Background: This study addresses the critical need for timely and accurate diagnosis of early postoperative infection (EPI) following cardiac surgery. EPI significantly impacts patient outcomes and healthcare costs, making its early detection vital. Objectives: To develop, validate, and clinically implement a machine-learning-based model for diagnosing EPI post-cardiac surgery, enhancing postoperative care. Methods: In this multi-center cohort study spanning 2020 to 2022, data from four medical centers involved 2001 participants. Of these, 1400 were used for trainingand 601 for validation. Several machines-learning algorithms, including XGBoost, random forest, support vector machines, least absolute shrinkage and selection operator, and single-layer neural networks, were applied to develop predictive models. These were compared against a traditional logistic regression model. The model with the highest area under the receiver operating characteristic curve (AUROC) was deemed optimal. Implemented across four centers since 1 January 2023, a retrospective real-world study assessed its clinical applicability. Among 400 patients with an estimated EPI risk above 10%, identified by the optimal model, 55 followed its antibiotic upgrade recommendations (DEICS group). The remaining 345 patients upgraded antibiotics empirically, with 55 in the control group, matched 1:1 with the DEICS group. Clinical utility was evaluated through antibiotic use density (AUD), hospital costs, and ICU stay duration. Results: The XGBoost model achieved the highest performance with an AUROC of 0.96 (95% CI: 0.93–0.98). The calibration curve exhibited strong agreement with Brier scores of 0.02. According to the XGBoost model, the DEICS group significantly demonstrated reduced AUD (P < 0.01) in the matched cohort, along with decreased ICU stay time (median: 5 vs. 6 days, P = 0.01) and hospital costs (median: ¥150 000 vs. median: ¥200 000, P = 0.01) in the EPI cohort. Conclusion: The successful implementation of the XGBoost model facilitates accurate EPI diagnosis, improves postoperative recovery, and lowers hospital costs.

Background: Edoxaban is a novel oral anticoagulant which may decrease the risk of stroke and systemic embolism in patients suffering from atrial fibrillation (AF). However, the decreased efficacy of edoxaban versus warfarin for the avoidance of stroke and systemic embolism in AF with creatinine clearance (CrCl) > 95 mL/min has been reported. The purpose of this meta-analysis is to further clarify the safety (major bleeding) and efficacy (stroke or systemic embolism) of edoxaban for AF patients with various CrCl. Methods: A systematic search of studies on edoxaban and warfarin in AF patients related to renal function was conducted in PubMed, Medline, Web of Science databases, EBSCO, Embase, and the Cochrane Central Register of Controlled Trials. In this meta-analysis (protocol number: PROSPERO CRD 42021245512), we included studies that provide specific data on three outcomes: ischemic stroke or systemic embolism (S/SE), bleeding, and all-cause mortality. Results: This meta-analysis enrolled two randomized controlled trials (RCTs) studies and two retrospective studies that enrolled 28,065 patients. According to CrCl, subjects are divided into three groups (CrCl 30–50 mL/min, CrCl 50–95 mL/min, CrCl > 95 mL/min). In AF patients with CrCl 30–50 mL/min, edoxaban 30 mg daily is similar to warfarin in the prevention of ischemic S/SE and all-cause mortality, resulting in lower bleeding rate and better net clinical outcome (ischemic S/SE: hazard ratio (HR), 0.85, 95% confidence interval (CI), 0.19–1.87; all-cause mortality: HR, 0.65, 95% CI, 0.35–1.19; bleeding: HR, 0.75, 95% CI, 0.60–0.93; net clinical outcome: HR, 0.75, 95% CI, 0.63–0.90). In the group of CrCl 50–95 mL/min, the net clinical outcome was more favorable with edoxaban 60 mg daily than warfarin (HR, 0.81, 95% CI: 0.68–0.96), and there was no significant difference between edoxaban 60 mg daily and warfarin in terms of prevention of bleeding, ischemic S/SE, and all-cause mortality. For AF patients with CrCl > 95 mL/min, there was a statistically significant difference in lower bleeding rate between edoxaban 60 mg daily and warfarin (bleeding: HR: 0.70, 95% CI: 0.58–0.84). There was no differential safety in ischemic S/SE, all-cause mortality, and net clinical outcome. Conclusion: Overall, edoxaban was superior to warfarin in terms of net clinical outcome in various groups of CrCl with AF patients. Although there was no significant difference in net clinical outcome between edoxaban and warfarin for AF patients with CrCl > 95 mL/min, edoxaban is not inferior to warfarin in safety and effectiveness in the various levels of CrCl. Edoxaban may be a more effective and safe treatment than warfarin for patients with chronic kidney disease (CKD) who require anticoagulation. More high-quality and long-term clinical research are needed to further estimate the effects of edoxaban.

Background: Type A aortic dissection (TAAD) remains a significant challenge in cardiac surgery, presenting high risks of adverse outcomes such as permanent neurological dysfunction and mortality despite advances in medical technology and surgical techniques. This study investigates the use of quantitative electroencephalography (QEEG) to monitor and predict neurological outcomes during the perioperative period in TAAD patients. Methods: This prospective observational study was conducted at the hospital, involving patients undergoing TAAD surgery from February 2022 to January 2023. QEEG parameters, including the dynamic amplitude-integrated electroencephalography (aEEG) grade, which assesses changes in brain function over time, alongside aEEG and relative band power (RBP), were monitored and analyzed to assess brain function preoperatively, intraoperatively, and within 2 hours postoperatively. A predictive nomogram model was developed using these QEEG metrics along with other clinical variables to forecast neurological outcomes. Results: In this study, we analyzed the factors contributing to adverse outcomes (AO) and transient neurological dysfunction (TND) following TAAD surgery. For AO, multivariable analysis identified pre-mental status (odds ratio [OR] = 4.652, 95% confidence interval [CI] = 2.316–10.074, P < 0.001), cardiopulmonary bypass time (OR = 1.014, 95% CI = 1.006–1.023, P = 0.001), and dynamic aEEG grade (OR = 9.926, 95% CI = 4.493–25.268, P < 0.001) as independent risk factors. The AO model showed high discriminative ability with an area under the curve of 0.888 (95% CI = 0.818–0.960) and good calibration (Brier score = 0.0728). For TND, significant preoperative differences included dynamic aEEG grade (P < 0.001) and Log(Post-RBP Alpha%) (6.00 vs. 4.00, P < 0.001). Multivariable analysis identified cardiopulmonary bypass time (OR = 1.014, 95% CI = 1.006–1.023, P = 0.001), Post-RBP Alpha% (OR = 0.263, 95% CI = 0.121–0.532, P < 0.001), and dynamic aEEG grade (OR = 12.444, 95% CI = 5.337–30.814, P < 0.001) as independent risk factors. The TND model had an area under the curve of 0.893 (95% CI = 0.844–0.941) and good calibration (Brier score = 0.125). These findings highlight the role of QEEG in predicting postoperative neurological dysfunction in TAAD patients. Conclusion: Through perioperative QEEG monitoring of TAAD patients, combined with clinical indicators such as cardiopulmonary bypass time and preoperative mental status, we developed clinical predictive models for AO and TND after surgery. These models allow for early detection of postoperative brain function impairment, as assessed by QEEG parameters monitored intraoperatively and during the first 2 hours after surgery, a period chosen based on clinical definitions of delayed awakening and supported by the findings of this study. This study provides evidence supporting postoperative brain function monitoring in TAAD patients, with potential clinical implications for improved outcomes.

Background: Despite the positive effect of early post-cardiac surgery exercises, the concern of safety issues is high, indicating the need for standardized and quantitative mobility indicators to enhance early mobilization monitoring in the intensive care unit while ensuring patient safety. This study aimed to compare the safety and efficacy of quantitative phase I exercise versus usual care in patients who have undergone cardiac surgery. Methods: In this non-randomized, single-blind trial, patients following on-pump cardiac surgery were allocated to either quantitative exercise (intervention group, n=114) or usual care (control group, n=114) based on their willingness. Continuous cycling ergometer was used for intervention, and the peak power was recorded for setting next exercise intensity. Noninvasive cardiac output monitoring during exercise was used for safety management. Patients received one time per day, seven sessions in total. Results: Two-way repeated-measure analysis of variance demonstrated significant group and test time difference for forced expiratory volume in 1 s (FEV1) (P=0.01), maximum expiratory pressure (MEP) (P=0.02), peak expiratory flow (PEF) rate (P=0.045), and 6-minute walking distance (6MWD) (P=0.001); more improvement of 6MWD in intervention group (P<0.001). Intervention group showed significant post-test improvements except FEV1/forced vital capacity (FVC). Post-test differences between groups were observed in FEV1 (P=0.02), FVC (P=0.02), MEP (P=0.02), 6MWD (P<0.001), and △6MWD (P<0.001). Analysis of covariance with smoking as covariate showed consistent results. Postoperative stay in intensive-care unit in the intervention group [mean ± standard deviation (SD), 3.0±1.3] was shorter than that in the control group (mean ± SD, 3.5±2.2) (P=0.03). Conclusions: Quantitative phase I exercise applied to patients following cardiopulmonary bypass is safe and recovers respiratory and physical capacity more quickly.

Background: This study investigated the impact of applying the anchored teaching mode with nursing interns on the cardiac surgery intensive care unit (CSICU). Method: A total of 110 interns were divided into a control group (taught through traditional methods) and an experimental group (taught using the anchored teaching mode). The anchored mode, emphasizing studentcentered learning, included creating scenarios, identifying problems, using self-directed and collaborative learning, and evaluating outcomes. Results: Our study found that the experimental group showed significantly higher scores in emergency response ability, nursing skills, and teaching effectiveness compared with the control group at graduation. Conclusion: The findings suggest that implementing the anchored teaching mode can effectively enhance the education of nursing interns on the CSICU, emphasizing the need for further research across different departments and types of hospitals. [ J Contin Educ Nurs. 2024;55(7):359-364.]

Background: Postoperative delirium (POD) is a common neurocognitive complication after type A aortic dissection (TAAD), which seriously affects the recovery of patients, and the current intervention timing and treatment methods are still uncertain. This prospective observational cohort study aimed to discuss the effect of dexmedetomidine on POD in patients undergoing TAAD surgery. Methods: Between February 2022 and March 2023, 167 eligible patients aged 18 to 85 years who underwent TAAD surgery participated in this study. The patients were assigned to either the dexmedetomidine or the control group, which did not receive dexmedetomidine treatment. The primary outcome of interest was the incidence of delirium within five days following surgery. Secondary outcomes included intubation duration, length of stay in the intensive care unit (ICU), total postoperative hospital stay, incidence of non-delirium complications, and all-cause mortality within seven days. To account for differences in baseline characteristics between the groups, propensity score matching (PSM) was utilized. Results: Before PSM, the dexmedetomidine group was made up of 120 patients, whereas the control group comprised 47. The occurrence rate of POD increased from 35.0% in the dexmedetomidine group to 42.6% in the control group, but there was no significant difference [odds ratio (OR) 0.73; 95% confidence interval (CI): 0.37–1.45; P=0.36]. After 1:1 PSM, there were 42 patients in each of the dexmedetomidine and control groups. The occurrence of POD was 28.6% and 45.2% in the dexmedetomidine and control groups, respectively, with no statistically significant difference observed (OR 0.48; 95% CI: 0.20–1.20; P=0.12). The dexmedetomidine group showed a shorter ICU hospitalization time and postoperative hospital stay than the control group, but the differences were not statistically significant. Furthermore, the two groups had no statistical differences in other secondary outcomes. Conclusions: Intraoperative dexmedetomidine did not decrease the occurrence rate of POD in TAAD patients. Additionally, no significant differences were observed between the dexmedetomidine and control groups regarding the occurrence of non-delirium complications, intubation time, ICU hospitalization time, and postoperative hospital stay.