AI Medical Compendium Journal:
BMC anesthesiology

Showing 11 to 20 of 24 articles

Analgesic effect of the ultrasound-guided thoracolumbar paravertebral block in patients undergoing robot-assisted laparoscopic nephrectomy: a randomized controlled trial.

BMC anesthesiology
BACKGROUND: Paravertebral block has similar effect as epidural anesthesia, and has good somatic and visceral analgesic effect. Paravertebral block is widely used in thoracic surgery, but rarely used in abdominal surgery.

Analgesia quality index improves the quality of postoperative pain management: a retrospective observational study of 14,747 patients between 2014 and 2021.

BMC anesthesiology
BACKGROUND: The application of artificial intelligence patient-controlled analgesia (AI-PCA) facilitates the remote monitoring of analgesia management, the implementation of mobile ward rounds, and the automatic recording of all types of key data in ...

Postoperative effects and complications of intrathecal morphine compared to epidural analgesia in patients undergoing intracorporeal robot-assisted radical cystectomy: a retrospective study.

BMC anesthesiology
BACKGROUND: Analgesia after robot assisted radical cystectomy aims to reduce postoperative pain and opioid consumption, while facilitating early mobilization and enteral nutrition and minimizing complications. Epidural analgesia is currently recommen...

Effect of positive end-expiratory pressure on pulmonary compliance and pulmonary complications in patients undergoing robot-assisted laparoscopic radical prostatectomy: a randomized control trial.

BMC anesthesiology
BACKGROUND: To observe the effects of different positive end-expiratory pressure (PEEP) ventilation strategies on pulmonary compliance and complications in patients undergoing robotic-assisted laparoscopic prostate surgery.

Machine learning prediction of postoperative major adverse cardiovascular events in geriatric patients: a prospective cohort study.

BMC anesthesiology
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 adva...

Learning to predict in-hospital mortality risk in the intensive care unit with attention-based temporal convolution network.

BMC anesthesiology
BACKGROUND: Dynamic prediction of patient mortality risk in the ICU with time series data is limited due to high dimensionality, uncertainty in sampling intervals, and other issues. A new deep learning method, temporal convolution network (TCN), make...

Implementation of a machine learning application in preoperative risk assessment for hip repair surgery.

BMC anesthesiology
BACKGROUND: This study aims to develop a machine learning-based application in a real-world medical domain to assist anesthesiologists in assessing the risk of complications in patients after a hip surgery.

Postoperative delirium prediction using machine learning models and preoperative electronic health record data.

BMC anesthesiology
BACKGROUND: Accurate, pragmatic risk stratification for postoperative delirium (POD) is necessary to target preventative resources toward high-risk patients. Machine learning (ML) offers a novel approach to leveraging electronic health record (EHR) d...

Machine learning approach to needle insertion site identification for spinal anesthesia in obese patients.

BMC anesthesiology
BACKGROUND: Ultrasonography for neuraxial anesthesia is increasingly being used to identify spinal structures and the identification of correct point of needle insertion to improve procedural success, in particular in obesity. We developed an ultraso...

Development and validation of a difficult laryngoscopy prediction model using machine learning of neck circumference and thyromental height.

BMC anesthesiology
BACKGROUND: Predicting difficult airway is challengeable in patients with limited airway evaluation. The aim of this study is to develop and validate a model that predicts difficult laryngoscopy by machine learning of neck circumference and thyroment...