Sepsis is a threat to global health, and domestically is the major cause of in-hospital mortality. Due to increases in inpatient morbidity and mortality resulting from sepsis, healthcare providers (HCPs) would accrue significant benefits from identifying the syndrome early and treating it promptly and effectively. Prompt and effective detection, diagnosis, and treatment of sepsis requires frequent monitoring and assessment of patient vital signs and other relevant data present in the electronic health record.

Cardiac surgery is known to have high rates of perioperative red blood cell (RBC) transfusions which are associated with increased postoperative mortality and morbidity. Perioperative erythropoietin (EPO) has been suggested to lower perioperative RBC transfusions, and the effect on postoperative morbidity or mortality is unknown.

Integrating machine learning (ML) into intensive care units (ICUs) can significantly enhance patient care and operational efficiency. ML algorithms can analyze vast amounts of data from electronic health records, physiological monitoring systems, and other medical devices, providing real-time insights and predictive analytics to assist clinicians in decision-making. ML has shown promising results in predictive modeling for patient outcomes, early detection of sepsis, optimizing ventilator settings, and resource allocation. For instance, predictive algorithms have demonstrated high accuracy in forecasting patient deterioration, enabling timely interventions and reducing mortality rates. Despite these advancements, challenges such as data heterogeneity, integration with existing clinical workflows, and the need for transparency and interpretability of ML models persist. The deployment of ML in ICUs also raises ethical and legal considerations regarding patient privacy and the potential for algorithmic biases. For clinicians interested in the early embracing of AI-driven changes in clinical practice, in this review, we discuss the challenges of integrating AI and ML tools in the ICU environment in several steps and issues: (1) Main categories of ML algorithms; (2) From data enabling to ML development; (3) Decision-support systems that will allow patient stratification, accelerating the foresight of adequate individual care; (4) Improving patient outcomes and healthcare efficiency, with positive society and research implications; (5) Risks and barriers to AI-ML application to the healthcare system, including transparency, privacy, and ethical concerns.

Septic shock is common and associated with significant morbidity and mortality. The ADRENAL trial examined the use of hydrocortisone in patients with septic shock, demonstrating no difference in patient-centred outcomes but a decrease in the time to shock resolution. The change in clinical practice related to the publication of the ADRENAL trial is currently unknown.

We hypothesize that lung ultrasound scores (LUS) can help stratify the cardiac risk of elderly patients undergoing orthopedic surgery for hip fracture, adding value to the Revised Cardiac Risk Index (RCRI), the American Society of Anesthesiologists Physical Status (ASA-PS) and the National Surgical Quality Improvement Program Myocardial infarction and Cardiac arrest (NSQIP-MICA).

Any surgical procedure carries a risk for venous thromboembolism (VTE), albeit variable. Improvements in medical and surgical practices and the shortening of care pathways due to the development of day surgery and enhanced recovery after surgery, have reduced the perioperative risk for VTE.

Hypocalcemia, measured through ionized calcium, is a common derangement in critically ill patients. Hypocalcemia is corrected as a routine procedure in intensive care units; however, no clear guidelines exist for its management.

Sedation strategies have not been well established for patients being treated with invasive mechanical ventilation (MV). This study aimed to compare the potential effects of alternative sedation strategies - including early deep-to-light sedation (DTLS), continuous deep sedation (CDS) and continuous light sedation (CLS, the currently recommended strategy) - on ventilator, intensive care unit (ICU) or hospital mortality.

Video-assisted thoracoscopic surgery (VATS) reduces postoperative discomfort and expedites recovery compared to open thoracotomy. Effective postoperative pain management is crucial to enhance recovery and reduce complications. Ketamine, an NMDA receptor antagonist, has shown promise, though its efficacy in VATS remains uncertain. This meta-analysis aims to evaluate the efficacy and safety of ketamine in reducing acute pain in VATS patients.

Some anaesthetists wonder whether confirming a train-of-four ratio (TOFR) ≥0.9 is necessary when using sugammadex to antagonise neuromuscular blockade (NMB). In this study, we aimed to determine whether using sugammadex at the recommended dose under neuromuscular monitoring (NMM) would ensure complete recovery, even without further NMM.

Nasal surgery has a reported high incidence of agitation during emergence from general anesthesia. Emergence Agitation (EA) increases the risk of surgical site bleeding, falling off the operating table, removal of catheters and intravenous lines, and self-extubation. This study investigated the role of nerve block in EA.

It remains unclear whether opioid-free anesthesia (OFA), when compared to opioid-sparing anesthesia (OSA), reduces postoperative opioid consumption while still providing adequate pain control. We thus tested the hypothesis that patients having an OFA strategy during laparoscopic colectomy would require less postoperative opioids when compared to an OSA strategy.

Postoperative pulmonary complications (PPCs) contribute to high mortality rates and impose significant financial burdens. In this study, a machine learning-based prediction model was developed to identify patients at high risk of developing PPCs following laparoscopic hepatectomy.

Emergence delirium (ED) is a common postoperative cognitive dysfunction in children. ED may cause distress to patients and their families in the early post-anesthesia period and have long-term adverse effects on children. THE PRIMARY PURPOSE: was to verify whether dexmedetomidine can reduce the occurrence of ED in children.

We explored the effects of dexmedetomidine (DEX) versus propofol on outcomes in critically ill patients and to assess whether these effects are dissimilar under different sedation depths.

The ESPA Pain Management Ladder Initiative is a clinical practice advisory based upon expert consensus supported by the current literature to help ensure a basic standard of perioperative pain management for all children. In 2018 the perioperative pain management of six common pediatric surgical procedures was summarised. The current Pain Management Ladder recommendations focus on five more complex pediatric surgical procedures and suggest basic, intermediate, and advanced pain management methods. The aim of this paper is to encourage best possible pain management practice and to support institutions to create their own pain management concepts according to their financial and human resources due to the diversity of clinical settings in Europe. Furthermore, the authors underline that these recommendations are intended for inpatients only.