Publications by authors named "Michelangelo Craca"

Background: Management of operating rooms is a critical point in health care organizations because surgical departments represent a significant cost in hospital budgets. Therefore, it is increasingly important that there is effective planning of elective, emergency, and day surgery and optimization of both the human and physical resources available, always maintaining a high level of care and health treatment. This would lead to a reduction in patient waiting lists and better performance not only of surgical departments but also of the entire hospital.

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The entry of Artificial Intelligence (AI) into Intensive Care has become a reality. We think that only with robust validation studies accomplished by a multidisciplinary team the gap between clinical research and clinical practice can be bridged.

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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).
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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.

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From February 2019 the World faces the Covid19 pandemic. The data in our possession are still insufficient to effectively combat this pathology. The gold standard for diagnosis remains molecular testing, while clinical and instrumental and serological diagnostics are highly nonspecific leading to a slowdown in the battle against covid19.

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