Background and Objectives: Numerous scoring systems have been introduced into modern medicine. None of the scoring systems assessed both anesthetic and surgical risk of the patient, predict the morbidity, mortality, or the need for postoperative intensive care unit admission. The aim of this study was to compare the anesthetic and surgical scores currently used, for a better evaluation of perioperative risks, morbidity, and mortality. Material and Methods: This is a pilot, prospective, observational study. We enrolled 50 patients scheduled for elective surgery. Anesthetic and surgery risk was assessed using American Society of Anesthesiologists (ASA) scale, Physiological and Operative Severity Score for the enumeration of Mortality and morbidity (P-POSSUM), Acute Physiology and Chronic Health Evaluation (APACHE II), and Surgical APGAR Score (SAS) scores. The real and the estimated length of stay (LOS) were registered. Results: We obtained several statistically significant positive correlations: ASA score–P-POSSUM (p < 0.01, r = 0.465); ASA score–SAS, (p < 0.01, r = −0.446); ASA score–APACHE II, (p < 0.01 r = 0.519); predicted LOS and ASA score (p < 0.01, r = 0.676); predicted LOS and p-POSSUM (p < 0.01, r = 0.433); and predicted LOS and APACHE II (p < 0.01, r = 0.454). A significant negative correlation between predicted LOS, real LOS, ASA class, and SAS (p < 0.05) was observed. We found a statistically significant difference between the predicted and actual LOS (p < 001). Conclusions: Anesthetic, surgical, and severity scores, used together, provide clearer information about mortality, morbidity, and LOS. ASA scale, associated with surgical scores and severity scores, presents a better image of the patient’s progress in the perioperative period. In our study, APACHE II is the best predictor of mortality, followed by P-POSSUM and SAS. P-POSSUM score and ASA scale may be complementary in terms of preoperative physiological factors, providing valuable information for postoperative outcomes.

Background: The increased production of carbon monoxide (CO) in sepsis has been proven, but the blood level variations of carboxyhemoglobin (COHb) as a potential evolutionary parameter of COVID-19 and sepsis/septic shock have yet to be determined. This study aims to evaluate the serum level variation of COHb as a potential evolutionary parameter in COVID-19 critically ill patients and in bacterial sepsis. Materials and method: A prospective and observational study was conducted on two groups of patients: the bacterial sepsis group (n = 52) and the COVID-19 group (n = 52). We followed paraclinical parameters on Day 1 (D1) and Day 5 (D5) of sepsis/ICU admission for COVID-19 patients. Results: D1 of sepsis: statistically significant positive correlations between: COHb values and serum lactate (p = 0.024, r = 0.316), and total bilirubin (p = 0.01, r = 0.359). In D5 of sepsis: a statistically significant positive correlations between: COHb values and procalcitonin (PCT) (p = 0.038, r = 0.402), and total bilirubin (p = 0.023, r = 0.319). D1 of COVID-19 group: COHb levels were statistically significantly positively correlated with C-reactive protein CRP values (p = 0.003, r = 0.407) and with PCT values (p = 0.022, r = 0.324) and statistically significantly negatively correlated with serum lactate values (p = 0.038, r = −0.285). Conclusion: COHb variation could provide rapid information about the outcome of bacterial sepsis/septic shock, having the advantages of a favorable cost-effectiveness ratio, and availability as a point-of-care test.

Introduction: The management of sedation during percutaneous endoscopic gastrojejunostomy (PEG-J) placement in patients with advanced Parkinson’s disease (PD) is challenging due to the complex interactions between PD treatment, anesthetic agents, and the disease’s motor and non-motor symptoms. This study evaluates the effectiveness and safety of a target-controlled infusion (TCI) propofol protocol in the context of PEG-J placement in advanced PD patients. Materials and Methods: This prospective study included 169 patients diagnosed with advanced Parkinson’s disease (Hoehn and Yahr stages 4 and 5) who underwent PEG-J placement at Târgu Mureș County Emergency Clinical Hospital, Romania. Sedation was induced and maintained using TCI propofol, with additional benzodiazepines and short-acting opioids, while muscle relaxants were not used. Procedural success rates and adverse outcomes were assessed for 30 days post-procedure. Results: The sedation protocol demonstrated a high procedural success rate. No deaths were reported within 30 days post-procedure. Conclusion: This study highlights the feasibility and clinical applicability of a TCI propofol protocol for PEG-J placement in patients with advanced PD (stages 4 and 5). While no deaths were recorded within the 30-day follow-up, the sample size is insufficient to draw definitive conclusions regarding long-term safety.

(1) Background: Since the onset of the COVID-19 pandemic, it has been recognized that a considerable proportion of critically ill patients may die of this disease. The current study aims to assess the overall 1-year outcomes within the UMFST COVID-19 Unit, providing valuable insights into the efficacy of specialized care facilities in managing severe cases of COVID-19. (2) Methods: This is a retrospective monocentric observational study including 294 patients confirmed to have SARS-CoV-2 infection. Demographic data and clinical and paraclinical parameters were assessed. Survival probabilities were estimated using Kaplan–Meier curves. (3) Results: Overall, the 1-year mortality was 89.4%. All deaths occurred in-hospital, with two patients dying after 28 days. Diabetes mellitus, chronic kidney failure, cerebrovascular disease, and atrial fibrillation were more prevalent in deceased patients. Thirty percent of patients needed endotracheal intubation during the first 24 h. The incidence of hospital-acquired pneumonia was higher among deceased patients. The SOFA score was significantly different between deceased vs. survivors. The survival analysis showed that the use of noradrenaline increased the likelihood of surviving COVID-19. (4) Conclusions: The severe comorbidities of the patients were the primary factors contributing to the increased mortality rate in the COVID-19 unit.

Serotonin syndrome (SS), also known as serotonin toxicity, is a life-threatening condition induced by certain drugs that affect serotonin metabolism. We report a case of SS, induced by a combination of three drugs encountered in a patient with a previously suspected allergy to metoclopramide and pitofenone discovered as an "anaesthetic incident”. In the immediate postoperative period, following the administration of antiemetic and analgesic treatment, the patient presented generalized myoclonus and intense abdominal pain. The diagnosis of SS was established using the Hunter Criteria. After the discontinuation of potentially triggering medication and anticonvulsant therapy, the patient was discharged from the ICU with complete resolution within six days. Given the increased use in clinical practice of drugs that may interfere with serotonin metabolism, the rising prevalence of mental health and the increasing use of illicit drugs, it is essential for anaesthetists to be aware of the potential for SS occurrence. Continue...

Intensive care medicine represents one of the most challenging setting in modern healthcare, where specific mechanisms intertwine and form a dynamic biological model, where organ dysfunction can easily evolve to multi-organ dysfunction, continuously reshaping the patient’s clinical course. The critically ill patient represents a biological system resulted from interaction between maladaptive and adaptative mechanisms, therefore generates a large volume of data that can exceeds human cognitive capacity. Artificial intelligence can integrate multimodal physiological, laboratory, and clinical data into a dynamic representation of the patient’s biological trajectory. AI-tools and machine learning technologies have evolved to potential clinical support tools, with great perspectives for future implementation, but currently with limited use in clinical practice. This article is a narrative review of artificial intelligence in ICU, aiming to present current evidence and limitations.