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.
Delirium is an acute cognitive disorder caused by a variety of factors which lead to cerebral cortical dysfunction. At present the studies on the pathophysiology of delirium is still very few. But studies on serum biomarker of delirium can help to elucidate the pathophysiological mechanism of delirium, and the studies are significant for delirium diagnosis, severity classification and prediction of long-term outcome. This review examines three major groups of delirium related serum biomarkers: ① risk markers: those that are present or elevated prior to disease onset, including serum chemistries, genetic markers and so on; ② disease markers: those markers elevate with delirium onset and fall when delirium recovery, including acetylcholine and serum anticholinergic activity, serotonin, serum amino acids, and melatonin, interleukin, C-reactive protein; and ③ end products: those that rise in proportion to the consequences of disease, including S-100ß and neuron specific enolase. The three markers mentioned above are helpful to further investigate the mechanism of delirium.
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 analyze whether hypernatremia within 48 hours after cardiac surgery will increase the incidence of delirium which developed 48 hours later after surgery (late-onset delirium).MethodsWe conducted a retrospective analysis of 3 365 patients, including 1 918 males and 1 447 females, aged 18-94 ( 60.53±11.50) years, who were admitted to the Department of Cardiothoracic and Vascular Surgery of Nanjing First Hospital and underwent cardiac surgery from May 2016 to May 2019.ResultsA total of 155 patients developed late-onset delirium, accounting for 4.61%. The incidence of late-onset delirium in patients with hypernatremia was 9.77%, the incidence of late onset delirium in patients without hypernatremia was 3.45%, and the difference was statistically different (P<0.001). The odds ratio (OR) of hypernatremia was 3.028 (95% confidence interval: 2.155-4.224, P<0.001). The OR adjusted for other risk factors including elderly patients, previous history of cerebrovascular disease, operation time, cardiopulmonary bypass time, lactate, hemoglobin≥100 g/L, prolonged mechanical ventilation, left ventricular systolic function, use of epinephrine, use of norepinephrine was 1.524 (95% confidence interval: 1.031-2.231, P=0.032).ConclusionHypernatremia within 48 hours after cardiac surgery may increase the risk of delirium in later stages.
ObjectiveTo systematically evaluate the risk factors for postoperative delirium (POD) in patients undergoing lung resection. MethodsPubMed, Web of Science, The Cochrane Library, CNKI, Wanfang, and VIP databases were searched from the inception to November 7, 2024 for cross-sectional studies, case-control studies, and cohort studies on POD in patients undergoing lung resection. Two researchers independently screened the literature, extracted data, and evaluated the quality of the literature. RevMan 5.4.1 software was used for meta-analysis. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the literature. ResultsA total of 12 studies were included, with 5 574 patients. The quality scores of the literature were all ≥6 points. Meta-analysis results showed that age (≥60 years) [OR=2.43, 95%CI (2.01, 2.93), P<0.01], ASA classification (Ⅳ) [OR=8.74, 95%CI (5.23, 14.61), P<0.01], history of diabetes [OR=12.81, 95%CI (10.45, 15.71), P<0.01], history of cerebrovascular disease [OR=3.00, 95%CI (2.46, 3.67), P<0.01], depression [OR=7.27, 95%CI (5.46, 9.67), P<0.01], squamous cell carcinoma [OR=4.79, 95%CI (1.83, 12.51), P<0.01], malnutrition [OR=5.25, 95%CI (3.35, 8.25), P<0.01], sleep disorders [OR=2.79, 95%CI (2.28, 3.42), P<0.01], and duration of one-lung ventilation during surgery [OR=1.32, 95%CI (1.11, 1.57), P<0.01] are all risk factors for POD, while high body mass index [OR=0.96, 95%CI (0.95, 0.97), P<0.01] is a protective factor for POD. ConclusionAge (≥60 years), ASA classification (Ⅳ), history of diabetes, history of cerebrovascular disease, depression, squamous cell carcinoma, malnutrition, sleep disorders, and duration of one-lung ventilation during surgery are independent risk factors for POD, while high BMI is a protective factor.
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.
ObjectiveTo explore the relevant risk factors for postoperative delirium (POD) in elderly patients undergoing radical colon cancer surgery, and provide a basis for formulating postoperative prevention and treatment measures for POD. MethodsA total of 128 elderly patients diagnosed with colon cancer and underwent radical colon cancer surgery at Xindu District People’s Hospital in Chengdu from January 2018 to December 2021 were included as the study subjects. Patients were divided into two groups according to the score of Delirium Assessment Scale (4AT Scale). The basic data, main perioperative clinical data and laboratory indicators of the two groups were collected, and univariate and logistic regression analysis were carried out to determine the potential risk factors of POD in elderly patients with colon cancer after radical operation. ResultsAccording to the results of the 4AT scale score, a total score of ≥4 points was used as the threshold for determining patient POD. Among 128 patients, there were 29 patients (22.66%) with POD and 99 patients (77.34%) without POD. ① General data comparison: There was no significant difference between the two groups in gender, body mass index, years of education, hypertension, diabetes, smoking history and drinking history (P>0.05), but there was significant difference in age, preoperative mini-mental state examination (MMSE) score and American Society of Anesthesiologists (ASA) grade (P<0.05). ② Comparison of main clinical data during the perioperative period: There was no statistically significant difference between the two groups of patients in ICU treatment, nonsteroidal anti-inflammatory drug treatment, visual analogue scale, and intraoperative hypotension (P>0.05), but there was a statistically significant difference in operative time, anesthesia time, intraoperative blood loss, and dexmedetomidine treatment (P<0.05). ③ Comparison of preoperative laboratory indicators: There was no statistically significant difference between the two groups of patients in terms of hemoglobin, serum albumin, white blood cell count, prognostic nutritional index, neutrophil/lymphocyte ratio, D-dimer, and albumin to fibrinogen ratio (P>0.05). ④ The results of logistic regression analysis showed that low preoperative MMSE score [OR=0.397, 95%CI (0.234, 0.673)], long surgical time [OR=1.159, 95%CI (1.059, 1.267) ], and long anesthesia time [OR=1.138, 95%CI (1.057, 1.226) ] were independent risk factors for the occurrence of POD in elderly colon cancer patients undergoing radical surgery. ConclusionPreoperative MMSE score, operative time, and anesthesia time are closely related to the occurrence of POD in elderly colon cancer radical surgery, worth implementing key perioperative management in clinical practice to prevent and manage POD.
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 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.
Delirium is a common complication in elderly inpatients which could result in cognitive impairment, and increase the risk of disability, fall and mortality. Moreover, it could cause heavy social burden. Even with multiple bedside screening scales to detect delirium, the rate of missed diagnosis is still high. Maybe it is associated with the acute fluctuation and nocturnal onset of delirium. With the development of the intelligence and automation of the electronic medical record (EMR), previous studies have explored the use of EMR to identify delirium patients, and this method provides help for delirium diagnosis and prevention. In this paper, we reviewed and summarized the current situation of research on delirium recognition by EMR, and put forward the development prospect in this method in order to provide basis and lay a foundation for intelligent diagnosis of delirium.