Approach to patients with COVID-19 disease: the procedure in Udine.

Coronavirus disease 2019 poses a serious threat to public health. The protocol developed at the Azienda Sanitaria Universitaria Friuli Centrale (Italy) is based on clinical data, laboratory tests, chest echography and HRCT. Several therapeutic options are considered, since patients vary in disease severity, evolution and co-morbidities and because so far there are no clear indications about therapeutic strategy based on randomized clinical trial. In this protocol chest echography has a central role in categorizing patient status, follow-up and decision-making.

The role of asymmetric dimethylarginine (ADMA) in COVID-19: association with respiratory failure and predictive role for outcome.

We aimed to assess the potential role of Asymmetric dimethylarginine (ADMA) in conditioning respiratory function and pulmonary vasoregulation during Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) infection. Within 72 h from admission, samples from 90 COVID-19 patients were assessed for ADMA, SDMA, L-arginine concentrations. In addition to classical statistics, patients were also clustered by a machine learning approach according to similar features. Multivariable analysis showed that C-reactive protein (OR 1.012), serum ADMA (OR 4.652), white blood cells (OR = 1.118) and SOFA (OR = 1.495) were significantly associated with negative outcomes. Machine learning-based clustering showed three distinct clusters: (1) patients with low severity not requiring invasive mechanical ventilation (IMV), (2) patients with moderate severity and respiratory failure whilst not requiring IMV, and (3) patients with highest severity requiring IMV. Serum ADMA concentration was significantly associated with disease severity and need for IMV although less pulmonary vasodilation was observed by CT scan. High serum levels of ADMA are indicative of high disease severity and requirement of mechanical ventilation. Serum ADMA at the time of hospital admission may therefore help to identify COVID-19 patients at high risk of deterioration and negative outcome.

Sarcopenia and Patient's Body Composition: New Morphometric Tools to Predict Clinical Outcome After Ivor Lewis Esophagectomy: a Multicenter Study.

BACKGROUND: The impact of preoperative body composition as independent predictor of prognosis for esophageal cancer patients after esophagectomy is still unclear. The aim of the study was to explore such a relationship. METHODS: This is a multicenter retrospective study from a prospectively maintained database. We enrolled consecutive patients who underwent Ivor-Lewis esophagectomy in four Italian high-volume centers from May 2014. Body composition parameters including total abdominal muscle area (TAMA), visceral fat area (VFA), and subcutaneous fat area (SFA) were determined based on CT images. Perioperative variables were systematically collected. RESULTS: After exclusions, 223 patients were enrolled and 24.2% had anastomotic leak (AL). Sixty-eight percent of patients were sarcopenic and were found to be more vulnerable in terms of postoperative 90-day mortality (p = 0.028). VFA/TAMA and VFA/SFA ratios demonstrated a linear correlation with the Clavien-Dindo classification (R = 0.311 and 0.239, respectively); patients with anastomotic leak (AL) had significantly higher VFA/TAMA (3.56 ± 1.86 vs. 2.75 ± 1.83, p = 0.003) and VFA/SFA (1.18 ± 0.68 vs. 0.87 ± 0.54, p = 0.002) ratios. No significant correlation was found between preoperative BMI and subsequent AL development (p = 0.159). Charlson comorbidity index correlated significantly with AL (p = 0.008): these patients had a significantly higher index (≥ 5). CONCLUSION: Analytical morphometric assessment represents a useful non-invasive tool for preoperative risk stratification. The concurrent association of sarcopenia and visceral obesity seems to be the best predictor of AL, far better than simple BMI evaluation, and potentially modifiable if targeted with prehabilitation programs.