Background: Circulatory failure is classified into four types of shock (obstructive, cardiogenic, distributive, and hypovolemic) that must be distinguished as each requires a different treatment. Point-of-care ultrasound (POCUS) is widely used in clinical practice for acute conditions, and several diagnostic protocols using POCUS for shock have been developed. This study aimed to evaluate the diagnostic accuracy of POCUS in identifying the etiology of shock.Methods: We conducted a systematic literature search of MEDLINE, Cochrane Central Register of Controlled Trials, Embase, Web of Science, Clinicaltrial.gov, European Union Clinical Trials Register, WHO International Clinical Trials Registry Platform, and University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) until June 15, 2022. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and assessed study quality using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Meta-analysis was conducted to pool the diagnostic accuracy of POCUS for each type of shock. The study protocol was prospectively registered in UMIN-CTR (UMIN 000048025).Results: Of the 1553 studies identified, 36 studies were full-text reviewed, and 12 studies with 1132 patients were included in the meta-analysis. Pooled sensitivity and specificity were 0.82 [95% confidence interval (CI) 0.68–0.91] and 0.98 [95% CI 0.92–0.99] for obstructive shock, 0.78 [95% CI 0.56–0.91] and 0.96 [95% CI 0.92–0.98] for cardiogenic shock, 0.90 [95% CI 0.84–0.94] and 0.92 [95% CI 0.88–0.95] for hypovolemic shock, and 0.79 [95% CI 0.71–0.85] and 0.96 [95% CI 0.91–0.98] for distributive shock, respectively. The area under the receiver operating characteristic curve for each type of shock was approximately 0.95. The positive likelihood ratios for each type of shock were all greater than 10, especially 40 [95% CI 11–105] for obstructive shock. The negative likelihood ratio for each type of shock was approximately 0.2.Conclusions: The identification of the etiology for each type of shock using POCUS was characterized by high sensitivity and positive likelihood ratios, especially for obstructive shock.

Summary: The purpose of this meta‐analysis was to determine the efficacy of lidocaine in preventing laryngospasm during general anaesthesia in children. An electronic search of six databases was conducted. The Preferred Reporting Items for Systematic Reviews and Meta‐analyses ( PRISMA ) guidelines were adhered to. We included randomised controlled trials reporting the effects of intravenous and/or topical lidocaine on the incidence of laryngospasm during general anaesthesia. Nine studies including 787 patients were analysed. The combined results demonstrated that lidocaine is effective in preventing laryngospasm (risk ratio ( RR ) 0.39, 95% CI 0.24–0.66; I ² = 0). Subgroup analysis revealed that both intravenous lidocaine ( RR 0.34, 95% CI 0.14–0.82) and topical lidocaine ( RR 0.42, 95% CI 0.22–0.80) lidocaine are effective in preventing laryngospasm. The results were not affected by studies with a high risk of bias. We conclude that, both topical and intravenous lidocaine are effective for preventing laryngospasm in children.

BACKGROUND: Emergence agitation (EA) is a common complication in children after general anesthesia. The goal of this 2-phase study was (1) to develop a predictive model (EA risk scale) for the incidence of EA in children receiving sevoflurane anesthesia by performing a retrospective analysis of data from our previous study (phase 1) and (2) to determine the validity of the EA risk scale in a prospective observational cohort study (phase 2). METHODS: Using data collected from 120 patients in our previous study, logistic regression analysis was used to predict the incidence of EA in phase 1. The optimal combination of the predictors was determined by a stepwise selection procedure using Akaike information criterion. The β-coefficient for the selected predictors was calculated, and scores for predictors determined. The predictive ability of the EA risk scale was assessed by a receiver operating characteristic (ROC) curve, and the area under the ROC curve (c-index) was calculated with a 95% confidence interval (CI). In phase 2, the validity of the EA risk scale was confirmed using another data set of 100 patients (who underwent minor surgery under general anesthesia). The ROC curve, the c-index, the best cutoff point, and the sensitivity and specificity at the point were calculated. In addition, we calculated the gray zone, which ranges between the two points where sensitivity and specificity, respectively, become 90%. RESULTS: In phase 1, the final model of the multivariable logistic regression analysis included the following 4 predictors: age (logarithm odds ratios [OR], −0.38; 95% CI, −0.81 to 0.00), Pediatric Anesthesia Behavior score (logarithm OR, 0.65; 95% CI, −0.09 to 1.40), anesthesia time (logarithm OR, 0.60; 95% CI, −0.18 to 1.19), and operative procedure (logarithm OR, 2.53; 95% CI, 1.30–3.75 for strabismus surgery and logarithm OR, 2.71; 95% CI, 0.99–4.45 for tonsillectomy). The EA risk scale included these 4 predictors and ranged from 1 to 23 points. In phase 2, the incidence of EA was 39%. The c-index of phase 1 was 0.84 (95% CI, 0.74–0.94), and the c-index of phase 2 was 0.81 (95% CI, 0.72–0.89). The best cutoff point for the EA risk scale was 11 (sensitivity = 87% and specificity = 61%). The gray zone ranged from 10 to 13 points, and included 38% of patients. CONCLUSIONS: We developed and validated an EA risk scale for children receiving sevoflurane anesthesia. In our validation cohort, this scale has excellent predictive performance (c-index > 0.8). The EA risk scale could be used to predict EA in children and adopt a preventive strategy for those at high risk. This score-based preventive approach should be studied prospectively to assess the safety and efficacy of such a strategy.

Background: General anesthesia induces long-lasting cognitive and learning deficits. However, the underlying mechanism remains unknown. The GluA1 subunit of AMPAR is a key molecule for learning and synaptic plasticity, which requires trafficking of GluA1-containing AMPARs into the synapse. Methods: Adult male rats were exposed to 1.8% isoflurane for 2 h and subjected to an inhibitory avoidance task, which is a hippocampus-dependent contextual fear learning paradigm (n = 16 to 39). The in vitro extracellular field potential of hippocampal synapses between the Schaffer collateral and the CA1 was evaluated using a multielectrode recorder (n = 6 per group). GluA1 expression in the synaptoneurosome was assessed using Western blotting (n = 5 to 8). The ubiquitination level of GluA1 was evaluated using immunoprecipitation and Western blotting (n = 7 per group). Results: Seven days after exposure to 1.8% isoflurane for 2 h (Iso_1.8), the inhibitory avoidance learning (control vs. Iso_1.8; 294 ± 34 vs. 138 ± 28, the mean ± SEM [%]; P = 0.002) and long-term potentiation (125.7 ± 6.1 vs. 105.7 ± 3.3; P < 0.001) were impaired. Iso_1.8 also temporarily increased GluA1 in the synaptoneurosomes (100 ± 9.7 vs. 138.9 ± 8.9; P = 0.012) and reduced the GluA1 ubiquitination, a main degradation pathway of GluA1 (100 ± 8.7 vs. 71.1 ± 6.1; P = 0.014). Conclusions: Isoflurane impairs hippocampal learning and modulates synaptic plasticity in the postanesthetic period. Increased GluA1 may reduce synaptic capacity for additional GluA1-containing AMPARs trafficking.