Patients In Emergency Intensive Care Unit Research Articles

A predictive model for the classification of emergency intensive care unit patients with systemic inflammatory response syndrome based on a similarity network fusion algorithm

BackgroundIntensive care unit-acquired weakness (ICU-AW) is a prevalent and severe neuromuscular complication in critically ill patients. It is a consequence of critical illness and is characterized by systemic inflammatory response syndrome (SIRS)-induced metabolic stress and multiple organ dysfunctions. Moreover, ICU-AW is one of the most important factors affecting the prognosis of patients with SIRS, Electrophysiological examination is an effective method for early identification and monitoring of the course of the disease and is essential for accurate diagnosis of critical illness neuromyopathy (CINM). The data-intensive ICU environment is ideal for implementing the similarity network fusion (SNF) method. The objective of this study was to establish and validate a ICU-AW predictive model in SIRS patients, providing a practical tool for early clinical prediction. MethodsClinical characteristics, demographic data, longitudinal neurophysiological data, and disease severity indicators of the enrolled patients were recorded. The patient data included nerve conduction, F-wave, and direct muscle stimulation (DMS) data from 94 follow-up visits as well as various scores, including Medical Research Council (MRC), sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation II (APACHE II) scores and C-reactive protein (CRP). This algorithm was used to analyze electrophysiological data of emergency intensive care unit (EICU) patients with SIRS and fully exploit their similarities in age, sex, body mass index, and electrophysiological data by fusing the similarity networks of these patients with different sets of attributes. Existing patients was performed a clustering analysis and predicted the classification of new patients using spectral clustering and label propagation algorithms on the fusion network, respectively. ResultsClassification prediction model categorical of ICUAW in Patients with SIRS was highly consistent with the clinical diagnosis and had high accuracy and discriminative ability. The model captures the importance of advanced age and lung infections as risk factors for ICU-AW and also demonstrates the significant prognostic value of DMS in EICU patients with SIRS and its ability to predict the development of clinical muscle weakness. ConclusionsElectrophysiological abnormalities are a critical feature of both ICU-AW and non-ICU-AW. Modeling the prediction of SIRS patients progressing to ICUAW which is conducive to early intervention, mechanism studies, and patient rehabilitation.

Nomogram Models for Predicting Delirium of Patients in Emergency Intensive Care Unit: A Retrospective Cohort Study.

BackgroundIntensive care unit (ICU) delirium is one of the most common clinical syndromes that results in many adverse events that affect patients, families, and hospitals. To date, there has been no tool for effectively predicting the occurrence of delirium in emergency intensive care unit (EICU) patients.MethodsWe conducted a retrospective cohort study and constructed a prediction model for 319 patients in EICU, who met our inclusion criteria. We analyzed the relationship between patients’ clinical data within 24 hours of admission and delirium, applied univariate and multivariate logistic regression analyses to select the most relevant variables for construction of nomogram models, then applied bootstrapping for internal validation.ResultsA total of five variables, namely stomach and urinary tubes, as well as sedative, mechanical ventilation and APACHE-II scores, were selected for model construction. We generated a total of five sets of models (three sets of construction models and two sets of internal verification models), with similar predictive value. The optimal model was selected, and together with the 5 variables used to construct a nomogram. The AUC of the MFP model in all patients was 0.76 (0.70, 0.82), whereas that in non-elderly patients (<60 years old) for the full model was 0.83 (0.74, 0.91). In elderly patients (≥60 years old), the AUC of the MFP model was 0.82 (0.73, 0.91).ConclusionOverall, the five-marker-based prognostic tool, established herein, can effectively predict the occurrence of delirium in EICU patients.

Epidemiology and risk factors for hospital acquired Clostridium difficile infection and colonization in emergency intensive care unit of a general hospital in Shanghai

To investigate the clinical features, risk factors and prognosis of Clostridium difficile infection/colonization (CDI/CDC) in emergency intensive care unit (EICU) of Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, then provides theoretical basis for clinical treatment. A retrospective case-control study was conducted. The data of EICU patients admitted to Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine from June 2016 to June 2020 were collected. Taking the CDI/CDC patients as research objects [Clostridium difficile (CD) positive group] and the CD negative patients with the same gender and age difference less than 5 years who were admitted to the hospital during the same period as the control (CD negative group). Demographic information, risk factors, prognosis and stool samples were collected. Single factor analysis and binary Logistic regression were used to analyze the CD positive infection rate, risk factors, and hospital death of patients with different clinical characteristics. About 487 patients in EICU were included, 76 cases were taken into CD positive group, CD positive rate was 15.6%, including CDI 11 cases, CDC 65 cases. Among the CD positive group, all of the cases used proton pump inhibitor (PPI), and 75 cases used at least one antibiotic. Seventy-six CD negative patients with or without diarrhea (CD negative group) were included in this study. Among them, 75 patients used PPI and 74 patients used at least one antibiotic. Univariate analysis showed that acute physiology and chronic health evaluation II (APACHE II), duration of hospitalization, and carbapenem use were the risk factors for CDI/CDC. There were significant differences in the above indicators between CD positive group and CD negative group [APACHE II: 18.0 (12.2, 25.8) vs. 10.0 (7.0, 14.0), duration of hospitalization (days): 46.0 (30.5, 72.5) vs. 18.5 (9.2, 37.0), proportion of carbapenems: 81.6% (62/76) vs. 64.5% (49/76), all P < 0.05]. Binary Logistic analysis regression analysis showed that APACHE II score [odds ratio (OR) = 0.802, 95% confidence interval (95%CI) was 0.730-0.882, P < 0.01] and duration of hospitalization (OR = 0.960, 95%CI was 0.942-0.978, P < 0.01) were independent risk factors for CDI/CDC. There was no difference in overall mortality between the CD positive group and CD negative group [27.6% (21/76) vs. 38.2% (29/76), P = 0.167]. Critically ill patients in EICU routinely use PPI and antibiotics, and the use of antibiotics does not affect the CD positive rate. The independent risk factors of CDI/CDC are the APACHE II score and the duration of hospitalization, but fecal CD positive has no obvious influence on death.

Effect of eCASH Nursing Model on Life Self-care Ability, Physical Function, Psychological Function and Cognitive Function of Critical Patients in EICU

To explore and analyze the impact of Emergency Intensive Care Unit (EICU) critical care patients using eCASH nursing mode intervention on patients’ cognitive function, psychological function, physical function and life self-care ability. Randomly selected 142 critically ill patients in our hospital’s EICU ward from January 2018 to October 2019 as study subjects, and grouped them according to the time of admission. 71 patients in the observation group were intervened by the eCASH nursing model, and 71 patients in the control group received regular nursing intervention. Recording the cognitive, psychological, physical and other functions and self-care ability of the two groups of patients. Before nursing, the Bl score of critical patients in the observation group was compared with the control group (P&gt; 0.05). After the intervention of the observation group patients accepted eCASH nursing model, the Bl score was obviously higher than the control group (P &lt;0.05). According to the SCL-90 table scores, there is no significant difference in the scores of each dimension between the two groups before nursing (P&gt; 0.05). Compare before and after nursing and score except for obsessive compulsive disorder and psychosis (P&gt; 0.05). According to the SCL-90 scale score, there is no significant difference in the scores of each dimension between the two groups before nursing (P &lt;0.05). According to the comparison of the two groups of data after nursing, somatization, anxiety, depression, fear, hostility, paranoia and SCL-90 total score in the observation group were significantly lower than that of control group (P &lt;0.05). Before nursing, the cognitive level of the two groups was compared (P&gt; 0.05). After nursing, the HDS score of the observation group was higher than that of the control group (P &lt;0.05). The CM-PPT score was compared, and the data of the two groups before nursing was compared (P&gt; 0.05). The score of observation group after receiving eCASH nursing was higher than that of control group (P &lt;0.05). The study confirmed that eCASH nursing model for EICU critical patients as early as possible has a significant effect on improving patients ’cognitive function, mental state, physical function, etc. At the same time, it can improve patients’ self-care ability in life and is worthy of promotion.

STAPLAg: a convenient early warning score for use in infected patients in the intensive care unit.

Sepsis is a life-threatening disease in the intensive care unit (ICU). The current diagnostic criteria for sequential organ failure assessment (SOFA) scores do not reflect the current understanding of sepsis. We developed a novel and convenient score to aid early prognosis.Retrospective multivariable regression analysis of 185 infected emergency ICU (EICU) patients was conducted to identify independent variables associated with death, to develop the new "STAPLAg" score; STAPLAg was then validated in an internal cohort (n = 106) and an external cohort (n = 78) and its predictive efficacy was compared with that of the initial SOFA score.Age, and initial serum albumin, sodium, PLR, troponin, and lactate tests in the emergency department were independent predictors of death in infected EICU patients, and were used to establish the STAPLAg score (area under the curve [AUC] 0.865). The initial SOFA score on admission was predictive of death (AUC 0.782). Applying the above categories to the derivation cohort yielded mortality risks of 7.7% for grade I, 56.3% for grade II, and 75.0% for grade III. Internal (AUC 0.884) and external (AUC 0.918) cohort validation indicated that the score had good predictive power.The STAPLAg score can be determined early in infected EICU patients, and exhibited better prognostic capacity than the initial SOFA score on admission in both internal and external cohorts. STAPLAg constitutes a new resource for use in the clinical diagnosis of sepsis and can also predict mortality in infected EICU patients. REGISTRATION NUMBER:: ChinCTR-PNC-16010288.

Qualitative study on psychological experience in family members of middle-aged and young patients in emergency intensive care unit

Objective To explore the psychological experience and feelings of family members of middle-aged and young patients in emergency intensive care unit (EICU) . Methods The family members of EICU patients from a hospital were selected by purposive sampling between August and September 2018. The 8 family members of middle-aged and young EICU patients received in-depth semi-structural interview using qualitative methods. Colaizzi method was used for analysis of the data. Results The psychological experience of the 8 family members of middle-aged and young EICU patients could boil down to 5 themes: negative emotions such as anxiety, fear, worry and self-accusation; positive emotions such as hope and facing the reality; heavy economic burden on family; change of social roles; and desire for social support. Conclusions Medical workers should pay attention to the psychological experience of family members, and provide them with psychological and informational support; meanwhile, they should utilise the social support system, and assist family members to get help from hospital, society and community so that family members' psychological burden can be alleviated, thus enabling the recovery and return to society in the middle-aged and young patients. Key words: Intensive care unit; Emergency service, hospital; Middle-aged and young; Psychological experience; Qualitative study

Cell-free DNA increase over first 48 hours in emergency intensive care unit predicts fatal outcome in patients with shock.

ObjectiveTo investigate whether circulating cell-free (cf)-DNA levels are a useful biomarker for survival in patients with shock in the emergency intensive care unit (EICU).MethodsThis prospective observational study enrolled patients admitted to the EICU diagnosed with shock. Blood cf-DNA levels were analysed on admission, and after 24 and 48 h. As a measure of circulating cf-DNA, copy number of the β-globin gene in plasma was assessed using quantitative real-time polymerase chain reaction.ResultsCirculating cf-DNA levels were higher at hospital admission and after 24 h in EICU patients with shock who died than in those who recovered. Change in cf-DNA levels over the first 48 h in critical care was independently associated with 28-day mortality. The critical cut-off value for cf-DNA change over 48 h in predicting 28-day mortality was +16.12% (sensitivity 68.9%, specificity 89.7%).ConclusionsIncreased circulating cf-DNA levels in EICU patients with shock are associated with risk of death and measuring cf-DNA change over 48 h improves risk prediction. The present study suggests that cf-DNA may serve as a viable plasma biomarker of mortality risk in EICU patients with shock.

Freestanding Emergency Critical Care During the Aftermath of Hurricane Sandy: Implications for Disaster Preparedness and Response.

To assess the impact of an emergency intensive care unit (EICU) established concomitantly with a freestanding emergency department (ED) during the aftermath of Hurricane Sandy. We retrospectively reviewed records of all patients in Bellevue's EICU from freestanding ED opening (December 10, 2012) until hospital inpatient reopening (February 7, 2013). Temporal and clinical data, and disposition upon EICU arrival, and ultimate disposition were evaluated. Two hundred twenty-seven patients utilized the EICU, representing approximately 1.8% of freestanding ED patients. Ambulance arrival occurred in 31.6% of all EICU patients. Median length of stay was 11.55 hours; this was significantly longer for patients requiring airborne isolation (25.60 versus 11.37 hours, P<0.0001 by Wilcoxon rank sum test). After stabilization and treatment, 39% of EICU patients had an improvement in their disposition status (P<0.0001 by Wilcoxon signed rank test); upon interhospital transfer, the absolute proportion of patients requiring ICU and SDU resources decreased from 37.8% to 27.1% and from 22.2% to 2.7%, respectively. An EICU attached to a freestanding ED achieved significant reductions in resource-intensive medical care. Flexible, adaptable care systems should be explored for implementation in disaster response. (Disaster Med Public Health Preparedness. 2016;10:496-502).

A Prospective Validation of National Early Warning Score in Emergency Intensive Care Unit Patients at Beijing

Introduction National Early Warning Score (NEWS) was launched in 2012 by the Royal College of Physicians in UK with an aim to improve the assessment of critical patients and timely detection of clinical deterioration. Objective To assess the performance of NEWS in emergency intensive care unit (EICU) patients in Beijing, PROC. Design prospective cohort study. Setting EICU in a university hospital. Methods The inclusion criteria were patients who stayed in the EICU beds under Department of Emergency Medicine, Xuanwu Hospital of Capital Medical University. Data of patients on admission were collected and calculated NEWS. Main outcome measure was death within 24 hours. The ability to predict mortality was assessed by area under the receiver operating characteristic curve (AUROC) analysis. Results Data on 540 consecutive EICU patients were collected from 1st January, 2013 to 31st March, 2013. Scores of 7 or more were associated with increased risk of death (OR=16.8; 95% CI 6.6-42.9). The AUROC for death within 24 h of admission was 0.85 (95% CI 0.79-0.90). Conclusions NEWS is applicable and feasible for EICU patients in Beijing. This study shows that the prediction power of NEWS for death within 24 hours of acutely ill patients attending Xuan Wu Hospital is comparable to that reported for the United Kingdom patients. (Hong Kong j.emerg.med. 2015;22:137-144)

Relationship between serum gastrin levels and severe gastrointestinal dysfunction in emergency intensive care unit patients

Relationship between serum gastrin levels and severe gastrointestinal dysfunction in emergency intensive care unit patients