The advent of general anesthesia (GA) has significant implications for clinical practice. However, the exact mechanisms underlying GA-induced transitions in consciousness remain elusive. Given some similarities between GA and sleep, the sleep-arousal neural nuclei and circuits involved in sleep-arousal, including the 5-HTergic system, could be implicated in GA. Herein, we utilized pharmacology, optogenetics, chemogenetics, fiber photometry, and retrograde tracing to demonstrate that both endogenous and exogenous activation of the 5-HTergic neural circuit between the dorsal raphe nucleus (DR) and basolateral amygdala (BLA) promotes arousal and facilitates recovery of consciousness from sevoflurane anesthesia. Notably, the 5-HT1A receptor within this pathway holds a pivotal role. Our findings will be conducive to substantially expanding our comprehension of the neural circuit mechanisms underlying sevoflurane anesthesia and provide a potential target for modulating consciousness, ultimately leading to a reduction in anesthetic dose requirements and side effects.

BACKGROUND: While the relationship between glycemic variability (GV) and acute kidney injury (AKI) has been a subject of interest, the specific association of GV with persistent AKI beyond 48 hours postoperative after noncardiac surgery is not well-established. METHODS: This retrospective cohort study aimed to describe the patterns of different GV metrics in the immediate 48 hours after noncardiac surgery, evaluate the association between GV indices and persistent AKI within the 7-day postoperative window, and compare the risk identification capabilities of various GV for persistent AKI. A total of 10,937 patients who underwent major noncardiac surgery across 3 medical centers in eastern China between January 2015 and September 2023 were enrolled. GV was characterized using the coefficient of variations (CV), mean amplitude of glycemic excursions (MAGE), and the blood glucose risk index (BGRI). Multivariable logistic regression was used to examine the relationship between GV and AKI. Optimal cutoff values for GV metrics were calculated through the risk identification models, and an independent cohort from the INformative Surgical Patient dataset for Innovative Research Environment (INSPIRE) database with 7714 eligible cases served to externally validate the risk identification capability. RESULTS: Overall, 274 (2.5%) of the 10,937 patients undergoing major noncardiac surgery met the criteria of persistent AKI. Higher GV was associated with an increased risk of persistent AKI (CV: odds ratio [OR] = 1.26, 95% confidence interval [CI], 1.08–1.46; MAGE: OR = 1.31, 95% CI, 1.15–1.49; BGRI: OR = 1.18, 95% CI, 1.08–1.29). Compared to models that did not consider glycemic factors, MAGE and BGRI independently contributed to predicting persistent AKI (MAGE: areas under the curve [AUC] = 0.768, P = .011; BGRI: AUC = 0.764, P = .014), with cutoff points of 3.78 for MAGE, and 3.02 for BGRI. The classification of both the internal and external validation cohorts using cutoffs demonstrated good performance, achieving the best AUC values of 0.768 for MAGE in the internal cohort and 0.777 for MAGE in the external cohort. CONCLUSIONS: GV measured within 48 hours postoperative period is an independent risk factor for persistent AKI in patients undergoing noncardiac surgery. Specific cutoff points can be used to stratify at-risk patients. These findings indicate that stabilizing GV may potentially mitigate adverse kidney outcomes after noncardiac surgery, highlighting the importance of glycemic control in the perioperative period.

Background: While aging is closely associated with increased risk of acute kidney injury (AKI), chronological age often fails to capture the heterogeneity in biological decline among individuals. In contrast, biological age emerges as a more accurate indicator of the aging process. However, the association between accelerated biological aging and postoperative AKI remains unexplored. Therefore, this study aimed to assess the association between accelerated biological aging and postoperative AKI. Methods: We conducted a retrospective cohort study from 2015 to 2023 at three academic medical centers in China, including inpatients who underwent surgery under general anesthesia. Biological age was measured using Phenotypic Age approach. Biological aging was calculated by Phenotypic Age acceleration (PhenoAgeAccel). The primary endpoint was AKI within 7 days after surgery. Secondary endpoints included AKI stage 2 or 3 (AKI 2+) and length of stay (LOS). Results: Among 94 006 patients [median age 62 (51–71) years, 44.0% female], 37.7% were biologically older. The incidence of AKI was 1.62 per 100 person-days. After adjustment, accelerated biological aging was significantly associated with increased risk of AKI [adjusted hazard ratio (aHR) 1.50, 95% confidence interval (CI) 1.42–1.60], AKI 2 + (aHR 2.27, 95% CI 2.06–2.50), and prolonged LOS (adjusted coefficient 1.30, 95% CI 1.06–1.55). Dose-response relationship analyses revealed a monotonic non-linear positive association between PhenoAgeAccel and the risk of AKI. Discussion: Accelerated biological aging may serve as an independent risk factor for postoperative AKI, AKI 2+, and prolonged LOS, highlighting its potential as a target for preoperative risk stratification and intervention.

Background: In general, cerebral blood flow accounts for 10–15% of cardiac output (CO), of which about 75% is delivered through the carotid arteries. Hence, if carotid blood flow (CBF) is constantly proportional to CO with high reproducibility and reliability, it would be of great value to measure CBF as an alternative to CO. The aim of this study was to investigate the direct correlation between CBF and CO. We hypothesized that measurement of CBF could be a good substitute for CO, even under more extreme hemodynamic conditions, for a wider range of critically ill patients. Methods: Patients aged 65–80 years, undergoing elective cardiac surgery were included in this study. CBF in different cardiac cycles were measured by ultrasound: systolic carotid blood flow (SCF), diastolic carotid blood flow (DCF), and total (systolic and diastolic) carotid blood flow (TCF). CO simultaneously was measured by transesophageal echocardiography. Results: For all patients, the correlation coefficients between SCF and CO, TCF and CO were 0.45 and 0.30, respectively, which were statistically significant, but not between DCF and CO. There was no significant correlation between either SCF, TCF or DCF and CO, when CO was <3.5 L/min. Conclusions: Systolic carotid blood flow may be used as a better index to replace CO. However, the method of direct measurement of CO is essential when the patient's heart function is poor.

Background: A critical limitation of current risk assessment in cardiac surgery is its reliance on static preoperative models, which fail to account for dynamic intraoperative physiological changes. This limitation may lead to the oversight of critical factors that can greatly influence patient outcomes. Thus, identifying clinically meaningful phenotypes by mining dynamic intraoperative features and integrating them with multidimensional data is crucial for understanding phenotypic heterogeneity and enabling personalized perioperative care. Methods: This multicenter, retrospective study included adult patients undergoing cardiac surgery with cardiopulmonary bypass at three tertiary hospitals in eastern China (2013–2024) and an external cohort from an internationally public perioperative database (2011–2020). A high-dimensional dataset was constructed by integrating clinical data with high-resolution intraoperative vital sign time series, resulting in a comprehensive feature set composed of 1006 key parameters. An unsupervised agglomerative hierarchical clustering was used to calculate distinct phenotypes. Key clinical features and outcomes were compared across phenotypes, with the reproducibility and generalizability of these identified phenotypes validated in three independent external datasets. Results: From 10 847 eligible surgeries, five distinct clinical phenotypes were identified. Phenotype A (stable hemodynamics) was characterized by intraoperative hemodynamics closest to average cohort values and minimal comorbidities, leading to favorable outcomes. Phenotype B (heart rate instability) uniquely demonstrated a higher chronic comorbidity burden and high intraoperative heart rate variability, while other hemodynamic profiles remained relatively stable. Phenotype C (high blood pressure), comprising older patients with extensive coronary artery disease, was characterized by a low heart rate while blood pressure was maintained at an elevated level. Phenotype D (elevated central venous pressure) was distinguished by the most rapid early-onset organ dysfunction (0–12 h postoperative) and the longest ICU stays. Phenotype E (severe hemodynamic fluctuations), marked by the most profound intraoperative physiological deviations, incurred the highest incidences of both acute kidney injury (66.9%) and acute liver failure (38.8%), and the greatest overall mortality (11.4%). Validation across internal and external cohorts confirmed the reproducibility and generalizability of these distinct phenotypes. Conclusion: Through a data-driven phenotypic analysis utilizing machine learning, various subgroups were identified among heterogeneous surgical patients, each displaying distinct characteristics linked to adverse outcomes. The integration of multidimensional intraoperative vital signs with perioperative data may support the development of more precise, individualized risk stratification and future perioperative management strategies.

Type A aortic dissection (TAAD) is a severe cardiovascular condition associated with high risks for postoperative complications, particularly renal dysfunction. This study investigated whether intraoperative hypotension and venous congestion are important predictors of postoperative kidney injury and major adverse events. We retrospectively analyzed 543 adults undergoing TAAD surgery (2016-2023). Primary outcomes were acute kidney injury (AKI) and acute kidney disease (AKD). Secondary outcomes included death, stroke and composite outcome. Patients were divided into four groups: AKI only, AKD only, AKI and AKD, Non-AKI or AKD. We used restricted cubic spline and multivariate logistic regression models to adjust for confounding factors. AKI or AKD was significantly associated with each 10-minute epoch of central venous pressure (CVP) ≥10, 12, 16, 20 mmHg (all p < 0.001), with each 60-minute epoch of CVP ≥10, 12, 16, 20 mmHg area under the curve (AUC) (all p < 0.001). Regarding death, a 6% to 13% increase rate for each 10-minute epoch of CVP ≥10, 12, 16, 20 mmHg (all p ≤ 0.003), a 5% to 21% increase for each 60-minute epoch of CVP ≥10, 12, 16, 20 mmHg AUC (all p < 0.001). In terms of stroke risk, a 5% increase rate for every 10-minute increase in the CVP AUC above 16 mmHg, and an 11% increased risk for CVP AUC above 20 mmHg (p = 0.039 and p = 0.031, respectively). Elevated CVP and lower MAP levels were linked to postoperative AKI and AKD risk. CVP showed stronger associations with mortality and stroke. Optimizing perioperative hemodynamic management may improve individualized interventions.