Psilocybin is a hallucinogenic indole alkaloid derived from mushrooms, which is metabolized into psilocin in vivo and exerts biological effects. Clinical studies have shown that psilocybin has the effect of relieving anxiety and depression in cancer patients. Due to its fast onset, significant therapeutic effect, and low addictive nature, psilocybin has the potential to break through the bottleneck of slow action and poor efficacy of existing depression drugs, bringing new hope for the treatment of severe depression and refractory depression. This article will review the pharmacokinetics, antidepressant mechanisms, and research progress of psilocybin, providing a reference for subsequent research.
Poisoning is a frequent reason for patients to seek emergency medical attention, and in severe cases, it can result in severe cardiac disease or cardiac arrest. American Heart Association published the guideline for the management of patients with cardiac arrest or life-threatening toxicity due to poisoning in Circulation on September 18, 2023. Based on the literature, this article interprets the suggestions related to neurotoxic substances in this guideline, mainly involving the clinical management of benzodiazepines, opioids, cocaine, local anesthetics, and sympathomimetic substances poisoning. By interpreting the recommended points of the guide in detail, it is hoped that it will be helpful for the diagnosis and treatment of readers.
On September 18th, 2023, the American Heart Association published clinical management guidelines for patients with poisoning-induced cardiac arrest and critical cardiovascular illness in Circulation. Considering the important role of the guidelines in clinical practice, our team has divided them into three sections for detailed interpretation based on the different toxic effects of the drugs. This article is the second part of the interpretation, which combines the literature to interpret the recommendations related to cardiotoxic substance poisoning in the guidelines, mainly involving the clinical management of beta blockers, calcium channel blockers, digoxin and other cardiac glycosides, as well as sodium channel blocker poisoning, aiming to assist colleagues in their clinical practice through a detailed explanation of the key recommendations in the guidelines.
Objective To develop a novel prediction model based on cerebrospinal fluid (CSF) lactate for early identification of high-risk central nervous system (CNS) infection patients in the emergency setting. Methods Patients diagnosed with CNS infections admitted to the Department of Emergency Medicine of West China Hospital, Sichuan University between January 1, 2020 and December 31, 2023 were retrospectively selected. Patients were classified into a survival group and a death group according to their 28-day survival status, and clinical characteristics were compared between groups. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of 28-day mortality, which were subsequently used to construct a nomogram. Results A total of 173 patients were included, comprising 135 in the survival group and 38 in the death group. Multivariate analysis identified the Acute Physiology and Chronic Health Evaluation Ⅳ (APACHE Ⅳ) score [odds ratio (OR)=1.027, 95% confidence interval (CI) (1.002, 1.055), P=0.034], CSF lactate [OR=1.147, 95%CI (1.025, 1.286), P=0.018], and interleukin-6 [OR=1.002, 95%CI (1.001, 1.004), P=0.002] as independent predictors of 28-day mortality. The integrated model combining APACHE Ⅳ score, CSF lactate, and interleukin-6, demonstrated superior predictive performance compared with the APACHE Ⅳ score alone (P=0.020), and showed good calibration (Hosmer-Lemeshow P=0.50). Conclusions This tool may provide a useful instrument for emergency physicians to assess the 28-day mortality risk in patients with CNS infections, potentially facilitating early and targeted interventions for high-risk individuals. However, as the findings of this study are derived from a single-center retrospective dataset, the clinical applicability of this model requires further external validation through large-scale, prospective, multicenter studies to evaluate its generalizability.