Anesthesiology and Perioperative Science最新文献

Purpose

Sepsis is a life-threatening disorder marked by organ dysfunction due to infection. Transient receptor potential vanilloid 1 (TRPV1) is a non-selective, ligand-gated cation channel activated by multiple stimuli. This study investigates the role of TRPV1 in sepsis-associated encephalopathy (SAE).

Methods

The SAE models of wild-type and TRPV1 knockout (TRPV1^-/-) mice were established through intraperitoneal injection of 10 mg/kg lipopolysaccharide. Brain tissues and serum were collected 24 h post-injection for analysis. Rectal temperature was monitored at 12 and 24 h, and the 7-day survival rate was recorded. Mice were pretreated with capsaicin (CAP), and brain tissue and serum were collected for detection.

Results

TRPV1 expression was significantly elevated in the brain tissues of mice with sepsis. TRPV1^-/- aggravated SAE symptoms, as evidenced by a significant decrease in rectal temperature, a reduced 7-day survival rate, an elevated Murine Sepsis Score, and greater impairment in learning and memory. Mechanistically, TRPV1 deficiency increased NF-κB, pyroptosis-related proteins, and levels of IL-6 and TNF-α in SAE mice. CAP pretreatment significantly reduced abnormal neurons in the CA1 region, decreased NF-κB, Pro-caspase1, and Cleaved-caspase1 in brain tissues, and lowered IL-1β and IL-18 serum levels, with this effect being TRPV1-dependent.

Conclusion

In summary, TRPV1 deficiency worsens SAE-induced damage in mice, associated with activation of NF-κB and pyroptosis pathways. CAP pretreatment improved the damage caused by SAE by activating TRPV1.

Sleep architecture is frequently disrupted after major surgery, leading to acute and chronic postoperative sleep disorders that may contribute to episodic hypoxia, hemodynamic instability, postoperative fatigue, cognitive dysfunction, depression. These all have potentially detrimental impacts on disease regression. Pain is a key driver of postoperative sleep disruption and opioids are widely used for pain management due to their potent analgesic and sedative effects. Opioids are conventionally believed to induce natural sleep and reduce sleep disorders. However, available evidence suggests that opioids can disrupt sleep architecture, leading to sleep deprivation, fragmentation and restriction. This systematic review investigates the detrimental effects of opioids on postoperative sleep and explores the underlying mechanisms responsible for sleep disorders. By synthesizing current evidence wehighlight the risks associated with opioid-centric pain management strategies and advocate for a more balanced approach that optimizes pain relief while mitigating opioid-induced sleep disruption.

Purpose

Rebound pain occurs when peripheral nerve blocks (PNBs) subside and this hampers patient recovery after surgery. This study aims to determine the most effective adjuvant to mitigate rebound pain in adult surgical patients.

Methods

A comprehensive search was conducted for randomized controlled trials (RCTs) that reported rebound pain and utilized perineurally (PN) or intravenously (IV) administered adjuvants. We used multiple databases, including PubMed, Web of Science, the Cochrane Library, Embase, CNKI, Wanfang Data, SinoMed and Chinese medical journals from their inception until September 30, 2024. The primary outcome measured was the incidence of rebound pain. A network meta-analysis was performed using a frequentist approach.

Results

The meta-analysis included three RCTs examining ketamine/esketamine, eight evaluating dexamethasone and one assessing tropisetron. Compared to no adjuvant, IV dexamethasone was found to significantly reduce the incidence of rebound pain (odds ratio [OR] = 0.13, 95% confidence interval [CI]: 0.05, 0.35) and postoperative nausea and vomiting (PONV; OR = 0.33, 95% CI: 0.12, 0.85), while also prolonging the time to onset of rebound pain (mean difference [MD] = 3.95 h, 95% CI: 1.36, 6.53). PN dexamethasone extended the time to onset of rebound pain (MD = 6.57 h, 95% CI: 3.20, 9.93) but did not significantly reduce the incidence of rebound pain or PONV. Ketamine/esketamine was associated with a reduction in the incidence of rebound pain (OR = 0.30, 95% CI: 0.10, 0.89) but did not affect PONV. According to the rank order of surface under the cumulative ranking curve analysis, IV dexamethasone exhibited the lowest incidence of rebound pain and PONV compared to PN dexamethasone, ketamine/esketamine, tropisetron and no adjuvant. PN dexamethasone was most effective in prolonging the onset of rebound pain compared to IV dexamethasone, tropisetron and no adjuvant. The overall quality of evidence was rated as low or very low.

Conclusion

Current evidence, albeit of low quality, indicates that IV dexamethasone is the most effective adjuvant for the prevention of rebound pain, while PN dexamethasone is optimal for delaying its onset. Therefore, a combined approach utilizing both IV and PN dexamethasone following PNB may represent an effective strategy for managing rebound pain in adult surgical patients.

Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a form of extracorporeal circulation that provides cardiopulmonary support in cardiogenic shock unresponsive to conventional therapy. Historically, VA-ECMO was limited to the operating room and primarily used to manage postcardiotomy cardiogenic shock cases. However, with advances in ECMO technology and a better understanding of patient selection criteria, VA-ECMO has expanded its role as a temporary and adaptable intervention in cardiogenic shock of diverse etiologies. This review provides an updated overview of the indications for peripheral VA-ECMO, discussing how recent studies have enhanced our understanding of when VA-ECMO should be considered. In addition, we discuss the feasibility of surgery during VA-ECMO support to improve perioperative planning and tailored anesthetic strategies following ECMO-related physiologic and pharmacological changes.

The rapid development of artificial intelligence (AI) technology, in particular AlphaFold, has greatly improved protein structure prediction and design, reshaped protein biology and expanded research directions in anesthesiology and perioperative medicine. AI relies on deep learning to accurately model key proteins, such as G protein-coupled receptors, to aid drug development. In perioperative medicine, AI improves individualized treatment, patient safety and postoperative recovery through biomarker identification and anesthetic protocol optimization. In addition, AI accelerates anesthetic drug discovery, optimizes drug screening, toxicity prediction and clinical trials to improve the efficiency of research and development. Whilst data interpretation and diversity remain challenges, the continued advancement of AI in the fields of precision medicine and perioperative management will promote the development of individualized anesthesia and precision medicine.