Anesthesiology and Perioperative Science最新文献

This review provides an evidence-based overview of procedural sedation and analgesia (PSA) practices in emergency department settings, addressing pharmacologic agent selection, monitoring strategies, pediatric- and adult-specific considerations, and current guideline recommendations to support safe and effective PSA across diverse clinical scenarios. Literature published between 2014 and 2024 was reviewed using PubMed, Cochrane Library, Embase, Scopus, and Web of Science, with inclusion limited to English-language, full-text human studies of methodological quality and clinical relevance. Ketamine, propofol, midazolam, and fentanyl remain the most commonly used agents, often administered in combination to balance efficacy and adverse effects, while newer agents such as remimazolam, esketamine, and ciprofol are emerging but lack robust evidence in emergency settings. In pediatric populations, noninvasive administration routes and age-appropriate dosing are emphasized, and adherence to guidelines is consistently associated with improved procedural standardization and patient safety. Point-of-care ultrasound has gained increasing prominence in monitoring strategies, complementing established practices. Overall, when guided by appropriate patient selection, careful pharmacologic planning, and adherence to evidence-based protocols, PSA can be safely and effectively performed in emergency care, and the integration of standardized training, clinical guidelines, and novel monitoring tools will be critical for optimizing outcomes across diverse patient populations. 

Anaesthesiology is evolving from a clinical-based discipline focused primarily on maintaining intraoperative safety into an evidence-based perioperative medicine that emphasizes comprehensive patient care throughout before, during and after surgery journey. This shift has given rise to several important interdisciplinary research directions, which warrant systematic summarisation to better define future perspectives. In this review, we discuss four key intersecting domains: anaesthesia and neuroscience, perioperative organ protection, anaesthesia and cancer, and anaesthesia therapy. Furthermore, based on emerging establishment of perioperative medicine databases that integrate diverse-source data and leverage artificial intelligence for large-scale data analysis, we propose four new perspectives of anaesthesiology including personalized and perioperative management strategy, anaesthetic and organ-protective drugs, anaesthesia techniques and intelligent devices.

Graphical Abstract

Purpose

Sepsis is a complex and life-threatening condition that arises from an abnormal and dysregulated host response to an infection. Developing a practical and interpretable machine learning model to predict mortality in patients with sepsis is essential. To address the limitations of existing sepsis mortality prediction models (insufficient validation and limited interpretability), we developed a streamlined extreme gradient boosting (XGBoost) model that predicts mortality risk using only 7 routine clinical features.

Methods

Medical Information Mart for Intensive Care-IV (MIMIC-IV) data were used to train and internally validate our model. External validation was performed using the eICU-Collaborative Research Database (eICU-CRD). The area under the receiver operating characteristic curve (AUC) was used as the key evaluation index. Differences in model performances were assessed using DeLong's test. The optimal model was simplified using a recursive feature elimination algorithm, and model interpretability was evaluated using SHAP.

Results

Our 7-feature model demonstrated strong performance across training (AUC 0.920), internal validation (AUC 0.900) and external validation (AUC 0.839) cohorts. The selected features—platelet count (at discharge), leukocyte levels (post-antibiotic therapy and at discharge), BUN (post-antibiotic therapy), anion gap (post-antibiotic therapy and at discharge), and ICU length of stay—are objective (eliminating subjective/recall bias) and readily available in clinical practice. SHAP analysis showed that the prognostic contributions of these variables differed before and after antibiotic treatment.

Conclusion

The XGBoost model, built on 7 routine and objective clinical features, quantifies inter-feature relationships to provide mortality risk and treatment thresholds, thereby enabling clinicians to formulate evidence-based therapeutic strategies.

Purpose

Emerging evidence suggests that retinal changes may indicate brain disorders. However, the association between retinal nerve fiber layer (RNFL) thickness and delirium risk has not been investigated. This study examined whether reduced RNFL thickness could predict an increased risk of delirium.

Methods

A total of 42,449 participants without a history of delirium were recruited from the UK Biobank. Optical coherence tomography (OCT) was used for RNFL thickness measurement. Cox proportional hazard models were applied to calculate hazard ratios and 95% confidence intervals for incident delirium risk.

Results

Over a median follow-up of 13.7 years, 1.0% of participants (425) developed delirium. Each 5-μm decrease in RNFL thickness was associated with a 13.6% higher hazard of delirium. The lowest RNFL tertile was linked to a 47.7% higher hazard compared to the highest tertile. A similar correlation was observed for postoperative delirium.

Conclusion

Reduced RNFL thickness is associated with increased delirium risk, highlighting the potential of OCT-based RNFL measurements as a non-invasive tool to identify potential delirium patients.

Background

Atelectasis usually leads to gas exchange and respiratory function impairment, which deteriorate the quality of recovery and increasing mortality. Although recent evidence suggested that the ventilation mode during emergence may affect the occurrence of atelectasis, the optimal ventilation mode remains controversial and randomized controlled trial is needed to clarify the issue.

Methods

In this prospective, randomized, and double-blind controlled trial, adult patients undergoing laparoscopic abdominal surgery at West China Hospital were assigned randomly (1:1:1) into SIMV-PC, SIMV/PSV or intermittent manual assistance ventilation group. The primary outcome was the incidence of atelectasis. The secondary outcomes included the incidence of postoperative hypoxemia, the oxygenation index and a composite of postoperative pulmonary complications (PPCs).

Results

Following an 8.73% dropout rate, a total of 115 patients undergoing elective laparoscopic abdominal surgery were enrolled in the final analysis. The incidence of atelectasis was lower in the pooled SIMV group compared to that in intermittent manual assistance ventilation group (29.5% vs. 48.6%, 95% CI: 0.38 to 0.98; P = 0.045). Sensitivity analyses confirmed the robustness of this result. There were no statistical differences in the secondary outcomes.

Conclusions

Among patients undergoing laparoscopic abdominal surgery, the use of SIMV (SIMV-PC or SIMV/PSV) during emergence resulted in a reduced incidence of early postoperative atelectasis compared to intermittent manual assistance ventilation. Future research with a larger sample size is needed.

Trial registration

ChiCTR2300073366. This study was registered before enrollment (July 7, 2023). Available at: https://www.chictr.org.cn/showproj.html?proj=198051.

Purpose

Many observational studies have revealed intriguing connections between multisite chronic pain (MCP) and psychiatric disorders. Yet, the critical question of causality remains elusive. Our aim was to systematically evaluate the causal relationships between MCP and 11 psychiatric disorder subtypes while identifying potential mediators.

Methods

We adopted a three-stage two-sample bi-directional Mendelian randomization (MR) analysis to ensure the robustness and reliability of our findings. MCP summary data was sourced from a genome-wide association study with 387,649 individuals in the UK Biobank. The discovery stage used summary statistics mainly from the Psychiatric Genomics Consortium, while validation involved MR analysis with data from the FinnGen consortium. Meta-analysis was conducted to pool MR estimates from the discovery and validation stages.

Results

Positive causal relationships were found between MCP and 7 psychiatric disorder subtypes, including depression, panic disorder, anxiety disorders, insomnia, attention deficit hyperactivity disorder, post-traumatic stress disorder, and bipolar disorder, with combined odds ratios ranging from 1.361 (P < 0.00001) to 3.322 (P < 0.0045). Reverse MR revealed bidirectional causal associations between depression and MCP, along with anxiety disorders and MCP (P < 0.05). Additionally, causal links were identified between MCP and smoking initiation, physical activity, body mass index, and changes in human blood cells. Multivariable MR analysis indicated these factors may mediate the relationship between MCP and psychiatric disorders.

Conclusion

Our findings provide novel insights into the involvement of MCP in psychiatric disorders, highlighting potential modifiable risk factors to reduce their incidence.

With the continuous advancement of medical technologies, perioperative anesthesia management decisions are confronted with challenges of complexity and dynamicity, rendering traditional machine learning models insufficient for clinical needs. As one of the breakthrough applications in artificial intelligence, large language models (LLMs) may offer better help for intelligent anesthesia management. LLMs are capable of processing multidimensional and multi-source data, enabling more comprehensive prediction and intervention suggestions, thereby optimizing anesthesia management processes. This review summarizes the current applications of LLMs in anesthesiology and proposes methods for building specialized LLMs to tackle challenges in application. This work albeit mainly in the proposed stage aims to provide references for future development in this field and to promote in-depth research of LLMs in anesthesiology.

Graphical Abstract

Purpose

Frailty is increasingly recognized as a risk factor for surgical complications; however, its association with postoperative pulmonary complications (PPCs) following pulmonary resection remains controversial. This study aimed to systematically evaluate the association between frailty and PPCs in elderly patients undergoing pulmonary resection.

Methods

We systematically searched PubMed, Cochrane Library, Embase, CNKI (China National Knowledge Infrastructure), CBM (China Biology Medicine Disc) , Wanfang Database, Cochrane Central Register of Controlled Trials, and Web of Science from inception to April 2024, using the search terms: (frailty OR frail) AND (pneumonectomy OR lobectomy OR lung resection OR lung cancer). Two investigators independently screened literature, extracted data, and assessed risk of bias. Statistical analyses were performed using Review Manager version 5.4.

Results

Twelve observational studies involving 394,947 patients were included. Frailty was significantly linked to PPCs risk (odds ratio [OR] = 2.96, 95% confidence interval [CI]: 2.15–4.06, I² = 97%). Subgroup analysis indicated that the mFI-11 scale demonstrated a potentially strong predictive value (OR = 3.47, 95% CI: 2.04–5.92, I² = 59%), though this requires validation in larger prospective cohorts.

Conclusion

Frailty is independently associated with an increased risk of PPCs in elderly patients undergoing pulmonary resection.

Systematic review registration

PROSPERO (Prospective Register of Systematic Reviews), registration ID: CRD42024532270.

Background

Post-induction hypotension is a common complications in surgical patients under general anesthesia. Previous evidence indicated preoperative fluid bolus infusion might improve hemodynamic stability after anesthesia induction. But the reported results regarding the postoperative clinical outcomes remains controversary.

Methods

Colloids infusion for Optimal outcomes In Non-cardiac surgery (COIN) trial is a multicenter, double-blinded, parallel-group, randomized controlled trial being conducted in seven tertiary hospitals in China. The trial will enroll and randomize 2,020 adult participants scheduled to undergo noncardiac surgery under general anesthesia with tracheal intubation. Participants will receive either 5 ml/kg of 6% hydroxyethyl starch 130/0.4 electrolyte solution (colloid group) or balanced multiple electrolyte solution (crystalloid group) prior to anesthesia induction. The primary endpoint is the incidence of postoperative complications within 30 days after surgery, defined as Clavien-Dindo classification Grade I or higher (any deviation from the normal postoperative course, including those requiring pharmacological treatment). The primary analysis will be an unadjusted, modified intention-to-treat comparison between patients randomized to colloids group and crystalloids group using chi-square test. The first patient was enrolled on July 12, 2023, and the trial is expected to be completed in June 2025.

Conclusion

The study aims to provide evidence-based insights into reducing postoperative complications in non-cardiac surgery patients undergoing general anesthesia, by comparing the effects of preoperative colloid versus crystalloid solution infusion prior to anesthetic induction. Should the findings demonstrate that colloid solution infusion effectively reduces the 30-day postoperative complication rate, this protocol may contribute to an optimized perioperative management strategy and further promote the clinical adoption of standardized preoperative hemodynamic management.

Trial registration

This study was registered at ClinicalTrials.gov under the identifier NCT05728645 on July 9, 2023, prior to its initiation (http://clinicaltrials.gov).

Purpose

Understanding the current status of a discipline is crucial for its robust and progressive development. In 2018, the first nationwide survey of Chinese anesthesiology provided critical insights into workforce distribution, patient outcomes, infrastructure, and educational resources. Given the dynamic nature of the discipline and the rapidly changing healthcare landscape, a follow-up survey was deemed essential to capture the current status of Chinese anesthesiology.

Methods

This second round cross-sectional nationwide census survey was conducted from February 1, 2022, to August 31, 2022. Participants comprised each hospital department providing anesthesia services across the 31 provinces of mainland China. Data analysis was performed from January 2023 to January 2024. The survey content remains consistent with inaugural study, including general information of the department, hospital level and scale, volume of the anesthesiology department, characteristics of anesthesiologists, and anesthetic caseloads. Data were collected and uploaded using face-to-face interview conducted by trained interviewers. Data quality was controlled by electronic questionnaire and continuous oversight by the investigation committee throughout the whole process.

Results

The nationwide census survey, conducted among 11,505 hospital departments providing anesthesia services in China, identified a total workforce of 105,732 anesthesiologists. This represents a 14% increase in the number of anesthesiologists over the preceding five-year period. The national anesthesiologist-to-population ratio was calculated at 7.5 per 100,000 individuals, with regions boasting higher gross domestic product per capita exhibiting a higher density of anesthesiologists. Additionally, the survey documented 25,056 anesthesia nurses contributing to the anesthesia workforce. Analysis of anesthesiologists' workload indicated a compound annual growth rate of 2.72% from 2018 to 2020. Notably, non-operating room anesthesia cases demonstrated a growth rate approximately 7% higher than that of operating room anesthesia cases, suggesting a discernible shift in clinical practice patterns.

Conclusions

Chinese anesthesiology has experienced rapid growth, underscored by the substantial expansion in its workforce. Nevertheless, persistent challenges necessitate ongoing attention. The findings derived from this nationwide survey provide critical insights for guiding the discipline’s future development and informing evidence-based policy-making.