Publications by authors named "Antonio Desai"

Background: Traumatic brain injury (TBI) in the elderly is a noteworthy pathology due to the exponential increase in population age, and the effects of antiplatelet and anticoagulation on patients' outcomes are still a matter of dispute. The aim of the present study was to evaluate the impact of various antithrombotic agents on patients with mild TBI, focusing on the risk of intracranial bleeding (ICH) and length of hospitalization (LOS).

Methods: A retrospective analysis was conducted, including patients with a diagnosis of TBI admitted to the Emergency Department between 2021 and 2022.

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Introduction: Polymorphonuclear cell influx into the interstitial and bronchoalveolar spaces is a cardinal feature of severe coronavirus disease 2019 (COVID-19), principally mediated by interleukin-8 (IL-8). We sought to determine whether reparixin, a novel IL-8 pathway inhibitor, could reduce disease progression in patients hospitalized with severe COVID-19 pneumonia.

Methods: In this Phase 3, randomized, double-blind, placebo-controlled, multicenter study, hospitalized adult patients with severe COVID-19 pneumonia were randomized 2:1 to receive oral reparixin 1200 mg three times daily or placebo for up to 21 days or until hospital discharge.

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Ursodeoxycholic acid (UDCA) was demonstrated to reduce susceptibility to SARS-CoV-2 infection in vitro and improve infection course in chronic liver diseases. However, real-life evidence is lacking. We analyzed the impact of UDCA on COVID-19 outcomes in patients hospitalized in a tertiary center.

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Triage systems help provide the right care at the right time for patients presenting to emergency departments (EDs). Triage systems are generally used to subdivide patients into three to five categories according to the system used, and their performance must be carefully monitored to ensure the best care for patients. We examined ED accesses in the context of 4-level (4LT) and 5-level triage systems (5LT), implemented from 1 January 2014 to 31 December 2020.

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Article Synopsis
  • The study explores the use of AI, specifically semantic language models, to improve the early diagnosis of major ischemic stroke (MIS) in emergency departments.
  • Researchers analyzed patient data through text processing techniques and employed the word2vec algorithm to enhance the identification of MIS cases.
  • The findings indicate that the algorithm successfully detected 83.9% of MIS cases with a high accuracy, suggesting that NLP models could significantly aid in the triage process and support healthcare professionals.
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Community-acquired pneumonia (CAP) is accountable for high mortality in both pediatric and adult populations worldwide, about one-third of hospitalized patients pass away within a year of being discharged from the facility. The high mortality and morbidity rates are closely related to cardiovascular complications that are consequent or concomitant to the acute episode of pneumonia. An updated perspective on the major pathophysiological mechanisms, prevalence, risk factors, outcomes, and relevant treatments of cardiovascular events in CAP patients is provided in the current study.

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Background: Early prognostic stratification of patients with sepsis is a difficult clinical challenge. Aim of this study was to evaluate novel molecules in association with clinical parameters as predictors of 90-days mortality in patients admitted with sepsis at Humanitas Research Hospital.

Methods: Plasma samples were collected from 178 patients, diagnosed based on Sepsis-3 criteria, at admission to the Emergency Department and after 5 days of hospitalization.

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Introduction: Identifying SARS-CoV-2 patients at higher risk of mortality is crucial in the management of a pandemic. Artificial intelligence techniques allow one to analyze large amounts of data to find hidden patterns. We aimed to develop and validate a mortality score at admission for COVID-19 based on high-level machine learning.

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Vaccination against an airborne pathogen is very effective if it induces also the development of mucosal antibodies that can protect against infection. The mRNA-based vaccine-encoding SARS-CoV-2 full-length spike protein (BNT162b2, Pfizer/BioNTech) protects also against infection despite being administered systemically. Here, we show that upon vaccination, cognate IgG molecules are also found in the saliva and are more abundant in SARS-CoV-2 previously exposed subjects, paralleling the development of plasma IgG.

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Short-term adverse events are common following the BNT162b2 vaccine for SARS-Cov-2 and have been possibly associated with IgG response. We aimed to determine the incidence of adverse reactions to the vaccine and the impact on IgG response. Our study included 4156 health-care professionals who received two doses of the BNT162b2 vaccine 21 days apart and obtained 6113 online questionnaires inquiring about adverse events.

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Background And Aims: The SARS-CoV-2 pandemic has overwhelmed the treatment capacity of the health care systems during the highest viral diffusion rate. Patients reaching the emergency department had to be either hospitalized (inpatients) or discharged (outpatients). Still, the decision was taken based on the individual assessment of the actual clinical condition, without specific biomarkers to predict future improvement or deterioration, and discharged patients often returned to the hospital for aggravation of their condition.

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Since December 2019, the world has been devastated by the Coronavirus Disease 2019 (COVID-19) pandemic. Emergency Departments have been experiencing situations of urgency where clinical experts, without long experience and mature means in the fight against COVID-19, have to rapidly decide the most proper patient treatment. In this context, we introduce an artificially intelligent tool for effective and efficient Computed Tomography (CT)-based risk assessment to improve treatment and patient care.

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Background: Our aim was to investigate the impact of therapeutics with antiviral activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on mortality of older adults affected by coronavirus disease 2019 (COVID-19), taking into consideration the time interval from symptoms onset to drugs administration.

Methods: Data from 143 COVID-19 patients over 65 years of age admitted to the Humanitas Clinical and Research Center Emergency Department (Milan, Italy) and treated with Lopinavir/ritonavir (LPV/r) or Darunavir/cobicistat (DVR/c) associated to Hydroxychloroquine (HCQ) were retrospectively analyzed. Statistical analysis was performed by using a logistic regression model and survival analysis to assess the role of different predictors of in-hospital mortality, including an early (<6 days from symptoms onset) vs.

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Background And Objectives: urinary antigen (u-Ag) testing has recently gained attention in the early diagnosis of severe and critical acute respiratory syndrome coronavirus-2/pneumococcal co-infection. The aim of this study is to assess the effectiveness of u-Ag testing in coronavirus disease 2019 (COVID-19) patients, in order to assess whether pneumococcal co-infection is associated with different mortality rate and hospital stay in these patients.

Materials And Methods: Charts, protocols, mortality, and hospitalization data of a consecutive series of COVID-19 patients admitted to a tertiary hospital in northern Italy during COVID-19 outbreak were retrospectively reviewed.

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Article Synopsis
  • This study investigated the impact of chronic use of antihypertensive medications (ACE inhibitors and ARBs) and cardiovascular comorbidities on mortality rates in COVID-19 patients.
  • Results indicated that chronic use of ACE inhibitors may reduce mortality risk, while ARBs showed no significant effect.
  • Importantly, older age and cardiovascular issues were significant risk factors, and timely treatment with low-molecular-weight heparin was found to be protective against mortality in hospitalized COVID-19 patients.
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