anesthesia machine

BACKGROUND: The use of pressure-controlled ventilation (PCV) for anesthesia management is becoming more commonly used. Chest drainage is commonly performed after thoracic surgery, and the negative pressure it generates might affect the transpulmonary pressure (TPP). In the present study, we investigated how chest drainage could affect ventilating conditions during PCV. METHODS: We created a hand-made simple thoracic and lung model, which was connected to an anesthesia machine...

In this study, we analyzed Korean and foreign systems, focusing on high-risk medical devices that urgently need to be managed, and we present an life cycle calculation method for determining replacement time. A literature review was conducted to confirm the regulations of the medical device management system and life cycle by country, and a case analysis was performed to verify the replacement evaluation criteria of actual medical institutions. In addition, durability data from the Public Procurement Service, American Hospital Association, and Samsung Medical Center were used to calculate the life cycle of high-risk medical devices...

PURPOSE: Thermal ablation of large tumors may benefit from simultaneous placement of multiple needles, but accurate placement becomes challenging as the number of needles increases. The aim of this work was to evaluate use of personalized needle guidance grid templates based on intraprocedural CT and fabricated at the point of care to implement ablation treatment plans with multiple needles in vivo. METHODS: A plastic frame was designed to hold two parallel plastic guide plates in a rigid relationship, fixed over the abdomen by a mounting arm...

The goal of this study was to identify features in mouse electrocorticogram recordings that indicate the depth of anesthesia as approximated by the administered anesthetic dosage. Anesthetic depth in laboratory animals must be precisely monitored and controlled. However, for the most common lab species (mice) few indicators useful for monitoring anesthetic depth have been established. We used electrocorticogram recordings in mice, coupled with peripheral stimulation, in order to identify features of brain activity modulated by isoflurane anesthesia and explored their usefulness in monitoring anesthetic depth through machine learning techniques...

In order to investigate the correlation between neuroaxon-guiding factor (Netrin-1), deleted in colorectal cancer (DCC), uncoordinated 5B (UNC5B), and vascular endothelial growth factor (VEGF) expression machine in villus tissues of delayed abortion in colorectal cancer, a total of 120 pregnant women are selected from February 2019 to August 2021. The two groups of subjects improve the relevant examinations before surgery and the underwent negative pressure induces abortion hysterectomy guided by abdominal ultrasound under intravenous anesthesia...

BACKGROUND: Mechanical ventilators are essential to patients who become critically ill with acute respiratory distress syndrome (ARDS), and shortages have been reported due to the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We utilized 3D printing (3DP) technology to rapidly prototype and test critical components for a novel ventilator multiplexer system, Vent-Lock, to split one ventilator or anesthesia gas machine between two patients...

BACKGROUND: With the emergence of the concept of value-based care, efficient resource allocation has become an increasingly prominent factor in surgical decision-making. Validated machine learning (ML) models for cost prediction in outpatient spine surgery are limited. As such, we developed and internally validated a supervised ML algorithm to reliably identify cost drivers associated with ambulatory single-level lumbar decompression surgery. METHODS: A retrospective review of the New York State Ambulatory Surgical Database was performed to identify patients who underwent single-level lumbar decompression from 2014 to 2015...

BACKGROUND: Postoperative major adverse cardiovascular events (MACEs) account for more than one-third of perioperative deaths. Geriatric patients are more vulnerable to postoperative MACEs than younger patients. Identifying high-risk patients in advance can help with clinical decision making and improve prognosis. This study aimed to develop a machine learning model for the preoperative prediction of postoperative MACEs in geriatric patients. METHODS: We collected patients' clinical data and laboratory tests prospectively...

STUDY OBJECTIVE: Early post-operative delirium is a common perioperative complication in the post anesthesia care unit. To date it is unknown if a specific anesthetic regime can affect the incidence of delirium after surgery. Our objective was to examine the effect of volatile anesthetics on post-operative delirium. DESIGN: Single Center Observational Study. SETTING: Post Anesthesia Care Units at a German tertiary medical center. PATIENTS: 30,075 patients receiving general anesthesia for surgery...

An acute hypotensive episode (AHE) can lead to severe consequences and complications that threaten patients' lives within a short period of time. How to accurately and non-invasively predict AHE in advance has become a hot clinical topic that has attracted a lot of attention in the medical and engineering communities. In the last 20 years, with rapid advancements in machine learning methodology, this topic has been viewed from a different perspective. This review paper examines studies published from 2008 to 2021 that evaluated the performance of various machine learning algorithms developed to predict AHE...

Anesthesia drug overdose hazards and lack of gold standards in anesthesia monitoring lead to an urgent need for accurate anesthesia drug detection. To investigate the PPG waveform features affected by anesthesia drugs and develop a machine-learning classifier with high anesthesia drug sensitivity. This study used 64 anesthesia and non-anesthesia patient data (32 cases each), extracted from Queensland and MIMIC-II databases, respectively. The key waveform features (total area, rising time, width 75%, 50%, and 25%) were extracted from 16,310 signal recordings (5-s duration)...

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Accurate estimation of surgical risks is important for informing the process of shared decision making and informed consent. Postoperative reintubation (POR) is a severe complication that is associated with postoperative morbidity. Previous studies have divided POR into early POR (within 72 h of surgery) and late POR (within 30 days of surgery). Using data provided by American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP), machine learning classification models (logistic regression, random forest classification, and gradient boosting classification) were utilized to develop scoring systems for the prediction of combined, early, and late POR...

Background: Periprosthetic joint infection may result from pathogen to patient transmission within the environment. The purpose of this study is to evaluate the contamination level of selected high-touch surfaces in the operating room (OR) using a blacklight fluorescent marking system after a manual terminal clean. Methods: Prior to the manual terminal clean, 16 high-touch surfaces were marked using a blacklight fluorescent gel. The marked areas were assessed the next morning for thoroughness of cleaning...

Background: Although unplanned hospital readmission is an important indicator for monitoring the perioperative quality of hospital care, few published studies of hospital readmission have focused on surgical patient populations, especially in the elderly. We aimed to investigate if machine learning approaches can be used to predict postoperative unplanned 30-day hospital readmission in old surgical patients. Methods: We extracted demographic, comorbidity, laboratory, surgical, and medication data of elderly patients older than 65 who underwent surgeries under general anesthesia in West China Hospital, Sichuan University from July 2019 to February 2021...

AIM: Postoperative pulmonary complications (PPCs) can increase the risk of postoperative mortality, and the geriatric population has high incidence of PPCs. Early identification of high-risk geriatric patients is of great value for clinical decision making and prognosis improvement. Existing prediction models are based purely on structured data, and they lack predictive accuracy in geriatric patients. We aimed to develop and validate a deep neural network model based on combined natural language data and structured data for improving the prediction of PPCs in geriatric patients...

PURPOSE: The length of stay (LoS) is one of the most used metrics for resource use in Intensive Care Units (ICU). We propose a structured data-driven methodology to predict the ICU length of stay and the risk of prolonged stay, and its application in a large multicenter Brazilian ICU database. METHODS: Demographic data, comorbidities, complications, laboratory data, and primary and secondary diagnosis were prospectively collected and retrospectively analysed by a data-driven methodology, which includes eight different machine learning models and a stacking model...

Drug efficacy can be improved by understanding the effects of anesthesia on the neurovascular system. In this study, we used machine learning algorithms to predict the risk of infection in postoperative intensive care unit (ICU) patients who are on non-mechanical ventilation and are receiving hydromorphone analgesia. In this retrospective study, 130 patients were divided into high and low dose groups of hydromorphone analgesic pump patients admitted after surgery. The white blood cells (WBC) count and incidence rate of infection was significantly higher in the high hydromorphone dosage group compared to the low hydromorphone dosage groups ( p < 0...

Machine learning (ML) and artificial intelligence (AI) are widely used in many different fields of modern medicine. This narrative review gives, in the first part, a brief overview of the methods of ML and AI used in patient blood management (PBM) and, in the second part, aims at describing which fields have been analyzed using these methods so far. A total of 442 articles were identified by a literature search, and 47 of them were judged as qualified articles that applied ML and AI techniques in PBM. We assembled the eligible articles to provide insights into the areas of application, quality measures of these studies, and treatment outcomes that can pave the way for further adoption of this promising technology and its possible use in routine clinical decision making...

Perioperative cardiac arrest (POCA) is associated with a high mortality rate. This work aimed to study its prognostic factors for risk mitigation by means of care management and planning. A database of 380,919 surgeries was reviewed, and 150 POCAs were curated. The main outcome was mortality prior to hospital discharge. Patient demographic, medical history, and clinical characteristics (anesthesia and surgery) were the main features. Six machine learning (ML) algorithms, including LR, SVC, RF, GBM, AdaBoost, and VotingClassifier, were explored...