Volume 4, Issue 1

Cell death is a fundamental process influencing tissue homeostasis and recovery following surgical trauma. In the perioperative context, regulated cell death aids in clearing damaged cells and initiating repair. However, excessive or dysregulated cell death—often exacerbated by ischemia-reperfusion injury, surgical stress, and anesthetic agents—can trigger intense inflammatory responses, leading to complications such as postoperative organ dysfunction (e.g., acute lung injury, delirium, and myocardial injury), impaired wound healing, and increased risk of infections. Mitochondrial dysfunction, a key contributor to these processes, releases damage-associated molecular patterns, further amplifying perioperative inflammation. Emerging evidence suggests that modulating specific cell death pathways (e.g., apoptosis, pyroptosis, necroptosis) and associated inflammatory signaling (e.g., via NLRP3 inflammasome or TLR4 inhibition) may offer novel strategies to improve perioperative outcomes. This review explores the interplay between cell death and inflammation, with emphasis on perioperative relevance, and discusses emerging therapeutic targets that may facilitate precision medicine in surgical patients.

Fractional exhaled nitric oxide (FeNO) is a simple, sensitive and non-invasive marker that can monitor eosinophilic airway inflammation. Its levels are influenced by height, weight, gender, ethnicity and smoking status. FeNO was first introduced as a biomarker to assist in asthma detection, and now plays an important auxiliary role in its diagnosis, management, and prognosis evaluation, including treatment guidance and drug efficacy assessment. With continuous exploration, exhaled nitric oxide has demonstrated utility in a variety of respiratory diseases, including chronic obstructive pulmonary disease, chronic cough and interstitial lung disease. It can also serve as a biomarker after lung surgery to indicate the risk of postoperative complications and impaired lung function. This article summarizes the clinical value of exhaled nitric oxide in common pulmonary diseases, aiming to provide a reference for its clinical application.

Obstetric and perinatal anesthesia, while crucial for maternal and neonatal health, carries inherent risks that necessitate careful management and resource optimization to ensure patient safety. Improvements in anesthesia methods, ultrasound-assisted blocks, multimodal analgesia and accelerated rehabilitation protocols have enabled individualized and precise control of postoperative pain to be achieved more readily. Risk analysis, dynamic observation, and personalized intervention can all significantly lower the rates of hypotension, nausea and vomiting, and nerve injury. International practice variations highlight how resource availability—including staffing levels and expertise—and adherence to clinical guidelines profoundly impact maternal and neonatal outcomes, underscoring that scientific resource optimization is essential for ensuring safety and enhancing efficiency. This perspective discusses the current trends in perinatal anesthesia, focusing on risk minimization and resource utilization. By synthesizing recent advancements and practice variations, we aim to offer a conceptual framework and valuable insights for clinicians making management decisions.

Emergency surgery anesthesia is performed in an extremely time-critical and high-risk setting, where delayed or inaccurate assessment may lead to severe perioperative complications. Patients often present with hemodynamic instability, limited preoperative information, and complex comorbidities, creating major challenges for anesthesiologists to rapidly evaluate airway, circulation, and physiological reserve. Although multiple assessment tools exist, conventional approaches remain fragmented and insufficient for dynamic, real-time decision-making in emergency contexts. There is a clear need for an integrated rapid anesthesia assessment framework that combines advanced monitoring, intelligent decision support, and team-based coordination. This perspective article systematically analyzes rapid assessment models that integrate multimodal point-of-care ultrasound, artificial intelligence–assisted regulation, and closed-loop clinical decision support system (CDSS) protocols. Key applications in perioperative airway management, hemodynamic and respiratory assessment, and risk stratification for special populations, including elderly and pediatric patients, are discussed. We further summarize the rapid titration and hemodynamic advantages of novel anesthetic agents in emergency induction, the role of CDSS and closed-loop communication in clinical emergency management, and the optimization of team collaboration using standardized tools such as Situation–Background–Assessment–Recommendation. Ethical and legal considerations, including informed consent, presumed consent, and proxy decision-making in time-sensitive scenarios, are also addressed. Overall, integrated rapid assessment strategies supported by technology, interdisciplinary teamwork, and ethical safeguards may substantially enhance the safety, efficiency, and clinical outcomes of anesthesia management in emergency surgery, providing a practical framework for future perioperative practice and multicenter validation.

Perioperative management is essential for ensuring surgical safety and improving patient outcomes. With increasing surgical complexity and patient heterogeneity, traditional experience-based decision-making is no longer sufficient to meet the demands of precision medicine. Recent advances in artificial intelligence (AI), big data analytics, and large language models (LLMs) provide new opportunities to transform perioperative clinical decision support. AI-driven models enable accurate risk stratification and prediction of perioperative complications, while big data technologies facilitate multimodal data integration, real-time monitoring, and personalized intervention strategies. Meanwhile, LLMs enhance clinical communication, support medical documentation, and assist knowledge-based clinical decision-making through advanced natural language processing capabilities. However, despite rapid technological development, a comprehensive framework integrating AI, big data, and LLMs for perioperative intelligent decision-making remains insufficiently explored. This article reviews emerging applications of AI in preoperative risk assessment, intelligent anesthesia management, and postoperative complication prediction, and summarizes the role of big data in integrated clinical platforms and personalized treatment strategies. It also highlights the potential of  LLMs in patient education, clinical decision support systems, and automated knowledge synthesis. Overall, integrating AI, big data, and LLMs may establish an interpretable closed-loop perioperative decision-support ecosystem that improves surgical safety, clinical efficiency, and personalized healthcare delivery.

Sepsis-related myocardial dysfunction significantly increases patient mortality and remains a major challenge in critical care medicine. Its pathological mechanisms involve uncontrolled inflammation, excessive oxidative stress, and impaired stress tolerance of cardiomyocytes. Currently, no specific treatment methods are available. Although supportive treatment remains the mainstream in clinical practice, effective interventions for septic myocardial injury are still lacking. This review systematically summarizes the cardioprotective effects of traditional Chinese medicine (TCM) preparations, including Xuebijing injection (containing safflower, red peony root, and salvia miltiorrhiza) and Shenfu Injection (containing ginseng and aconite), in cell and animal models. The mechanisms include antioxidation, anti-inflammation, and enhancement of cardiomyocyte resistance to injury. Some of these preparations have been recommended in the "Guidelines for the Diagnosis and Treatment of Sepsis" in China and are used as adjunctive treatments in intensive care units (ICUs). Preliminary clinical studies suggest  that these agents may improve microcirculation and potentially enhance survival rates. This review not only highlights the multi-target potential of TCM in sepsis-induced myocardial injury but also provides a direction for future high-quality mechanistic research and international multicenter randomized controlled trials, thereby facilitating the integration of traditional medicine into modern critical care practice.

Background: Current prognostic research on sepsis-associated encephalopathy (SAE) predominantly focuses on elderly populations, while independent risk markers for young patients remain unclear. Objective: To investigate the prognostic value of red cell distribution width (RDW) for 30-day mortality in young SAE patients admitted to the intensive care unit (ICU). Methods: This retrospective cohort study analyzed 1,594 SAE patients (18-65 years) from the MIMIC-IV database. Using propensity score matching  (1:1 nearest-neighbor matching), 352 matched pairs were generated. RDW-mortality association was assessed through restricted cubic splines, multivariable Cox regression, and Kaplan-Meier analysis. Results: Among the 1,594 young patients with SAE analyzed, 144 subjects (9.0%) passed away within 30 days following their ICU admission. Non-survivors exhibited significantly higher baseline RDW than survivors (17.5±3.1 versus 14.9±2.4, P<0.001). Patients exhibiting elevated RDW showed higher rates of hepatic disorders, clotting dysfunction, and impaired kidney function (all P<0.001). RDW and 30-day post-ICU admission mortality were nonlinearly related. After matching (standardized mean difference <0.1 for all covariates), higher RDW values showed a notable association with greater mortality risk over a 30-day period (hazard ratio [HR]=2.7, 95% confidence interval [CI]: 1.4-5.3, P=0.003). Also, after comprehensive adjustment for covariates, each 1-unit increase in RDW was still associated with a 20% rise in the risk of death (HR=1.2, 95% CI: 1.1-1.4, P<0.001). Kaplan-Meier curves confirmed reduced 30-day survival in high-RDW group (log-rank test, P=0.002). Conclusions: Elevated RDW at ICU admission independently predicts 30-day mortality in young SAE patients.

Minimally invasive surgery (MIS) has been developed based on the concept of minimum trauma and maximal function, epitomizing the advancement in modern surgery. Following the introduction of laparoscopy in the 1980s, MIS has continued to evolve into multiple modalities, including single-incision surgery, natural orifice transluminal endoscopic surgery, and robotic surgery. The advancements in imaging, artificial intelligence (AI) and robotization have come together to enhance not only the precision and safety of operations, but also the visualization and technical feasibility even in very complex cases. Numerous investigations have shown that MIS, compared with open surgery, decreases blood loss, reduces complication rates, shortens hospital day, and improves postoperative quality of life. The use of AI has brought surgery to the new age of machine intelligence and data-based decision making. Nevertheless, ethical and legal barriers, inadequate physician training programs, and uneven distribution of resources are obstacles to its wider implementation. The next wave of MIS, will be characterized by intelligence and personalization, incorporating AI navigation, augmented reality, and a multi-disciplinary approach.

With advancements in surgical techniques and increasing complexity of patients' underlying conditions, the management of perioperative bleeding and coagulation disorders has intensified. Clinical practice faces issues such as non-standardized monitoring, inconsistent management protocols for specific patient populations, and unclear thresholds for blood transfusion and hemostatic agent administration. Based on evidence-based principles and integrating the latest evidence since 2020, the task force developed this consensus, titled "Expert Opinion on Perioperative Management of Bleeding and Coagulation in Anesthesiology (2026 Edition)". Focusing on the entire perioperative process, it covered coagulation assessment and monitoring, indications for blood product transfusion, rational use of hemostatic agents, and individualized strategies for special populations, including patients on antithrombotic therapy and those undergoing cardiac, neurosurgical, orthopedic or obstetric surgery. It emphasized preoperative risk screening, intraoperative dynamic monitoring, and post-operative balance between hemostasis and thrombosis prevention. Clinical decision-making should integrate the patient's baseline condition, surgical type, and real-time monitoring results. This opinion aims to provide standardized, multi-disciplinary guidance, optimize management protocols, reduce transfusion-related risks and thrombotic complications, and ultimately enhance perioperative patient safety and improve outcomes.

Objective: This study integrated network pharmacology and molecular docking to identify the active constituents, core targets, and potential mechanisms of Dunhuang Mofeng ointment in treating rheumatoid arthritis (RA). The therapeutic efficacy was validated using a collagen-induced arthritis (CIA) rat model. Methods: Bioactive compounds and target molecules of Dunhuang Mofeng ointment were identified using R language-based network pharmacological analysis. These were integrated with RA-related differential genes from the GEO database to construct regulatory and protein-protein interaction networks. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to elucidate intervention mechanisms. Molecular docking simulations validated the conformational stability of core targets. A seven-week CIA rat model was established to assess therapeutic effects, including general health, joint swelling, limb deformities, serum inflammatory markers, and mRNA expression of key targets in joint tissues, thereby validating the network pharmacology predictions. Results: The core active ingredients were quercetin, apigenin, luteolin, aloe-emodin,and emodin. Primary therapeutic targets included STAT1, CDK4, CCND1, MCL1, FOS, CDKN1A and MYC, with anti-inflammatory effects mediated through pathways such as JAK-STAT, PI3K-Akt, and Toll-like receptor pathways. After 7 weeks of treatment, CIA rats showed significant improvements, including reduced joint swelling and deformity, decreased pro-inflammatory cytokines, and increased anti-inflammatory cytokine IL-10. MRNA expression of STAT1, CDK4, CCND1, MCL1, FOS, and MYC in joint tissues was significantly downregulated (P<0.05), while CDKN1A expression was upregulated (P<0.001). The medium-dose and Western medicine groups exhibited pronounced therapeutic effects. Conclusion: Dunhuang Mofeng ointment may exert therapeutic effects in RA by modulating pro-inflammatory cytokines and regulating key genes. These findings support its potential as an effective intervention for RA.