Background: Complications following kidney transplantation elevate the risks of readmission and mortality. The aim of this study was to assess the association between the age-adjusted Charlson Comorbidity Index (ACCI) and postoperative complications among kidney transplant (KT) recipients.
Methods: Between January 2015 and March 2021, a study involving 886 kidney transplant recipients at the Third Affiliated Hospital of Sun Yat-sen University was conducted.
Background: Systemic inflammatory response syndrome (SIRS) is a serious postoperative complication among older adult surgical patients that frequently develops into sepsis or even death. Notably, the incidences of SIRS and sepsis steadily increase with age. It is important to identify the risk of postoperative SIRS for older adult patients at a sufficiently early stage, which would allow preemptive individualized enhanced therapy to be conducted to improve the prognosis of older adult patients.
View Article and Find Full Text PDFIntroduction: Postoperative systemic inflammatory response syndrome (SIRS) is common in surgical patients especially in older patients, and the geriatric population with SIRS is more susceptible to sepsis, MODS, and even death. We aimed to develop and validate a model for predicting postoperative SIRS in older patients.
Methods: Patients aged ≥65 years who underwent general anesthesia in two centers of Third Affiliated Hospital of Sun Yat-sen University from January 2015 to September 2020 were included.
Background: The high risk of cross-infection during tracheal intubation has caused excessive occupational anxiety for anaesthesiologists amid the novel coronavirus disease 2019 (COVID-19) pandemic. Currently, there is no effective way to attenuate their anxiety in clinical practice. We found that anaesthesiologist with better protective equipment might experience decreased levels of anxiety during intubation.
View Article and Find Full Text PDFBackground: Early prediction of acute kidney injury (AKI) after liver transplantation (LT) facilitates timely recognition and intervention. We aimed to build a risk predictor of post-LT AKI via supervised machine learning and visualize the mechanism driving within to assist clinical decision-making.
Methods: Data of 894 cases that underwent liver transplantation from January 2015 to September 2019 were collected, covering demographics, donor characteristics, etiology, peri-operative laboratory results, co-morbidities and medications.
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