Anesthesiology and Perioperative Science最新文献

Remimazolam is a novel ultra-short-acting benzodiazepine gaining attention for its rapid onset, predictable pharmacokinetics, and favorable safety profile in adult procedural sedation and anesthesia. Early pediatric data suggest it may offer significant advantages over traditional sedatives, including enhanced predictability, improved safety, and faster recovery times. Despite these promising attributes, its routine use in pediatric populations remains underexplored and unestablished. This narrative review examines remimazolam’s pharmacological properties, including its mechanism of action, metabolism, and elimination, and evaluates its safety and efficacy in pediatric sedation. Potential clinical applications are highlighted, such as procedural sedation, intensive care, and anesthesia induction, with comparisons to conventional agents. While initial studies suggest benefits, critical gaps remain in understanding its use in children. These include age-specific dosing strategies, long-term safety considerations, and its efficacy in children with comorbid conditions or undergoing complex procedures. Addressing these gaps will require robust clinical trials and large-scale observational studies. This review synthesizes current evidence and explores the potential of remimazolam to enhance pediatric sedation and anesthesia practices. By identifying key knowledge gaps and proposing future research directions, it aims to inform clinicians and researchers about the role of remimazolam in improving safety and outcomes in pediatric anesthesia.

Pharmacological interventions with the inhaled anesthetic sevoflurane, widely used in cardiac surgery, have been reported to mimic the cardioprotection produced by ischemic conditioning against myocardial ischemia–reperfusion injury. Beneficial effects of sevoflurane conditioning vary with dose, time window and duration and have been reported in a variety of studies involving both laboratory experiments and clinical trials. However, sevoflurane conditioning effects are impaired or lost in subjects with diabetes in both laboratory and clinical settings with mechanisms incompletely understood. This article summarizes the major findings investigating sevoflurane-induced myocardial protection. Our aim is to provide a better understanding of the interrelated but poorly described sevoflurane conditioning signaling pathways. Moreover, this may facilitate the development of more effective therapeutic or preventive strategies for myocardial ischemia-reperfusion injury.

Anesthesia is a fundamental aspect of modern medical practice, ensuring patient safety and comfort during surgical procedures by effectively managing hypnosis and analgesia. The rapid advancement of artificial intelligence (AI) has facilitated the emergence of automated anesthesia systems, significantly enhancing the precision, efficiency, and adaptability of anesthesia management in complex surgical environments. This review provides a comprehensive survey of the existing literature on automated anesthesia, focusing on three key areas: physiological modeling, automatic anesthesia control, and performance evaluation. It critically examines the strengths and limitations of current methodologies, including traditional statistical learning, machine learning and deep learning approaches, while discussing future development trends in the field. By synthesizing recent technological advancements and clinical applications, this work aims to provide valuable insights for researchers and clinicians, promoting the evolution of intelligent and automated anesthesia practices. Ultimately, this review underscores the transformative potential of AI-driven solutions in delivering personalized anesthesia care, optimizing both hypnosis and analgesia, and enhancing surgical outcomes.

Purpose

Persistent opioid use is one of the most common post-operative complications. Identification of at-risk patients pre-operatively is key to reducing post-operative opioid use. We sought to develop a predictive model for persistent post-operative opioid used and to determine if geographic factors from community databases improve model prediction based solely on electronic health records (EHRs) and claims data.

Methods

EHR and claims data for 4,116 opioid-naïve surgical patients older than 18 in North Carolina were linked with census tract-level unemployment data from the American Community Survey and Centers for Disease Control and Prevention data on opioid prescriptions and deaths attributed to drug poisoning. Primary outcome was new persistent opioid use and covariates included patient factors from EHR, claims data, and geographic factors. Multivariable logistic regression models of potential risk factors were evaluated.

Results

6.0% of patients developed new persistent opioid use. Associated risk factors based on multivariable logistic regressions include age (adjusted odds ratio [AOR] 1.08; 95% confidence interval [CI] 1.00, 1.16), back and neck pain (1.82; 1.39, 2.39), joint disorders (1.58; 1.18, 2.11), mood disorders (1.71; 1.28, 2.28), opioid retail prescription (1.04; 1.00, 1.07) and drug poisoning rates (1.33; 1.09, 1.62). On Monte-Carlo cross-validation, the addition of geographic factors to EHRs and claims may modestly improve prediction performance (area under the curve, AUC) of logistic regression models compared to those based on EHRs and claims data (AUC 0.667 (95% CI 0.619, 0.717) vs AUC 0.653 (0.600, 0.706)).

Conclusions

Co-morbidities and area-based factors are predictive of new persistent post-operative opioid use. As the addition of geographic-based factors did not significantly improve performance of multivariable logistic regression, larger samples are needed to fully differentiate models.

Mitochondria, as the cellular end-users of oxygen and responsible for approximately 98% of total body oxygen consumption, play a significant role in the development of organ dysfunction during shock. Therefore, integrating information on mitochondrial oxygen homeostasis with macroscopic observations of macrocirculation and microcirculation is crucial for monitoring critically ill patients or those undergoing high-risk surgery. However, current clinical practice still lack reliable surrogate parameters for assessing mitochondrial function. The Cellular Oxygen METabolism (COMET) monitor, utilizing the protoporphyrin IX triplet state lifetime technique (PpIX-TSLT), represents the first clinical device capable of non-invasive, in vivo measurement of mitochondrial oxygen pressure and oxidative phosphorylation. Recent research suggests that implementing this real-time bedside monitoring will provide additional insights into microcirculatory dynamics and enhance patient management. This review will comprehensively detail the rationale, methodologies, evolution, and clinical applications of the technique, aiming at improving the understanding of mitochondrial pathology in daily clinical practice and facilitating the development of targeted therapeutic strategies.

Graphical Abstract