Publications by authors named "Barbara Pifferi"
Machine learning in perioperative medicine: a systematic review.
J Anesth Analg Crit Care
January 2022
Article Synopsis
- Risk stratification is crucial for anesthetic evaluation, and machine learning (ML) can effectively analyze large healthcare data to predict post-surgical outcomes.
- A systematic review of studies from January 2015 to March 2021 evaluated ML's role in risk prediction for surgeries, focusing on quality reporting using the TRIPOD checklist, which showed acceptable adherence in most studies.
- The main outcomes of interest included risks of mortality and complications, with techniques like random forest and gradient boosting identified as the most effective algorithms, achieving high performance ratings (AUC > 0.90).
Background And Aim: During the first wave of the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) pandemic, we faced a massive clinical and organizational challenge having to manage critically ill patients outside the Intensive Care Unit (ICU). This was due to the significant imbalance between ICU bed availability and the number of patients presenting Acute Hypoxemic Respiratory Failure caused by SARS-CoV-2-related interstitial pneumonia. We therefore needed to perform Non-Invasive Ventilation (NIV) in non-intensive wards to assist these patients and relieve pressure on the ICUs and subsequently implemented a new organizational and clinical model.
View Article and Find Full Text PDFThe current COVID-19 pandemic underlines the importance of a mindful utilization of financial and human resources. Preserving resources and manpower is paramount in healthcare. It is important to ensure the ability of surgeons and specialized professionals to function through the pandemic.
View Article and Find Full Text PDF