 0.627, VAT p = 0.153, FMI p = 0.519 and SP p = 0.938), length of stay (WC p = 0.345, VAT p = 0.650, FMI p = 0.159 and SP p = 0.992) and mortality (WC p = 0.277, VAT p = 0.533, FMI p = 0.957 and SP p = 0.211). Obesity and MS did not discriminate for the intensity of ventilatory outcome (p = 0.142 and p = 0.198, respectively), ICU admission (p = 0.802 and p = 0.947, respectively), length of stay (p = 0.471 and p = 0.768, respectively) and mortality (p = 0.495 and p = 0.268, respectively). We did not find significant differences in inflammatory markers and secondary complications within the five groups. CONCLUSIONS: In patients admitted with COVID-19, increased WC, visceral abdominal fat and SP are associated with higher need for ventilatory support. However, obesity, MS, SP and abdominal adiposity are not sensitive predictive factors for mortality.

Cytokines from Bench to Bedside: A Retrospective Study Identifies a Definite Panel of Biomarkers to Early Assess the Risk of Negative Outcome in COVID-19 Patients.

The main aim of this study was to identify the most relevant cytokines which, when assessed in the earliest stages from hospital admission, may help to select COVID-19 patients with worse prognosis. A retrospective observational study was conducted in 415 COVID-19 patients (272 males; mean age 68 ± 14 years) hospitalized between May 2020 and March 2021. Within the first 72 h from hospital admission, patients were tested for a large panel of biomarkers, including C-reactive protein (CRP), Mid-regional proadrenomedullin (MR-proADM), Interferon-γ, interleukin 6 (IL-6), IL-1ß, IL-8, IL-10, soluble IL2-receptor-α (sIL2Rα), IP10 and TNFα. Extensive statistical analyses were performed (correlations, t-tests, ranking tests and tree modeling). The mortality rate was 65/415 (15.7%) and a negative outcome (death and/or orotracheal intubation) affected 98/415 (23.6%) of cases. Univariate tests showed the majority of biomarkers increased in severe patients, but ranking tests helped to select the best variables to put on decisional tree modeling which identified IL-6 as the first dichotomic marker with a cut-off of 114 pg/mL. Then, a good synergy was found between IL-10, MR-proADM, sIL2Rα, IP10 and CRP in increasing the predictive value in classifying patients at risk or not for a negative outcome. In conclusion, beside IL-6, a panel of other cytokines representing the degree of immunoparalysis and the anti-inflammatory response (IP10, sIL2Rα and IL-10) showed synergic role when combined to biomarkers of systemic inflammation and endothelial dysfunction (CRP, MR-proADM) and may also better explain disease pathogenesis and suggests targeted intervention.

Validation of a One-Step Reverse Transcription-Droplet Digital PCR (RT-ddPCR) Approach to Detect and Quantify SARS-CoV-2 RNA in Nasopharyngeal Swabs.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has rapidly spread worldwide from the beginning of 2020. Quantitative reverse transcription-PCR (RT-qPCR) is, to this day, the preferred methodology for viral RNA detection, even if not without problems. To overcome some of the limitations still existing for the detection and quantification of nucleic acids in various applications, the use of one-step reverse transcription-droplet digital PCR (RT-ddPCR) has been established. The purpose of this study was, then, to evaluate the efficacy of ddPCR for the detection of SARS-CoV-2 RNA in nasopharyngeal swabs, optimizing the detection of low-viral load-burdened samples. METHODS: The RT-ddPCR workflow was validated for sensitivity, specificity, linearity, reproducibility, and precision using samples from 90 COVID-19-infected patients referred to the Department of Laboratory Medicine of the University Hospital of Udine (Italy). RESULTS: The present study shows that RT-ddPCR allows the detection of as low as 10.3 copies of a SARS-COV-2 E-gene per sample with a higher level of accuracy and precision, especially at low concentration. CONCLUSION: During the postpeak phase of the SARS-CoV-2 pandemic, it is essential to rely on a highly robust molecular biology method to identify infected subjects, whether they have symptoms or not, in order to prepare appropriate containment measures.

Interleukin 6, soluble interleukin 2 receptor alpha (CD25), monocyte colony-stimulating factor, and hepatocyte growth factor linked with systemic hyperinflammation, innate immunity hyperactivation, and organ damage in COVID-19 pneumonia.

BACKGROUND: Patients infected by SARS-CoV-2 can develop interstitial pneumonia, requiring hospitalisation or mechanical ventilation. Increased levels of inflammatory biomarkers are associated with development of acute respiratory distress syndrome (ARDS). The aim of the present study was to determine which cytokines are associated with respiratory insufficiency in patients hospitalised for COVID-19. PATIENTS AND METHODS: Data on 67 consecutive patients were collected between March 8 and March 30, 2020. PaO2/FiO2 ratio (P/F) was calculated at hospital admission. The following cytokines were analysed: interleukin (IL)-6, IL-1α, IL-18, tumour necrosis factor (TNF)-ß, macrophage colony-stimulating factor (M-CSF), macrophage migration inhibitory factor (MIF), soluble IL-2 receptor alpha (sIL-2Rα; CD25), IL-12ß, IL-3, interferon (IFN) α2a, monokine induced by gamma interferon (MIG), monocyte-chemotactic protein 3 (MCP3) and hepatocyte growth factor (HGF). RESULTS: P/F lower than 300 was recorded in 22 out of 67 patients (32.8%). P/F strongly correlated with IL-6 (r = -0.62, P < 0.0001), M-CSF (r = -0.63, P < 0.0001), sIL-2Rα (r = -0.54, P < 0.0001), and HGF (r = -0.53, P < 0.0001). ROC curve analyses for IL-6 (AUC 0.83, 95% CI 0.73-0.93, P < 0.0001), M-CSF (AUC 0.87, 95% CI 0.79-0.96, P < 0.0001), HGF (AUC 0.81, 95% CI 0.70-0.93, P < 0.0001), and sIL-2Rα (AUC 0.80, 95% CI, 0.69-0.90, P < 0.0001) showed that these four soluble factors were highly significant. All four soluble factors correlated with LDH, white blood cell count, neutrophil count, lymphocyte count, and CRP. CONCLUSION: IL-6, M-CSF, sIL-2Rα, and HGF are possibly involved in the main biological processes of severe COVID-19, mirroring the level of systemic hyperinflammatory state, the level of lung inflammation, and the severity of organ damage.

A Streamlined Approach to Rapidly Detect SARS-CoV-2 Infection Avoiding RNA Extraction: Workflow Validation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has rapidly spread worldwide from the beginning of 2020. The presence of viral RNA in samples by nucleic acid (NA) molecular analysis is the only method available to diagnose COVID-19 disease and to assess patients' viral load. Since the demand for laboratory reagents has increased, there has been a worldwide shortage of RNA extraction kits. We, therefore, developed a fast and cost-effective viral genome isolation method that, combined with quantitative RT-PCR assay, detects SARS-CoV-2 RNA in patient samples. The method relies on the addition of Proteinase K followed by a controlled heat-shock incubation and, then, E gene evaluation by RT-qPCR. It was validated for sensitivity, specificity, linearity, reproducibility, and precision. It detects as low as 10 viral copies/sample, is rapid, and has been characterized in 60 COVID-19-infected patients. Compared to automated extraction methods, our pretreatment guarantees the same positivity rate with the advantage of shortening the time of the analysis and reducing its cost. This is a rapid workflow meant to aid the healthcare system in the rapid identification of infected patients, such as during a pathogen-related outbreak. For its intrinsic characteristics, this workflow is suitable for large-scale screenings.