A5065720184- Intensive Care Unit Cognitive Disorders
- Cardiac, Anesthesia and Surgical Outcomes
- Anesthesia and Neurotoxicity Research
- Non-Invasive Vital Sign Monitoring
- Phonocardiography and Auscultation Techniques
- Hip and Femur Fractures
- COVID-19 diagnosis using AI
- Emotion and Mood Recognition
- Anesthesia and Sedative Agents
- EEG and Brain-Computer Interfaces
- Cardiac Arrest and Resuscitation
Chinese PLA General Hospital
2022-2024
Chinese People’s Liberation Army 263 hospital
2022-2023
Abstract Aims To compare the performance of logistic regression and machine learning methods in predicting postoperative delirium (POD) elderly patients. Method This was a retrospective study perioperative medical data from patients undergoing non‐cardiac non‐neurology surgery over 65 years old January 2014 to August 2019. Forty‐six variables were used predict POD. A traditional five models (Random Forest, GBM, AdaBoost, XGBoost, stacking ensemble model) compared by area under receiver...
Abstract Background Postoperative delirium (POD) is a common complication among elderly patients after surgery. It unclear whether the systemic immune-inflammation index (SII) can be predictor of POD. We explored prognostic value SII in predicting POD undergoing non-neurosurgery and non-cardiac surgery large retrospective cohort. Methods enrolled between January 2014 August 2019. Univariate multivariate logistic regression analyses were performed to explore correlation as both continuous...
Postoperative delirium is a common complication in older patients, with poor long-term outcomes. This study aimed to investigate risk factors and develop predictive model for postoperative patients after major abdominal surgery. retrospectively recruited 7577 aged ≥ 65 years who underwent surgery between January 2014 December 2018 single hospital Beijing, China. Patients were divided into training cohort (n = 5303) validation 2224) univariate multivariate logistic regression analyses build...
Background: Identifying the risk factors associated with perioperative mortality is crucial, particularly in older patients. Predicting 6-month patients based on large data sets can assist and surgeons clinical decision-making. This study aimed to develop a prediction model of within 6 months after non-cardiac surgery using from 11,894 China. Materials Methods: A multicentre, retrospective cohort was conducted 20 tertiary hospitals. We retrospectively included (aged ≥ 65 years) who underwent...
Introduction: Hemorrhagic shock (HS) is a severe medical emergency. Early diagnosis of HS important for clinical treatment. In this paper, we report flexible material-based heart sound monitoring device which can evaluate the degree through phonocardiogram (PCG) change. Methods: Progressive hemorrhage treatments (H1, H2, and H3 stage) were used in swine to build animal models. The PCG sensor was mounted on chest swine. Routine at same time. Results: This study showed that arterial blood...
Background: Postoperative delirium (POD) is an acute clinical reversible syndrome with many adverse effects. Identifying patients at high risk of developing POD can optimize perioperative management and improve outcomes. This study aims to compare the performance logistic regression machine learning methods for predicting in elderly patients. Methods: was a retrospective medical data from undergoing non-cardiac non-neurology surgery over 65 years old January 2014 August 2019. Forty-six...
Abstract Background Postoperative delirium (POD) is a common complication among elderly patients after surgery. It unclear whether the systemic immune-inflammation index (SII) can be predictor of POD. We explored prognostic value SII in predicting POD undergoing nonneurosurgery and noncardiac surgery large retrospective cohort. Methods enrolled between January 2014 August 2019. Univariate multivariate logistic regression analyses were performed to explore correlation as both continuous...