Anesthesiology and Perioperative Science最新文献

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

Purpose

This study aims to investigate whether adding fosaprepitant to palonosetron and dexamethasone is effective in preventing postoperative nausea and vomiting (PONV) in high-risk patients undergoing gynecologic surgery.

Methods

Eligible patients undergoing gynecological surgery were randomized into two groups (1:1). One group received fosaprepitant (150 mg) and the other (control) received a placebo infusion. Both groups received a single dose of palonosetron (0.25 mg) and dexamethasone (5 mg) together with therapeutic medication. The primary endpoint was the absence of vomiting and no use of rescue antiemetics during the first 24 h after surgery; complete response rate (CRR).

Results

CRR was significantly higher in the fosaprepitant group compared to the control group 0–24 h after surgery (P = 0.037; relative risk [RR], 1.116; 95% confidence interval [CI], 1.007 to 1.235). Moreover, CRR was also significantly higher during the 24–48 h (P = 0.004; RR, 1.148; 95% CI, 1.045 to 1.261) and 48–72 h (P = 0.039; RR, 1.083; 95% CI, 1.005 to 1.168) observation periods respectively. The complete control rate was higher in the fosaprepitant group than in the control group during the 0–24 h observation period (P = 0.012; RR, 1.367; 95% CI, 1.067 to 1.751). Nausea and rescue antiemetic use were comparable between the two groups. The severity of vomiting was significantly higher in the fosaprepitant group than in the control group on the second day (P = 0.016). Dynamic pain visual analog scale score was lower in the fosaprepitant group and quality of recovery-15 scores were significantly higher in the same group during 0–24 h observation period (P = 0.018 and 0.005, respectively).

Conclusions

The triple combination of fosaprepitant, palonosetron, and dexamethasone was superior in the prevention of PONV after gynecologic surgery in high-risk patients. We suggest that for high-risk patients, a triple combination therapy may be a better choice.

Trial registration

Registered at the Chinese Clinical Trial Registry (https://www.chictr.org.cn/showproj.html?proj=171741) with No. ChiCTR2200060890 on June 13, 2022. Principal investigator: Jingdun Xie.

Postoperative cognitive dysfunction, a common neurological complication in the perioperative period, seriously affects patient survival and prognosis. Its high incidence has made the study of postoperative cognitive dysfunction challenging. Whether the clinical application of dexmedetomidine, a potential neuroprotective drug, can reduce the incidence of postoperative cognitive dysfunction is controversial, although several potential mechanisms by which dexmedetomidine improves postoperative cognitive dysfunction have been identified; therefore, this remains an area in need of further exploration.