Sedation and analgesia is an essential part of the emergency work. Presently, for adults, clinical assessment and application of sedation and analgesia has been gradually perfect, but in the face of pediatric patients, clinicians would always concern drug-related adverse reactions as well as a variety of uncontrollable factors, leading to reducing and even ignoring the sedation and analgesia in children. This review focuses on the current research status and relevant evidence of pediatric sedation depth and risk assessment, pain assessment, as well as the principles, application methods, advantages and disadvantages of various commonly used clinical drugs, and the aim is to provide evidence for higher quality sedation and analgesia for children.
Objective To establish and verify the early prediction model of critical illness patients with influenza. Methods Critical illness patients with influenza who diagnosed with influenza in the emergency departments from West China Hospital of Sichuan University, Shangjin Hospital of West China Hospital of Sichuan University, and Panzhihua Central Hospital between January 1, 2017 and June 30, 2020 were selected. According to K-fold cross validation method, 70% of patients were randomly assigned to the model group, and 30% of patients were assigned to the model verification group. The patients in the model group and the model verification group were divided into the critical illness group and the non-critical illness group, respectively. Based on the modified National Early Warning Score (MEWS) and the Simplified British Thoracic Society Score (confusion, uremia, respiratory, BP, age 65 years, CRB-65 score), a critical illness influenza early prediction model was constructed and its accuracy was evaluated. Results A total of 612 patients were included. Among them, there were 427 cases in the model group and 185 cases in the model verification group. In the model group, there were 304 cases of non-critical illness and 123 cases of critical illness. In the model verification group, there were 152 cases of non-critical illness and 33 cases of critical illness. The results of binary logistic regression analysis showed that age, hypertension, the number of days between the onset of symptoms and presentation at the emergency department, consciousness state, white blood cell count, and lymphocyte count, oxygen saturation of blood were the independent risk factors for critical illness influenza. Based on these 7 risk factors, an early prediction model for critical illness influenza was established. The correct percentages of the model for non-critical illness and critical illness patients were 95.4% and 77.2%, respectively, with an overall correct prediction percentage of 90.2%. The results of the receiver operator characteristic curve showed that the sensitivity and specificity of the early prediction model for critical illness influenza in predicting critical illness patients were 0.909, 0.921, and the area under the curve and its 95% confidence interval were 0.931 (0.860, 0.999). The sensitivity, specificity, and area under the curve (0.935, 0.865, 0.942) of the early prediction model for critical illness influenza were higher than those of MEWS (0.642, 0.595, 0.536) and CRB-65 (0.628, 0.862, 0.703). Conclusions The conclusion is that age, hypertension, the number of days between the onset of symptoms and presentation at the emergency department, consciousness, oxygen saturation, white blood cell count, and absolute lymphocyte count are independent risk factors for predicting severe influenza cases. The early prediction model for critical illness patients with influenza has high accuracy in predicting severe influenza cases, and its predictive value and accuracy are superior to those of the MEWS score and CRB-65 score.
In recent years, with the development of ultrasound technology, pulmonary ultrasound is more and more used in the evaluation of patients with heart failure. B-lines are defined as reverberation artifacts starting from the pleural line and extending to the bottom of the screen without disappearing, and moving synchronously with pleural sliding, which are proportional to extravascular lung water in congestive heart failure (CHF). B-lines have the characteristics of no attenuation and synchronous movement with pleural sliding. Pulmonary ultrasound mainly record the numbers and widths of B-lines in the areas when assessing the severity of CHF, which have the characteristics of effectivity, non-invasiveness, instantaneousness, and good repeatability. Currently, there are 4-, 8-, 12-, and 28-subdivision methods for the evaluation of CHF in the pulmonary ultrasound subdivision method. The more subdivisions are, the longer the operation time will be, and the sensitivity and specificity will be different. How to choose a subdivision method is still controversial in clinical practice. Lung ultrasound could be used alone or combined with brain natriuretic peptide, echocardiography, chest X-ray, chest CT scan, etc. in the early diagnosis, assessment of disease severity, evaluation of efficacy, and assessment of prognosis of CHF, with different advantages and disadvantages. This article reviews the application and progress of pulmonary ultrasound in CHF.
Hepatitis B virus related acute-on-chronic liver failure (HBV-ACLF) has the characteristics of rapid progress and high mortality. Artificial liver support system (ALSS) is far superior to standard drug therapy in the treatment of such patients, and is widely used in emergency. ALSS is the use of external mechanical or biological devices to replace a part of the damaged liver function, divided into bioartificial, non-bioartificial liver and a combination of the two. At present, there is no unified sensitive prognostic index and recognized prognostic model for HBV-ACLF in artificial liver treatment. This paper reviews the research progress of prognosis evaluation of ALSS in the treatment of HBV-ACLF, in order to provide reference for clinicians and researchers
Objective To investigate the efficacy of systemic immune inflammation index (SII) at admission and National Institutes of Health Stroke Scale (NIHSS) score immediately after thrombolysis on evaluating the short-term prognosis of neurological function in patients with acute ischemic stroke (AIS) receiving intravenous thrombolysis. Methods Patients with AIS treated with intravenous thrombolysis in the Second People’s Hospital of Chengdu between March 2022 and March 2023 were retrospectively analyzed. The basic data of the patients, NIHSS score at emergency admission, NIHSS score immediately after thrombolysis, modified Rankin Scale (mRS) score 3 months after discharge, and laboratory data at admission were collected, and SII at admission was calculated. According to the mRS score 3 months after discharge, the patients were divided into the good prognosis group (mRS≤2) and the poor prognosis group (mRS>2). Multivariate logistic regression analysis was used to screen out the factors affecting the prognosis of patients, and the receiver operating characteristic curve was drawn to analyze the evaluation effect of SII at admission and NIHSS score immediately after thrombolysis on the poor prognosis of neurological function of patients in the short term. Results A total of 213 patients were enrolled, and the prognosis was poor in 88 patients. Multivariate logistic regression analysis showed that age, onset-to-needle time, uric acid at admission, SII at admission, fasting blood glucose after admission, and NIHSS score immediately after thrombolysis were independent risk factors for poor prognosis in AIS patients (P<0.05). The area under the receiver operating characteristic curve (AUC) of SII at admission for predicting poor prognosis was 0.715, the sensitivity was 55.7%, and the specificity was 84.0%. The AUC of NIHSS score immediately after thrombolysis for predicting poor prognosis of patients was 0.866, the sensitivity was 87.5%, and the specificity was 72.8%. The AUC of SII at admission combined with NIHSS score immediately after thrombolysis for predicting poor prognosis of patients was 0.875, the sensitivity was 84.1%, the specificity was 77.6%, the positive predictive value was 72.5%, and the negative predictive value was 87.4%. SII at admission was positively correlated with NIHSS score at emergency admission, NIHSS score immediately after thrombolysis, and mRS score 3 months after discharge (P<0.05). Conclusion SII at admission can predict the short-term prognosis of neurological function of patients with AIS after thrombolysis therapy, and the combination of SII at admission and NIHSS score immediately after thrombolysis can improve the prediction efficiency.
Objective To analyze the characteristics of patients transferred by ambulances to emergency department before and after coronavirus disease 2019 epidemic, in order to improve the efficiency of emergency triage, optimize the utilization of emergency resources, and provide a reference for standardized tiered medical services in different situation. Methods The patients’ information collected through Wenjuanxing questionnaire was extracted, who were transferred by ambulances to the Emergency Department of West China Hospital of Sichuan University between December 27th, 2018 and April 28th, 2019 (before epidemic), or between December 27th, 2019 and April 28th, 2020 (during epidemic), or between December 27th, 2020 and April 28th, 2021 [in regular epidemic prevention and control period (REPCP)]. The general information, sources, reasons for referral, disease spectrum and triage levels of patients in the three periods were compared. Results There were 3993, 2252 and 1851 cases before epidemic, during epidemic, and in REPCP, respectively. The differences in gender and age among the three periods were not statistically significant (P>0.05). The percentage of referrals from tertiary hospitals in each period was 74.00%, 72.65%, and 76.12%, respectively, which was higher in REPCP than that during epidemic (P<0.05). The percentage of direct referrals from emergency department in each period was 41.00%, 42.14%, and 44.46%, respectively, which was higher in REPCP than that before epidemic (P<0.05). The percentage of two-way referrals in each period was 37.79%, 36.63%, and 34.36%, respectively, which was lower in REPCP than that before epidemic (P<0.05). During epidemic and in REPCP, the proportions of referrals due to “need for surgery” (24.72%, 27.84%, and 28.74%, respectively) and “request by family members” (49.64%, 53.33%, and 56.24%, respectively) increased compared with those before epidemic (P<0.05), while the proportion of referrals due to “critical illness” decreased compared with that before epidemic (40.20%, 35.21%, and 33.17%, respectively; P<0.05); the proportion of referrals due to “diagnosis unknown” decreased in REPCP compared with that before epidemic (15.50%, 13.90%, and 11.89%, respectively; P<0.05). The proportion of acute aortic syndromes in REPCP increased compared with that during epidemic (3.46%, 2.98%, and 4.65%, respectively; P<0.05), the proportion of trauma in REPCP increased compared with that before epidemic (13.72%, 15.76%, and 17.77%, respectively; P<0.05), and the proportion of pneumonia/acute exacerbation of chronic obstructive pulmonary disease during epidemic and in REPCP decreased compared with that before epidemic (8.44%, 3.73%, and 3.84%, respectively; P<0.05). The proportion of critically ill patients referred in each period was 72.88%, 75.58%, and 79.15%, respectively, which was the highest in REPCP (P<0.05). Conclusions The epidemic has a significant impact on emergency ambulance referrals, and emergency triage needs to be continuously optimised and improved in staff, facilities, processes and management. It is necessary to further improve the implementation of hierarchical diagnosis and treatment, strengthen information communication between referral and emergency departments of receiving hospitals, and improve referral efficiency.