anesthesia machine

Orthotopic liver transplantation (OLT) is the most effective treatment for patients with end-stage liver disease (ESLD). Hepatic insufficiency within a week of OLT, termed early allograft dysfunction (EAD), occurs in 20% to 25% of deceased donor OLT recipients and is associated with morbidity and mortality. Primary nonfunction (PNF), the most severe form of EAD, leads to death or retransplantation within 7 days. The etiology of EAD is multifactorial, including donor, recipient, and surgery-related factors, and largely driven by ischemia-reperfusion injury (IRI)...

OBJECTIVE: By constructing a predictive model using machine learning and deep learning technologies, we aim to understand the risk factors for postoperative intestinal obstruction in laparoscopic colorectal cancer patients, and establish an effective artificial intelligence-based predictive model to guide individualized prevention and treatment, thus improving patient outcomes. METHODS: We constructed a model of the artificial intelligence algorithm in Python. Subjects were randomly assigned to either a training set for variable identification and model construction, or a test set for testing model performance, at a ratio of 7:3...

New artificial intelligence tools have been developed that have implications for medical usage. Large language models (LLMs), such as the widely used ChatGPT developed by OpenAI, have not been explored in the context of anesthesiology education. Understanding the reliability of various publicly available LLMs for medical specialties could offer insight into their understanding of the physiology, pharmacology, and practical applications of anesthesiology. An exploratory prospective review was conducted using 3 commercially available LLMs--OpenAI's ChatGPT GPT-3...

BACKGROUND: The diagnosis of failure to progress, the most common indication for intrapartum cesarean delivery, is based on the assessment of cervical dilation and station over time. Labor curves serve as references of expected changes in dilation and fetal descent. The labor curves of Friedman, Zhang et al and others are based on time alone and derived from mothers with spontaneous labor onset. However, labor induction is now common, and clinicians also consider other factors when assessing labor progress...

BACKGROUND: Contamination of the breathing circuit and medication preparation surface of an anesthesia machine can increase the risk of cross-infection. OBJECTIVE: To evaluate the contamination of the anesthetic medication preparation surface, respiratory circuits, and devices used in general anesthesia with assisted mechanical ventilation. DESIGN AND SETTING: Cross-sectional, quantitative study conducted at the surgical center of a philanthropic hospital, of medium complexity located in the municipality of Três Lagoas, in the eastern region of the State of Mato Grosso do Sul...

OBJECTIVE: We aimed to evaluate the effects of cardiopulmonary bypass (CPB) machines used in coronary artery bypass grafting surgeries on cerebral perfusion by performing cerebral oximetry monitoring [near-infrared spectroscopy (NIRS)], S100-β protein measurements, and neurocognitive function assessment tests using both pulsatile and non-pulsatile modes. METHODS: A total of 44 patients, 22 non-pulsatile (Group NP) and 22 pulsatile (Group P), were included in the study...

PURPOSE: Preventing the spread of pathogens in the anesthesia work area reduces surgical site infections. Improved cleaning reduces the percentage of anesthesia machine samples with ≥ 100 colony-forming units (CFU) per surface area sampled. Targeting a threshold of < 100 CFU when cleaning anesthesia machines may be associated with a lower prevalence of bacterial pathogens. We hypothesized that anesthesia work area reservoir samples returning < 100 CFU would have a low (< 5%) prevalence of pathogens...

The role of point-of-care ultrasonography in the perioperative setting has expanded rapidly over recent years. Revolutionizing this technology further is integrating artificial intelligence to assist clinicians in optimizing images, identifying anomalies, performing automated measurements and calculations, and facilitating diagnoses. Artificial intelligence can increase point-of-care ultrasonography efficiency and accuracy, making it an even more valuable point-of-care tool. Given this topic's importance and ever-changing landscape, this review discusses the latest trends to serve as an introduction and update in this area...

This study uses machine learning and population data to analyze major determinants of blood transfusion among patients with hip arthroplasty. Retrospective cohort data came from Korea National Health Insurance Service claims data for 19,110 patients aged 65 years or more with hip arthroplasty in 2019. The dependent variable was blood transfusion (yes vs no) in 2019 and its 31 predictors were included. Random forest variable importance and Shapley Additive Explanations were used for identifying major predictors and the directions of their associations with blood transfusion...

Background : Hypotension is common in the post-anesthesia care unit (PACU) and intensive care unit (ICU), and is associated with adverse patient outcomes. The Hypotension Prediction Index (HPI) algorithm has been shown to accurately predict hypotension in mechanically ventilated patients in the OR and ICU and to reduce intraoperative hypotension (IOH). Since positive pressure ventilation significantly affects patient hemodynamics, we performed this validation study to examine the performance of the HPI algorithm in a non-ventilated PACU and ICU population...

Intraoperative hypotension (IH) is common in patients receiving general anesthesia and can lead to serious complications such as kidney failure, myocardial injury and increased mortality. The Hypotension Prediction Index (HPI) algorithm is a machine learning system that analyzes the arterial pressure waveform and alerts the clinician of an impending hypotension event. The purpose of the study was to compare the frequency of perioperative hypotension in patients undergoing major abdominal surgery with different types of hemodynamic monitoring...

The brain-based assessments under anesthesia have provided the ability to evaluate pain/nociception during surgery and the potential to prevent long-term evolution of chronic pain. Prior studies have shown that the functional near-infrared spectroscopy (fNIRS)-measured changes in cortical regions such as the primary somatosensory and the polar frontal cortices show consistent response to evoked and ongoing pain in awake, sedated, and anesthetized patients. We take this basic approach and integrate it into a potential framework that could provide real-time measures of pain/nociception during the peri-surgical period...

OBJECTIVES: Inhaled volatile anesthetics support management of status asthmaticus (SA), status epilepticus (SE), and difficult sedation (DS). This study aimed to evaluate the effectiveness, safety, and feasibility of using inhaled anesthetics for SA, SE, and DS in adult ICU and PICU patients. DATA SOURCES: MEDLINE, Cochrane Central Register of Controlled Trials, and Embase. STUDY SELECTION: Primary literature search that reported the use of inhaled anesthetics in ventilated patients with SA, SE, and DS from 1970 to 2021...

Central core disease is a rare muscular disorder in which anesthetic considerations for the prevention of malignant hyperthermia and for avoidance of residual neuromuscular block are required. A 63-year-old woman with central core disease underwent thoracoscopic sublobar lung resection under total IV anesthesia with a prepared anesthetic workstation. The rocuronium-induced neuromuscular block was monitored by using acceleromyography at the left adductor pollicis muscle and the right masseter muscle. The recovery of neuromuscular block at the masseter was slower than that at the adductor pollicis...

BACKGROUND: Transfusion of packed red blood cells (pRBCs) is still associated with risks. This study aims to determine whether renal function deterioration in the context of individual transfusions in individual patients can be predicted using machine learning. Recipient and donor characteristics linked to increased risk are identified. METHODS: This study was registered at ClinicalTrials.gov (NCT05466370) and was conducted after local ethics committee approval...

BACKGROUND: The use of cardiac CT (CCT) has increased dramatically in recent years among patients with pediatric and congenital heart disease (CHD), but little is known about trends and practice pattern variation in CCT utilization for this population among centers. METHODS: A 21-item survey was created to assess CCT utilization in the pediatric/CHD population in calendar years 2011 and 2021. The survey was sent to all non-invasive cardiac imaging directors of pediatric cardiology centers in North America in September 2022...

BACKGROUND: Up to 25% of patients requiring hip or knee arthroplasty have sleep apnea (SA), and these patients have historically been excluded from outpatient programs. The objectives of this study were to evaluate same-day discharge failure as well as 30-day complications, readmissions, and unexpected visits. METHODS: A retrospective case-control study comparing patients who have and do not have SA matched for age, sex and arthroplasty type (total hip arthroplasty [THA], total knee arthroplasty [TKA], unicompartimental knee arthroplasty [UKA]) who underwent primary outpatient surgery between February 2019 and December 2022 in two academic hospitals was conducted...

This systematic review examines the recent use of artificial intelligence, particularly machine learning, in the management of operating rooms. A total of 22 selected studies from February 2019 to September 2023 are analyzed. The review emphasizes the significant impact of AI on predicting surgical case durations, optimizing post-anesthesia care unit resource allocation, and detecting surgical case cancellations. Machine learning algorithms such as XGBoost, random forest, and neural networks have demonstrated their effectiveness in improving prediction accuracy and resource utilization...

Surgeons and anesthesia clinicians commonly face a hemodynamic disturbance known as intraoperative hypotension (IOH), which has been linked to more severe postoperative outcomes and increases mortality rates. Increased occurrence of IOH has been positively associated with mortality and incidence of myocardial infarction, stroke, and organ dysfunction hypertension. Hence, early detection and recognition of IOH is meaningful for perioperative management. Currently, when hypotension occurs, clinicians use vasopressor or fluid therapy to intervene as IOH develops but interventions should be taken before hypotension occurs; therefore, the Hypotension Prediction Index (HPI) method can be used to help clinicians further react to the IOH process...

BACKGROUND: Electroconvulsive therapy (ECT) endures as a definitive treatment for refractory depression and catatonia and is also considered an effective treatment for a number of other severe psychiatric disorders (Lisanby, N Engl J Med 357:1939-1945, 2007)(Weiner and Prudic, Biol Psychiatry 73:105-106, 2013). GA is an essential component of the ECT procedure for various reasons (Lee, Jenkins and Sparkle, Life 11, 2021). Monitoring anesthetic effects on the brain is desirable as anesthetic agents affect seizure duration and recovery (Rasulo, Hopkins, Lobo, et al,  Neurocrit Care 38:296-311, 2023) (Jones , Nittur , Fleming and Applegate,  BMC Anesthesiol 21:105, 2021) (Soehle , Kayser , Ellerkmann and Schlaepfer,  BJA 112:695-702, 2013)...