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OBJECTIVE: Coronavirus disease 2019 (COVID-19) has evolved into a global pandemic, affecting a wide range of medical and surgical specialties. During COVID-19, we assisted in the reallocation of medical resources and services, as well as social distancing measures, and many patients with chronic diseases and comorbidities may have experienced difficulties in obtaining the correct medical care. The aim of the study was to investigate the impact of the COVID-19 pandemic on major adverse cardiovascular events (MACE) and major adverse limb events (MALE) in patients with peripheral arterial disease (PAD) and chronic limb-threatening ischemia (CLTI), compared to previous years. PATIENTS AND METHODS: We evaluated 1,335 hospital admissions of 877 patients with PAD admitted to Policlinico A. Gemelli Hospital between January 2017 and February 2020 and 368 hospital admissions of 272 patients with PAD admitted to the Policlinico A. Gemelli Hospital between March 2020 and March 2021. Data on demographic characteristics, comorbidities, symptoms, physical and radiological findings, laboratory tests, and routine visits before or after discharge were collected from electronic medical records. RESULTS: Emergency room (ER) admissions among PAD patients during COVID-19 were higher than before the pandemic [190 (51.63%) vs. 579 (43.37%), p = 0.01]. A MACE was found in 78 (5.84%) pre-pandemic hospitalizations and 126 (34.24%) pandemic hospitalizations (p < 0.01). A MALE was identified in 942 (70.56%) pre-pandemic hospitalizations and 331 (89.95%) pandemic hospitalizations (p < 0.01). Amputation rates during the pandemic were higher than before the pandemic [80 (21.74%) vs. 191 (14.31%), p < 0.01]. The number of in-hospital deaths did not differ between the pandemic and pre-pandemic periods [11 (2.99%) vs. 51 (3.82%), p = 0.55]. CONCLUSIONS: In patients with PAD and CLTI, the number of MACE, MALE, and amputations was higher during the COVID-19 period compared to the three years before the pandemic. [ABSTRACT FROM AUTHOR]

OBJECTIVE: SARS-CoV-2 disease (COVID-19) has become a pandemic disease, determining a public health emergency. The use of artificial intelligence in identifying easily available biomarkers capable of predicting the risk for severe disease may be helpful in guiding clinical decisions. The aim of the study was to investigate the ability of interleukin (IL)-6, troponin I, and D-dimer to identify patients with COVID-19 at risk for intensive care unit (ICU)-admission and death by using a machine-learning predictive model. PATIENTS AND METHODS: Data on demographic characteristics, underlying comorbidities, symptoms, physical and radiological findings, and laboratory tests have been retrospectively collected from electronic medical records of patients admitted to Policlinico A. Gemelli Foundation from March 1, 2020, to September 15, 2020, by using artificial intelligence techniques. RESULTS: From an initial cohort of 425 patients, 146 met the inclusion criteria and were enrolled in the study. The in-hospital mortality rate was 15%, and the ICU admission rate was 41%. Patients who died had higher troponin I (p-value<0.01) and IL-6 values (p-value=0.04), compared to those who survived. Patients admitted to ICU had higher levels of troponin I (p-value<0.01) and IL-6 (p-value< 0.01), compared to those not admitted to ICU. Threshold values to predict in-hospital mortality and ICU admission have been identified. IL-6 levels higher than 15.133 ng/L have been associated with a 22.91% risk of in-hospital mortality, and IL-6 levels higher than 25.65 ng/L have been associated with a 56.16% risk of ICU admission. Troponin I levels higher than 12 ng/L have been associated with a 26.76% risk of in-hospital mortality and troponin I levels higher than 12 ng/L have been associated with a 52.11% risk of ICU admission. CONCLUSIONS: Levels of IL-6 and troponin I are associated with poor COVID-19 outcomes. Cut-off values capable of predicting in-hospital mortality and ICU admission have been identified. Building a predictive model using a machine-learning approach may be helpful in supporting clinical decisions in a more precise and personalized way. [ABSTRACT FROM AUTHOR]

The microbiome plays a crucial role in maintaining the homeostasis of the organism. Recent evidence has provided novel insights for understanding the interaction between the microbiota and the host. However, the vast majority of such studies have analyzed the interactions taking place in the intestinal tract. The biliary tree has traditionally been considered sterile under normal conditions. However, the advent of metagenomic techniques has revealed an unexpectedly rich bacterial community in the biliary tract. Associations between specific microbiological patterns and inflammatory biliary diseases and cancer have been recently described. Hence, biliary dysbiosis may be a primary trigger in the pathogenesis of biliary diseases. In particular, recent studies have suggested that microorganisms could play a significant role in the development of gallstones, pathogenesis of autoimmune cholangiopathies and biliary carcinogenesis. Moreover, the intimate connection between the biliary tract, liver and pancreas, could reveal hidden influences on the development of diseases of these organs. Further studies are needed to deepen the comprehension of the influence of the biliary microbiota in human pathology. This knowledge could lead to the formulation of strategies for modulating the biliary microbiota in order to treat and prevent these pathological conditions. [ABSTRACT FROM AUTHOR]