BACKGROUND Postoperative pulmonary complications(PPCs)are the most common complications following major upper abdominal surgeries,particularly hepatobiliary procedures,and significantly compromise surgical outcomes an...BACKGROUND Postoperative pulmonary complications(PPCs)are the most common complications following major upper abdominal surgeries,particularly hepatobiliary procedures,and significantly compromise surgical outcomes and patients’quality of life.Although the adoption of laparoscopy has lowered their incidence,PPCs remain a frequent and serious concern after hepatobiliary surgery.Existing research on risk factors specific to hepatobiliary surgeries is limited,particularly regarding the epidemiology and risk factors of PPCs in liver and gallbladder surgeries in China.Therefore,this study aimed to investigate the risk factors for PPCs in a large hepatobiliary center.AIM To identify the incidence and risk factors for PPCs following hepatobiliary surgery based on perioperative variables.METHODS Retrospective data were collected from patients who underwent liver,gallbladder,or pancreatic surgery at a hepatobiliary center in China between May 2023 and December 2023.We retrospectively reviewed comprehensive medical records to extract demographic and hospital admission information for determining PPC incidence.Statistically significant variables were initially screened through univariate analysis,followed by binary logistic regression modeling to identify independent predictors of PPCs.Hospitalization expenditures and duration of stay were further contrasted across the study cohorts.RESULTS This study included 1941 patients who underwent liver,gallbladder,or pancreatic surgery,of whom 78 developed PPCs,resulting in an incidence rate of 4.02%.Logistic regression analysis revealed two independent predictors of PPCs in hepatobiliary surgery patients:Age≥75 year(odds ratio=8.350,95%CI:3.521-19.798,P<0.001)and prolonged anesthesia(odds ratio=1.052,95%CI:1.015-1.091,P=0.006).Patients with PPCs had significantly elevated healthcare resource utilization,including higher total hospitalization costs,increased medication expenses,longer hospital stays,and extended postoperative admissions(all P<0.001).CONCLUSION Age≥75 years and prolonged anesthesia emerged as independent predictors of PPCs following hepatobiliary surgery.These complications were correlated with protracted hospitalization and increased healthcare costs.展开更多
Artificial intelligence(Al)and digital twin technologies exhibit significant potential in analyzing and integrating multidimensional datasets and offer novel perspectives for the management of chronic diseases includi...Artificial intelligence(Al)and digital twin technologies exhibit significant potential in analyzing and integrating multidimensional datasets and offer novel perspectives for the management of chronic diseases including diabetes.These technologies offer opportunities for personalizing treatment and potentially reversing the conditions.This review systematically evaluated the advantages and limitations of Al applications,potential for predictive analytics in formulating personalized management strategies,and practical roles of AI and digital twin technologies in diabetes diagnosis and treatment.Special attention was given to their strengths and weaknesses in disease prediction,early detection,and development of individualized management strategies.AI algorithms have demonstrated great efficiency in analyzing large datasets,aiding in the early identification and intervention of prediabetes.Machine learning algorithms,including deep learning neural networks,integrate lifestyle,genetic,and other influencing factors to accurately predict the progression of prediabetes to diabetes.Moreover,Al-driven wearable devices and mobile applications provide real-time monitoring and personalized guidance,thereby effectively mitigating diabetes.This study also explored the challenges of integrating AI and digital twin technologies into clinical practice for diabetes management and broader healthcare domains,focusing on data privacy,need for diverse and comprehensive datasets,and the importance of integrating AI tools into clinical workflows.展开更多
Medical device technology develops rapidly,and the life cycle of a medical device is much shorter than drugs.It is necessary to evaluate the safety and effectiveness ofamedical device in a timelymanner to keep upwith ...Medical device technology develops rapidly,and the life cycle of a medical device is much shorter than drugs.It is necessary to evaluate the safety and effectiveness ofamedical device in a timelymanner to keep upwith technology flux.Bayesian methods provides an efficient approach to addressing this challenge.In this article,we review the characteristics of the Bayesian approach and some Bayesian designs that were commonly used in medical device regulatory setting,including Bayesian adaptive design,Bayesian diagnostic design,Bayesian multiregional design,and Bayesian label expansion study.We illustrate these designs with medical devices approved by the US Food and Drug Administration(FDA).We also review several innovative Bayesian information borrowing methods,and briefly discuss the challenges and future directions of the Bayesian application in medical device trials.Our objective is to promote the use of the Bayesian approach to accelerate the development of innovative medical devices and their accessibility to patients for effective disease diagnoses and treatments.展开更多
基金Supported by the Beijing Tsinghua Changgung Hospital Fund,China,No.12023C01005.
文摘BACKGROUND Postoperative pulmonary complications(PPCs)are the most common complications following major upper abdominal surgeries,particularly hepatobiliary procedures,and significantly compromise surgical outcomes and patients’quality of life.Although the adoption of laparoscopy has lowered their incidence,PPCs remain a frequent and serious concern after hepatobiliary surgery.Existing research on risk factors specific to hepatobiliary surgeries is limited,particularly regarding the epidemiology and risk factors of PPCs in liver and gallbladder surgeries in China.Therefore,this study aimed to investigate the risk factors for PPCs in a large hepatobiliary center.AIM To identify the incidence and risk factors for PPCs following hepatobiliary surgery based on perioperative variables.METHODS Retrospective data were collected from patients who underwent liver,gallbladder,or pancreatic surgery at a hepatobiliary center in China between May 2023 and December 2023.We retrospectively reviewed comprehensive medical records to extract demographic and hospital admission information for determining PPC incidence.Statistically significant variables were initially screened through univariate analysis,followed by binary logistic regression modeling to identify independent predictors of PPCs.Hospitalization expenditures and duration of stay were further contrasted across the study cohorts.RESULTS This study included 1941 patients who underwent liver,gallbladder,or pancreatic surgery,of whom 78 developed PPCs,resulting in an incidence rate of 4.02%.Logistic regression analysis revealed two independent predictors of PPCs in hepatobiliary surgery patients:Age≥75 year(odds ratio=8.350,95%CI:3.521-19.798,P<0.001)and prolonged anesthesia(odds ratio=1.052,95%CI:1.015-1.091,P=0.006).Patients with PPCs had significantly elevated healthcare resource utilization,including higher total hospitalization costs,increased medication expenses,longer hospital stays,and extended postoperative admissions(all P<0.001).CONCLUSION Age≥75 years and prolonged anesthesia emerged as independent predictors of PPCs following hepatobiliary surgery.These complications were correlated with protracted hospitalization and increased healthcare costs.
基金supported by the National Key Research and Development Program of China(2024YFC3607504 for Dr.Dong Li and 2024YFC3607500).
文摘Artificial intelligence(Al)and digital twin technologies exhibit significant potential in analyzing and integrating multidimensional datasets and offer novel perspectives for the management of chronic diseases including diabetes.These technologies offer opportunities for personalizing treatment and potentially reversing the conditions.This review systematically evaluated the advantages and limitations of Al applications,potential for predictive analytics in formulating personalized management strategies,and practical roles of AI and digital twin technologies in diabetes diagnosis and treatment.Special attention was given to their strengths and weaknesses in disease prediction,early detection,and development of individualized management strategies.AI algorithms have demonstrated great efficiency in analyzing large datasets,aiding in the early identification and intervention of prediabetes.Machine learning algorithms,including deep learning neural networks,integrate lifestyle,genetic,and other influencing factors to accurately predict the progression of prediabetes to diabetes.Moreover,Al-driven wearable devices and mobile applications provide real-time monitoring and personalized guidance,thereby effectively mitigating diabetes.This study also explored the challenges of integrating AI and digital twin technologies into clinical practice for diabetes management and broader healthcare domains,focusing on data privacy,need for diverse and comprehensive datasets,and the importance of integrating AI tools into clinical workflows.
文摘Medical device technology develops rapidly,and the life cycle of a medical device is much shorter than drugs.It is necessary to evaluate the safety and effectiveness ofamedical device in a timelymanner to keep upwith technology flux.Bayesian methods provides an efficient approach to addressing this challenge.In this article,we review the characteristics of the Bayesian approach and some Bayesian designs that were commonly used in medical device regulatory setting,including Bayesian adaptive design,Bayesian diagnostic design,Bayesian multiregional design,and Bayesian label expansion study.We illustrate these designs with medical devices approved by the US Food and Drug Administration(FDA).We also review several innovative Bayesian information borrowing methods,and briefly discuss the challenges and future directions of the Bayesian application in medical device trials.Our objective is to promote the use of the Bayesian approach to accelerate the development of innovative medical devices and their accessibility to patients for effective disease diagnoses and treatments.
