Publications by authors named "Bignami E"
: A tracheostomy is a frequently performed surgical intervention in intensive care units (ICUs) for patients requiring prolonged mechanical ventilation. This procedure can offer significant benefits, including reduced sedation requirements, improved patient comfort, and enhanced airway management. However, it is also associated with various risks, and the absence of standardized clinical guidelines complicates its implementation.
View Article and Find Full Text PDFObjectives: This scoping review aimed to identify existing literature on the application of augmented reality (AR) in the intensive care unit (ICU) and analyse its current state of play regarding hands-on skills.
Background: Active learner engagement can greatly enrich educational outcomes. With the rise of immersive and interactive technologies, AR is progressively integrated into nursing education to enhance this aspect.
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.
View Article and Find Full Text PDF: 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.
View Article and Find Full Text PDFArtificial Intelligence for Mechanical Ventilation: A Transformative Shift in Critical Care.
Ther Adv Pulm Crit Care Med
November 2024
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.
View Article and Find Full Text PDFArticle Synopsis
- The study aims to develop machine learning models to identify factors linked to Emergence Delirium (ED) in pediatric patients undergoing tonsillectomy or adenotonsillectomy.
- After cleaning and analyzing a dataset of 423 cases, four predictive models (logistic regression, random forest, support vector machine, and gradient boosting) were tested, with the random forest model showing the best performance (AUC-ROC of 0.96).
- Key findings highlighted significant correlations between factors like age, weight, and surgery duration with ED risk, while K-means clustering identified distinct patient groups characterized by varying risk levels for ED.
Article Synopsis
- Millions of ICU survivors annually face post-intensive care syndrome (PICS), which includes cognitive, psychological, and physical impairments after discharge.
- Cognitive issues may involve memory and attention deficits, while psychological problems like depression, anxiety, and PTSD are common.
- The impact of PICS extends to families, leading to PICS-family (PICS-F), where caregivers also experience psychological distress, highlighting the need for targeted prevention and treatment strategies.
Wearable devices as part of postoperative early warning score systems: a scoping review.
J Clin Monit Comput
October 2024
Article Synopsis
- Postoperative deterioration can be indicated by changes in vital signs, but many hospitals lack resources for continuous monitoring outside of ICUs, prompting the use of wearable devices (WDs) for patient monitoring.
- A Scoping Review was conducted using various databases to analyze the effectiveness of WDs as part of Continuous Remote Early Warning Score (CREWS) systems in monitoring patients after cardiac and non-cardiac surgeries, resulting in 10 studies featuring 11 CE/FDA approved devices.
- The findings suggest that WDs are not only feasible and safe for monitoring but also help reduce the length of hospital stays and ICU admissions, leading to lower healthcare costs and better identification of potential complications post-surgery
Article Synopsis
- Researchers believe that lung ultrasound scores (LUS) can better predict cardiac risks in elderly patients undergoing hip fracture surgery, compared to existing methods like the Revised Cardiac Risk Index and ASA Physical Status.
- The study involved 877 patients across 11 Italian hospitals, finding a significant correlation between higher LUS scores and complications, with a notable incidence of major adverse cardiovascular events (MACE).
- Results showed that a preoperative LUS score of 8 or higher was more effective at predicting MACE than traditional scoring methods, indicating its potential as a valuable tool for risk assessment in this patient population.
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.
Article Synopsis
- Postoperative pulmonary complications (PPCs) are a significant issue after esophagectomy, affecting up to 40% of patients despite advances in surgical care.
- This study aims to determine if using high-flow nasal cannula (HFNC) right after extubation can lower PPC rates compared to standard oxygen therapy.
- The research involves 320 participants who will be randomly assigned to either HFNC or standard therapy post-surgery, with various complications being tracked to assess the effectiveness of each approach.
Article Synopsis
- A panel of Italian intensive care specialists explored the use of angiotensin II (ATII) in treating distributive shock, considering patient factors and the effectiveness of existing treatment protocols.
- They employed a modified Delphi technique to establish consensus on clinical questions and statements related to ATII, resulting in agreement on 13 key statements from a survey.
- The panel concluded that ATII could be beneficial for specific patients, particularly those with reduced angiotensin-converting enzyme activity or high renin levels, while also noting potential barriers to its use.
Article Synopsis
- Lung ultrasonography (LUS) is a useful, non-invasive tool for diagnosing respiratory conditions, particularly in resource-limited settings, as it reduces radiation exposure and quantifies regional loss of aeration.
- A study assessed the agreement among 20 experienced LUS operators by having them evaluate 25 video clips, revealing strong but not perfect inter-rater reliability, with varying levels of consensus on the scores assigned to the clips.
- Despite some discrepancies, the findings indicate that LUS scoring can reliably inform severity assessments in respiratory diseases, making it a valuable clinical tool.
Emergency general surgeons often provide care to severely ill patients requiring surgical interventions and intensive support. One of the primary drivers of morbidity and mortality is perioperative bleeding. In general, when addressing life threatening haemorrhage, blood transfusion can become an essential part of overall resuscitation.
View Article and Find Full Text PDFWe 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.
View Article and Find Full Text PDFBackground: Reintubation is associated with higher risk of mortality. There is no clear evidence on the best spontaneous breathing trial (SBT) method to reduce the risk of reintubation.
Research Question: Are different methods of conducting SBTs in critically ill patients associated with different risk of reintubation compared with T-tube?
Study Design And Methods: We conducted a systematic review and Bayesian network meta-analysis of randomized controlled trials investigating the effects of different SBT methods on reintubation.
Article Synopsis
- The use of artificial intelligence (AI) and machine learning in urology aims to enhance diagnostic processes and improve prognosis for patients, particularly those with urolithiasis who are at risk for serious infections.
- A systematic scoping review was conducted to evaluate existing literature on AI applications for predicting infectious complications in urolithiasis, yielding nine relevant studies from an initial search of 467 articles, primarily published between 2021 and 2023.
- The reviewed studies showed promising results, with AI models like random forests and neural networks demonstrating superior performance in predicting infections compared to traditional methods, although further research and validation are necessary before widespread clinical implementation.
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.