Methods To explore the level of delirium knowledge of geriatric nurses in Sichuan province and analyze the factors, so as to provide the basis for systematic and targeted knowledge training on delirium and clinical management. Methods Using the self-designed “the Questionnaire of Elderly Delirium Knowledge”, geriatric nurses from 22 hospitals in Sichuan province were investigated through a convenient sampling method from September 2018 to February 2019. Results A total of 475 geriatric nurses were investigated. The average delirium knowledge score of the 475 geriatric nurses was 69.51±12.42. Multiple linear regression analysis showed that the main factors affecting the score of delirium-related knowledge were the education of nurses (P=0.037), technical title (P<0.001), years of working in the geriatric department (P=0.001), and the level of working hospital (P=0.001). Conclusions The level of delirium knowledge of geriatric nurses is low and can not meet the needs of clinical work. Nursing managers should carry out delirium knowledge training according to the different characteristics of nurses.
Objective To analyze the influencing factors of delirium after endovascular aortic repair, and to provide a basis for clinical nursing and prevention of this condition. Methods Patients who underwent endovascular aortic repair at Fuwai Hospital, Chinese Academy of Medical Sciences from 2018 to 2019 were selected. The Chinese version of the Nursing Delirium Screening Scale (Nu-DESC) was used to assess whether postoperative delirium occurred. Patients with a Nu-DESC score≥ 3 were assigned to the delirium group. Non-delirium patients who had the same surgeon and adjacent surgical order were selected at a 1 : 4 ratio to form the non-delirium group. Univariate analysis was performed on the clinical data of the two groups. Factors with P<0.1 in the univariate analysis and those considered clinically significant were included in a multivariate logistic regression analysis to identify the influencing factors of postoperative delirium. Stratified analysis was conducted based on thoracic endovascular aortic repair (TEVAR) and endovascular abdominal aortic repair (EVAR). Results A total of 213 patients were included, comprising 46 in the delirium group and 167 in the non-delirium group. The overall mean age was (60.3±12.0) years, and 183 (85.9%) were male. Univariate analysis showed that emergency admission, preoperative neutrophil percentage, aortic dissection, surgical duration, intubation time, and ICU stay may be associated with postoperative delirium. Multivariate analysis revealed that longer operative and intubation times were associated with a higher likelihood of delirium. In the stratified analysis, the results for the TEVAR group were consistent with the overall findings, whereas no significant differences were observed in the EVAR group. Conclusion Longer surgical and intubation times are associated with an increased risk of delirium in patients undergoing TEVAR. No significant factors influencing delirium are identified in patients undergoing EVAR.
目的:分析脊柱外科患者术后并发谵妄综合征的原因,总结其诊断、预防、治疗。方法:回顾性分析我科2008年10月至2009年4月脊柱手术167例,其中11例患者术后发生谵妄综合征。结果:11例患者均给予氟哌啶醇5mg im bid治疗,平均使用5.6天,症状缓解;并获3~6月随访,无一例复发谵妄综合征。结论:谵妄综合征是脊柱外科患者术后常见并发症,其发生与年龄,性别,低血糖等有关,目前治疗首选氟哌啶醇。
Postoperative delirium (POD) is a common postoperative complication. Dysregulation of gut flora is involved in POD through mechanisms such as neuroinflammation, oxidative stress, deposition of β-amyloid, and aberrant production of metabolites of gut flora. Therefore, interventions to regulate gut flora, such as probiotics, prebiotics, and faecal microbiota transplantation, can alleviate cognitive dysfunction. This article reviews the mechanisms of gut flora in POD and its prevention and treatment strategies, with the aim of providing new ideas for the clinical prevention and treatment of POD.
ObjectiveTo analyze the predictive value of ensemble classification algorithm of random forest for delirium risk in ICU patients with cardiothoracic surgery. MethodsA total of 360 patients hospitalized in cardiothoracic ICU of our hospital from June 2019 to December 2020 were retrospectively analyzed. There were 193 males and 167 females, aged 18-80 (56.45±9.33) years. The patients were divided into a delirium group and a control group according to whether delirium occurred during hospitalization or not. The clinical data of the two groups were compared, and the related factors affecting the occurrence of delirium in cardiothoracic ICU patients were predicted by the multivariate logistic regression analysis and the ensemble classification algorithm of random forest respectively, and the difference of the prediction efficiency between the two groups was compared.ResultsOf the included patients, 19 patients fell out, 165 patients developed ICU delirium and were enrolled into the delirium group, with an incidence of 48.39% in ICU, and the remaining 176 patients without ICU delirium were enrolled into the control group. There was no statistical significance in gender, educational level, or other general data between the two groups (P>0.05). But compared with the control group, the patients of the delirium group were older, length of hospital stay was longer, and acute physiology and chronic health evaluationⅡ(APACHEⅡ) score, proportion of mechanical assisted ventilation, physical constraints, sedative drug use in the delirium group were higher (P<0.05). Multivariate logistic regression analysis showed that age (OR=1.162), length of hospital stay (OR=1.238), APACHEⅡ score (OR=1.057), mechanical ventilation (OR=1.329), physical constraints (OR=1.345) and sedative drug use (OR=1.630) were independent risk factors for delirium of cardiothoracic ICU patients. The variables in the random forest model for sorting, on top of important predictor variable were: age, length of hospital stay, APACHEⅡ score, mechanical ventilation, physical constraints and sedative drug use. The diagnostic efficiency of ensemble classification algorithm of random forest was obviously higher than that of multivariate logistic regression analysis. The area under receiver operating characteristic curve of ensemble classification algorithm of random forest was 0.87, and the one of multivariate logistic regression analysis model was 0.79.ConclusionThe ensemble classification algorithm of random forest is more effective in predicting the occurrence of delirium in cardiothoracic ICU patients, which can be popularized and applied in clinical practice and contribute to early identification and strengthening nursing of high-risk patients.
ObjectiveTo investigate the risk factors and prevention strategies of postoperative delirium in Stanford B aortic dissection. MethodsClinical data of the patients diagnosed with Stanford B aortic dissection and undergoing endovascular aortic repair from January 2020 to August 2021 in our department were retrospectively collected. Patients were divided into a non-delirium group and a delirium group according to the presence of postoperative delirium. The risk factors for postoperative delirium after Stanford type B aortic dissection and the protective effect of dexmedetomidine on delirium were analyzed. ResultsA total of 659 patients with Stanford type B aortic dissection were enrolled, including 540 males and 119 females with a median age of 58.00 (41.00, 75.00) years. There were 450 patients in the non-delirium group, and 209 patients in the delirium group. There was no statistical difference in gender, body mass index, hypertension, hyperlipidemia, smoking and drinking history, cholesterol triglyceride level, or creatinine glomerular filtration rate (P＞0.05). Age was an independent risk factor for postoperative delirium in Stanford type B aortic dissection (OR=1.392, 95%CI 1.008-1.923, P=0.044). Moreover, whether dexmedetomidine was used or not had no effect on the duration of postoperative delirium (χ2=4.662, P=0.588). Conclusion Age is an independent risk factor for postoperative delirium in patients with Stanford type B aortic dissection. The incidence of postoperative delirium in young patients is lower than that in the patients with middle and elderly age, and it may be of reference value to prevent postoperative delirium. Dexmedetomidine has no significant effect on controlling the duration of postoperative delirium.
ObjectiveTo systematically evaluate the risk prediction models for postoperative delirium in adults with cardiac surgery. MethodsThe SinoMed, CNKI, Wanfang, VIP, PubMed, EMbase, Web of Science, and Cochrane Library databases were searched to collect studies on risk prediction models for postoperative delirium in cardiac surgery published up to January 29, 2025. Two researchers screened the literature according to inclusion and exclusion criteria, used the PROBAST bias tool to assess the quality of the literature, and conducted a meta-analysis of common predictors in the model using Stata 17.0 software. ResultsA total of 21 articles were included, establishing 45 models with 28733 patients. Age, cardiopulmonary bypass time, history of diabetes, history of cerebrovascular disease, and gender were the top five common predictors. The area under the curve (AUC) of the 45 models ranged from 0.6 to 0.926. Fourteen out of the 21 studies had good applicability, while the applicability of the remaining seven was unclear; 20 studies had a high risk of bias. Meta-analysis showed that the incidence of postoperative delirium in adults with cardiac surgery was 18.6% [95%CI (15.7%, 21.6%)], and age [OR=1.04 (1.04, 1.05), P<0.001], history of cerebrovascular disease [OR=1.76 (1.46, 2.06), P<0.001], gender [OR=1.73 (1.43, 2.03), P<0.001], minimum mental state examination score [OR=1.00 (0.82, 1.17), P<0.001], and length of ICU stay [OR=5.59 (4.29, 6.88), P<0.001] weer independent influencing factors of postoperative delirium after cardiac surgery. ConclusionThe risk prediction models for postoperative delirium after cardiac surgery have good predictive performance, but there is a high overall risk of bias. In the future, large-sample, multicenter, high-quality prospective clinical studies should be conducted to construct the optimal risk prediction model for postoperative delirium in adults with cardiac surgery, aiming to identify and prevent the occurrence of postoperative delirium as early as possible.
ObjectiveTo evaluate the quality of guidelines for the management of delirium in adult patients in the last ten years, so as to provide references for updating, selection, implementation guidelines and delirium management optimization.MethodsWe searched guidelines from databases including PubMed, EMbase, WanFang Data and CNKI, and websites of guidelines from January 1st 2010 to September 1st 2019. Guidelines were comprehensively screened, evaluated based on AGREE Ⅱ and data was independently extracted by two researchers.ResultsGuidelines of NICE, RNAO and SIGN had higher scores, while CSCCM’s and IPS’s gained lower. Among domains of AGREE Ⅱ, Domain I (scope and purpose) and IV (clarity of presentation) scored the highest, with a minimum of Domain Ⅱ (stakeholder involvement) and V (applicability). Delirium management focused on screening, prediction, prevention and treatment both pharmacologically and non-pharmacologically, and information support.ConclusionsFuture development of delirium guidelines should follow the methodology of guideline development, update or adjustment, and dedicate to every domain, especially domain of application. Medical staffs can establish our own domestic guidelines based on high quality guidelines, to promote knowledge translation and delirium management.
Postoperative delirium is one of the most common postoperative complications in elderly patients, affecting the outcome of approximately half of surgical patients. The pathogenesis of postoperative delirium is still unclear, but multivariate models of the etiology of postoperative delirium are well-validated and widely accepted, and 40% of postoperative delirium can be effectively prevented by targeting predisposing factors. Benzodiazepines have long been considered as predisposing factors for postoperative delirium. Although benzodiazepines are widely used in clinical practice, most relevant guidelines recommend avoiding the use of benzodiazepines in the perioperative period to reduce the incidence of postoperative delirium. Controversy exists regarding the association of benzodiazepine use with postoperative delirium. This article discusses the results of studies on perioperative benzodiazepines and postoperative delirium.