Impact of Anti-SARS-CoV-2 Vaccination on Disease Severity and Clinical Outcomes of Individuals Hospitalized for COVID-19 Throughout Successive Pandemic Waves: Data from an Italian Reference Hospital.

This is a retrospective observational study including all COVID-19 patients admitted at our Institute throughout three successive pandemic waves, from January 2021 to June 2023. The main in-hospital outcomes (clinical progression [CP], defined as admission to Intensive Care Unit [ICU]/death, and death within 28 days) were compared among participants unvaccinated (NV), fully vaccinated (FV), with one (FV&B1) and two (FV&B2) booster doses. Vaccinated participants were stratified into recently and waned FV/FV&B1/FV&B2, depending on the time elapsed from last dose (≤ and >120 days, respectively).

BART, the new robotic assistant: big data, artificial intelligence, robotics, and telemedicine integration for an ICU 4.0.

We are in the era of Health 4.0 when novel technologies are providing tools capable of improving the quality and safety of the services provided. Our project involves the integration of different technologies (AI, big data, robotics, and telemedicine) to create a unique system for patients admitted to intensive care units suffering from infectious diseases capable of both increasing the personalization of care and ensuring a safer environment for caregivers.

A novel risk score predicting 30-day hospital re-admission of patients with acute stroke by machine learning model.

Background: The 30-day hospital re-admission rate is a quality measure of hospital care to monitor the efficiency of the healthcare system. The hospital re-admission of acute stroke (AS) patients is often associated with higher mortality rates, greater levels of disability and increased healthcare costs. The aim of our study was to identify predictors of unplanned 30-day hospital re-admissions after discharge of AS patients and define an early re-admission risk score (RRS).

COVID-19 pandemic in the intensive care unit: Psychological implications and interventions, a systematic review.

Background: The coronavirus disease 2019 (COVID-19) pandemic produced changes in intensive care units (ICUs) in patient care and health organizations. The pandemic event increased patients' risk of developing psychological symptoms during and after hospitalisation. These consequences also affected those family members who could not access the hospital.

Thromboelastography Profile Is Associated with Lung Aeration Assessed by Point-of-Care Ultrasound in COVID-19 Critically Ill Patients: An Observational Retrospective Study.

Background. To evaluate relationships between lung aeration assessed by lung ultrasound (LUS) with viscoelastic profiles obtained by thromboelastography (TEG) in COVID-19 respiratory failure. Methods.

Machine Learning and Antibiotic Management.

Machine learning and cluster analysis applied to the clinical setting of an intensive care unit can be a valuable aid for clinical management, especially with the increasing complexity of clinical monitoring. Providing a method to measure clinical experience, a proxy for that automatic evaluation that an experienced clinician sometimes effortlessly, but often only after long, hard consideration and consultation with colleagues, relies upon for decision making, is what we wanted to achieve with the application of machine learning to antibiotic therapy and clinical monitoring in the present work. This is a single-center retrospective analysis proposing methods for evaluation of vitals and antimicrobial therapy in intensive care patients.

Hemodynamic response to positive end-expiratory pressure and prone position in COVID-19 ARDS.

Background: Use of high positive end-expiratory pressure (PEEP) and prone positioning is common in patients with COVID-19-induced acute respiratory failure. Few data clarify the hemodynamic effects of these interventions in this specific condition. We performed a physiologic study to assess the hemodynamic effects of PEEP and prone position during COVID-19 respiratory failure.

Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients.

Background: Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care.

Methods: We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry.

Diaphragm thickening fraction predicts noninvasive ventilation outcome: a preliminary physiological study.

Background: A correlation between unsuccessful noninvasive ventilation (NIV) and poor outcome has been suggested in de-novo Acute Respiratory Failure (ARF) patients. Consequently, it is of paramount importance to identify accurate predictors of NIV outcome. The aim of our preliminary study is to evaluate the Diaphragmatic Thickening Fraction (DTF) and the respiratory rate/DTF ratio as predictors of NIV outcome in de-novo ARF patients.

Effect of Helmet Noninvasive Ventilation vs High-Flow Nasal Oxygen on Days Free of Respiratory Support in Patients With COVID-19 and Moderate to Severe Hypoxemic Respiratory Failure: The HENIVOT Randomized Clinical Trial.

Importance: High-flow nasal oxygen is recommended as initial treatment for acute hypoxemic respiratory failure and is widely applied in patients with COVID-19.

Objective: To assess whether helmet noninvasive ventilation can increase the days free of respiratory support in patients with COVID-19 compared with high-flow nasal oxygen alone.

Design, Setting, And Participants: Multicenter randomized clinical trial in 4 intensive care units (ICUs) in Italy between October and December 2020, end of follow-up February 11, 2021, including 109 patients with COVID-19 and moderate to severe hypoxemic respiratory failure (ratio of partial pressure of arterial oxygen to fraction of inspired oxygen ≤200).

Blood Glucose Levels Combined with Triage Revised Trauma Score Improve the Outcome Prediction in Adults and in Elderly Patients with Trauma.

Introduction: This study was aimed to assess if combining the evaluation of blood glucose level (BGL) and the Triage Revised Trauma Score (T-RTS) may result in a more accurate prediction of the actual clinical outcome, both in general adult population and in elderly patients with trauma.

Methods: This is a retrospective cohort study, conducted in the emergency department (ED) of an urban teaching hospital, with an average ED admission rate of 75,000 patients per year. Those excluded: known diagnosis of diabetes, age <18 years old, pregnancy, and mild trauma (classified as isolate trauma of upper or lower limb, in absence of exposed fractures).

How to communicate with families living in complete isolation.

Importance: During the SARS-CoV-2 pandemic, a complete physical isolation has been worldwide introduced. The impossibility of visiting their loved ones during the hospital stay causes additional distress for families: in addition to the worries about clinical recovery, they may feel exclusion and powerlessness, anxiety, depression, mistrust in the care team and post-traumatic stress disorder. The impossibility of conducting the daily meetings with families poses a challenge for healthcare professionals.

Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores.

Aims: To identify the most accurate early warning score (EWS) for predicting an adverse outcome in COVID-19 patients admitted to the emergency department (ED).

Methods: In adult consecutive patients admitted (March 1-April 15, 2020) to the ED of a major referral centre for COVID-19, we retrospectively calculated NEWS, NEWS2, NEWS-C, MEWS, qSOFA, and REMS from physiological variables measured on arrival. Sensitivity, specificity, positive (PPV) and negative predictive value (NPV), and the area under the receiver operating characteristic (AUROC) curve of each EWS for predicting admission to the intensive care unit (ICU) and death at 48 h and 7 days were calculated.

Respiratory physiology of COVID-19-induced respiratory failure compared to ARDS of other etiologies.

Background: Whether respiratory physiology of COVID-19-induced respiratory failure is different from acute respiratory distress syndrome (ARDS) of other etiologies is unclear. We conducted a single-center study to describe respiratory mechanics and response to positive end-expiratory pressure (PEEP) in COVID-19 ARDS and to compare COVID-19 patients to matched-control subjects with ARDS from other causes.

Methods: Thirty consecutive COVID-19 patients admitted to an intensive care unit in Rome, Italy, and fulfilling moderate-to-severe ARDS criteria were enrolled within 24 h from endotracheal intubation.

Data on the application of early coagulation support protocol in the management of major trauma patients.

This article provides additional data on the application of early coagulation support protocol in the management of major trauma patients. Data come from a retrospective analysis reported in the article "Early coagulation support protocol: a valid approach in real-life management of major trauma patients. Results from two Italian centres" [1].

Early coagulation support protocol: A valid approach in real-life management of major trauma patients. Results from two Italian centres.

Introduction: Early coagulation support (ECS) includes prompt infusion of tranexamic acid, fibrinogen concentrate, and packed red blood cells for initial resuscitation of major trauma patients. The aim of this study was to determine the effects, in terms of blood product consumption, length of stay, and in-hospital mortality, of the ECS protocol, compared to the massive transfusion protocol (MTP) in the treatment of major trauma patients.

Patients And Methods: A retrospective analysis was conducted using the registry data of two Italian trauma centres.

Physiological Comparison of High-Flow Nasal Cannula and Helmet Noninvasive Ventilation in Acute Hypoxemic Respiratory Failure.

High-flow nasal cannula (HFNC) and helmet noninvasive ventilation (NIV) are used for the management of acute hypoxemic respiratory failure. Physiological comparison of HFNC and helmet NIV in patients with hypoxemia. Fifteen patients with hypoxemia with Pa/Fi < 200 mm Hg received helmet NIV (positive end-expiratory pressure ≥ 10 cm HO, pressure support = 10-15 cm HO) and HFNC (50 L/min) in randomized crossover order.

Improving communication toward ICU families to facilitate understanding and reduce stress. Protocol for a multicenter randomized and controlled Italian study.

Objective: Families of ICU patients have a pressing need for information: they find themselves suddenly in a complex technical environment often because of a life-threatening illness of a loved one. Some evidence suggests that specific communication tools (like websites or brochures) could improve the experience of ICU families.

Design: Randomized, multicenter, stepped wedge trial for large-scale assessment of the effectiveness of a multitasking intervention to improve communication with families of critically ill patients.