Artificial Intelligence in Sepsis Management: An Overview for Clinicians.

Sepsis is one of the leading causes of mortality in hospital settings, and early diagnosis is a crucial challenge to improve clinical outcomes. Artificial intelligence (AI) is emerging as a valuable resource to address this challenge, with numerous investigations exploring its application to predict and diagnose sepsis early, as well as personalizing its treatment. Machine learning (ML) models are able to use clinical data collected from hospital Electronic Health Records or continuous monitoring to predict patients at risk of sepsis hours before the onset of symptoms.

Assessing the Efficacy and Safety of Extubation Protocols in the Intensive Care Unit Following Transoral Robotic Surgery for Obstructive Sleep Apnea Syndrome: A Retrospective Cohort Study.

: There is a notable lack of protocols addressing extubation techniques in transoral robotic surgery (TORS) for obstructive sleep apnea (OSA). : This retrospective cohort study enrolled patients who underwent TORS for OSA between March 2015 and December 2021 and were managed with different extubation approaches. The patients were divided into two groups: high-flow nasal cannula (HFNC) therapy and conventional oxygen therapy.

Artificial Intelligence for Mechanical Ventilation: A Transformative Shift in Critical Care.

With the large volume of data coming from implemented technologies and monitoring systems, intensive care units (ICUs) represent a key area for artificial intelligence (AI) application. Despite the last decade has been marked by studies focused on the use of AI in medicine, its application in mechanical ventilation management is still limited. Optimizing mechanical ventilation is a complex and high-stake intervention, which requires a deep understanding of respiratory pathophysiology.

Opportunities and barriers for telemedicine in pain management: insights from a SIAARTI survey among Italian pain physicians.

Background: The integration of telemedicine in pain management represents a significant advancement in healthcare delivery, offering opportunities to enhance patient access to specialized care, improve satisfaction, and streamline chronic pain management. Despite its growing adoption, there remains a lack of comprehensive data on its utilization in pain therapy, necessitating a deeper understanding of physicians' perspectives, experiences, and challenges.

Methods: A survey was conducted in Italy between January 2024 and May 2024.

Maladaptive personality traits are associated with burnout risk in Italian anesthesiologists and intensivists: a secondary analysis from a cross-sectional study.

Background: Burnout is a maladaptive response to chronic stress, particularly prevalent among clinicians. Anesthesiologists are at risk of burnout, but the role of maladaptive traits in their vulnerability to burnout remains understudied.

Methods: A secondary analysis was performed on data from the Italian Association of Hospital Anesthesiologists, Pain Medicine Specialists, Critical Care, and Emergency (AAROI-EMAC) physicians.

Cardiac arrest and cardiopulmonary resuscitation in the next decade: Predicting and shaping the impact of technological innovations.

Introduction: Cardiac arrest (CA) is the third leading cause of death, with persistently low survival rates despite medical advancements. This article evaluates the potential of emerging technologies to enhance CA management over the next decade, using predictions from the AI tools ChatGPT-4 and Gemini Advanced.

Methods: We conducted an exploratory literature review to envision the future of cardiopulmonary arrest (CA) management.

Artificial Intelligence in Operating Room Management.

This systematic review examines the recent use of artificial intelligence, particularly machine learning, in the management of operating rooms. A total of 22 selected studies from February 2019 to September 2023 are analyzed. The review emphasizes the significant impact of AI on predicting surgical case durations, optimizing post-anesthesia care unit resource allocation, and detecting surgical case cancellations.

Continuous vs intermittent Non-Invasive blood pressure MONitoring in preventing postoperative organ failure (niMON): study protocol for an open-label, multicenter randomized trial.

Background: Blood pressure has become one of the most important vital signs to monitor in the perioperative setting. Recently, the Italian Society of Anesthesia Analgesia Resuscitation and Intensive Care (SIAARTI) recommended, with low level of evidence, continuous monitoring of blood pressure during the intraoperative period. Continuous monitoring allows for early detection of hypotension, which may potentially lead to a timely treatment.

Health coaching for undergraduate nursing students: a pilot study for an action research.

Background And Aim: The Nursing undergraduate degree educational program represents an intensive and complex course, and includes a number of professionalizing practical internships, and for these reasons it requires an action to support and improve. Coaching is based on the premise that people have personal strengths and abilities which, through a interview, can be directed to solving their problems. Several studies demonstrate the efficacy of Health Coaching in different University, but never have been measured benefits regard skills improving.

Remdesivir administration for SARS-CoV-2 pneumonia in ICU and non-ICU patients: outcome and posttreatment differences - the Italian Military Hospital experience.

Background: Four-hundred forty-nine patients affected by Covid-19 were hospitalized at the Rome Military Hospital between March 2020 and July 2022. Depending on the severity of the disease, they were assigned either to the Functional Health Emergency Unit - if suffering from interstitial pneumonia with a clinical manifestation of dyspnea associated with peripheral oxygen saturation  < 92%, and oxygen atmospheric pressure therapy - or to the intensive care unit - if the blood gas-lytic index P/F (ratio between partial pressure of arterial O2 and inspired fraction of O2) was below 150. This prospective observation and monocentric study aim to verify the outcome (healing/death) of early use of remdesivir in pneumonia patients.

Supraspinal neuroinflammation and anxio-depressive-like behaviors in young- and older- adult mice with osteoarthritis pain: the effect of morphine.

Rationale: Asteoarthritis (OA) is a leading cause of chronic pain in the elderly population and is often associated with emotional comorbidities such as anxiety and depression. Despite age is a risk factor for both OA and mood disorders, preclinical studies are mainly conducted in young adult animals.

Objectives: Here, using young adult (11-week-old) and older adult (20-month-old) mice, we evaluate in a monosodium-iodoacetate-(MIA)-induced OA model the development of anxio-depressive-like behaviors and whether brain neuroinflammation may underlie the observed changes.

Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives.

Although proper pain evaluation is mandatory for establishing the appropriate therapy, self-reported pain level assessment has several limitations. Data-driven artificial intelligence (AI) methods can be employed for research on automatic pain assessment (APA). The goal is the development of objective, standardized, and generalizable instruments useful for pain assessment in different clinical contexts.