scholarly journals CRB-65: Predictor for Intensive Care Unit Admission in Patients with Biliary Tract Infection Presenting to An Emergency Department

2020 ◽  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Tract Infection ◽  
Hospital Mortality ◽  
Biliary Tract ◽  
Screening Tools ◽  
High Morbidity ◽  
Biliary Tract Infection ◽  
Icu Admission

Objectives: Biliary tract infection (BTI) is a common cause of bacteremia and is associated with high morbidity and mortality. However, studies on screening tools to predict disease severity in BTI patients are lacking. This study aimed to comparatively validate CRB, CRB-65, quick Sequential Organ Failure Assessment (qSOFA), and Systemic Inflammatory Response Syndrome (SIRS) in predicting the clinical outcomes of BTI patients. Methods: This retrospective cohort study included patients with BTI who visited the emergency department of a medical center between February 2018 and March 2020. Baseline patient data were compared to assess the prevalence of intensive care unit (ICU) admission and in-hospital mortality. The effectiveness of CRB, CRB-65, qSOFA, and SIRS scores as indicators of ICU admission and in-hospital mortality was evaluated using the area under the receiver operating characteristic (AUROC) curve. Results: This study included 745 patients, of whom 111 (14.8%) were admitted to the ICU and 20 (2.7%) died in-hospital. AUROC values (95% CI) for predicting ICU admission and in-hospital mortality were as follows: CRB, 0.774 and 0.707 (0.742 –0.803 and 0.673 – 0.739); CRB - 65, 0.816 and 0.735 (0.786 – 0.843 and 0.0.702 – 0.766); qSOFA, 0.779 and 0.724 (03747 – 0.808 and 0.690 – 0.755); and SIRS, 0.686 and 0.659 (0.651 – 0.719 and 0.623 – 0.693), respectively. Conclusions: CRB-65 can be used as useful screening tools to predict ICU admission in patients with BTI on presentation to the emergency department.

scholarly journals LO51: Increased mortality and costs in emergency department sepsis patients with delayed intensive care unit admission

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S24-S24
Author(s):  
S. M. Fernando ◽  
B. Rochwerg ◽  
P. M. Reardon ◽  
K. Thavorn ◽  
N. I. Shapiro ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Rapid Identification ◽  
Multivariable Logistic Regression Model ◽  
Icu Admission ◽  
Icu Length Of Stay ◽  
Improved Outcomes ◽  
Hospital Wards

Introduction: Sepsis remains a major cause of mortality. In the Emergency Department (ED), rapid identification and management of sepsis have been associated with improved outcomes. Following ED assessment, patients with infection may be directly admitted to the Intensive Care Unit (ICU), or alternatively admitted to hospital wards or sent home, with risk of future deterioration necessitating ICU admission. Little is known regarding outcomes and costs of ICU sepsis patients who are initially admitted to a ward or discharged home (delayed ICU admission), as compared to those with direct ICU admission from the ED. Methods: We analyzed a prospectively collected registry (2011-2014) of patients admitted to the ICU with a diagnosis of sepsis at two academic hospitals. We included all adult patients with an index ED visit within 72 hours of ICU admission. Patients were categorized into 3 groups: 1) Admitted directly to ICU; 2) Admitted to wards, with ICU admission within 72 hours; and 3) Sent home, with ICU admission within 72 hours. ICU length of stay (LOS) and total costs (both direct and indirect) were recorded. The primary outcome, in-hospital mortality, was analyzed using a multivariable logistic regression model, controlling for confounding variables (including patient sex, comorbidities, and illness severity). Results: 657 ICU patients were included. Of these, 338 (51.4%) were admitted directly from ED to ICU, 246 (37.4%) were initially admitted to the wards, and 73 (11.1%) were initially sent home. In-hospital mortality was lowest amongst patients admitted directly to the ICU (29.5%), as compared to patients admitted to ICU from wards (42.7%), or home (61.6%). Delayed ICU admission was associated with increased odds of mortality (adjusted odds ratio 1.85 [1.24-2.76], P<0.01) and increased median ICU LOS (11 days vs. 4 days, P<0.001). Median total costs were lowest among patients directly admitted to the ICU ($19,924, [Interquartile range [IQR], 10,333-32,387]), as compared to those admitted from wards ($72,155 [IQR, $42,771-122,749]) and those initially sent home ($45,121 [IQR, $19,930-86,843]). Conclusion: Only half of ED sepsis patients ultimately requiring ICU admission within 72 hours of ED arrival are directly admitted to the ICU. Delayed ICU admission is associated with higher mortality, LOS, and costs.

scholarly journals In-Hospital Outcomes in Patients Admitted to the Intensive Care Unit after a Return Visit to the Emergency Department

Healthcare ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 431
Author(s):  
Chun-Fu Lin ◽  
Yi-Syun Huang ◽  
Ming-Ta Tsai ◽  
Kuan-Han Wu ◽  
Chien-Fu Lin ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Regression Analysis ◽  
Intensive Care ◽  
Medical Cost ◽  
Total Medical Cost ◽  
Hospital Outcomes ◽  
Return Visit ◽  
Icu Admission ◽  
Ed Visits

Background: Intensive care unit (ICU) admission following a short-term emergency department (ED) revisit has been considered a particularly undesirable outcome among return-visit patients, although their in-hospital prognosis has not been discussed. We aimed to compare clinical outcomes between adult patients admitted to the ICU after unscheduled ED revisits and those admitted during index ED visits. Method: This retrospective study was conducted at two tertiary medical centers in Taiwan from 1 January 2016 to 31 December 2017. All adult non-trauma patients admitted to the ICU directly via the ED during the study period were included and divided into two comparison groups: patients admitted to the ICU during index ED visits and those admitted to the ICU during return ED visits. The outcomes of interest included in-hospital mortality, mechanical ventilation (MV) support, profound shock, hospital length of stay (HLOS), and total medical cost. Results: Altogether, 12,075 patients with a mean (standard deviation) age of 64.6 (15.7) years were included. Among these, 5.3% were admitted to the ICU following a return ED visit within 14 days and 3.1% were admitted following a return ED visit within 7 days. After adjusting for confounding factors for multivariate regression analysis, ICU admission following an ED revisit within 14 days was not associated with an increased mortality rate (adjusted odds ratio (aOR): 1.08, 95% confidence interval (CI): 0.89 to 1.32), MV support (aOR: 1.06, 95% CI: 0.89 to 1.26), profound shock (aOR: 0.99, 95% CI: 0.84 to 1.18), prolonged HLOS (difference: 0.04 days, 95% CI: −1.02 to 1.09), and increased total medical cost (difference: USD 361, 95% CI: −303 to 1025). Similar results were observed after the regression analysis in patients that had a 7-day return visit. Conclusion: ICU admission following a return ED visit was not associated with major in-hospital outcomes including mortality, MV support, shock, increased HLOS, or medical cost. Although ICU admissions following ED revisits are considered serious adverse events, they may not indicate poor prognosis in ED practice.

scholarly journals Respiratory events in ward are associated with later intensive care unit (ICU) admission and hospital mortality in onco-hematology patients not admitted to ICU after a first request

PLoS ONE ◽  
2017 ◽  
Vol 12 (7) ◽  
pp. e0181808 ◽  
Author(s):  
Laure Doukhan ◽  
Magali Bisbal ◽  
Laurent Chow-Chine ◽  
Antoine Sannini ◽  
Jean Paul Brun ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Icu Admission ◽  
Respiratory Events

scholarly journals COVID outcome prediction in the emergency department (COPE): using retrospective Dutch hospital data to develop simple and valid models for predicting mortality and need for intensive care unit admission in patients who present at the emergency department with suspected COVID-19

BMJ Open ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. e051468
Author(s):  
David van Klaveren ◽  
Alexandros Rekkas ◽  
Jelmer Alsma ◽  
Rob J C G Verdonschot ◽  
Dick T J J Koning ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Outcome Prediction ◽  
Characteristic Curve ◽  
Hospital Death ◽  
Hospital Data ◽  
Dutch Hospital ◽  
Icu Admission ◽  
Second Wave

ObjectivesDevelop simple and valid models for predicting mortality and need for intensive care unit (ICU) admission in patients who present at the emergency department (ED) with suspected COVID-19.DesignRetrospective.SettingSecondary care in four large Dutch hospitals.ParticipantsPatients who presented at the ED and were admitted to hospital with suspected COVID-19. We used 5831 first-wave patients who presented between March and August 2020 for model development and 3252 second-wave patients who presented between September and December 2020 for model validation.Outcome measuresWe developed separate logistic regression models for in-hospital death and for need for ICU admission, both within 28 days after hospital admission. Based on prior literature, we considered quickly and objectively obtainable patient characteristics, vital parameters and blood test values as predictors. We assessed model performance by the area under the receiver operating characteristic curve (AUC) and by calibration plots.ResultsOf 5831 first-wave patients, 629 (10.8%) died within 28 days after admission. ICU admission was fully recorded for 2633 first-wave patients in 2 hospitals, with 214 (8.1%) ICU admissions within 28 days. A simple model—COVID outcome prediction in the emergency department (COPE)—with age, respiratory rate, C reactive protein, lactate dehydrogenase, albumin and urea captured most of the ability to predict death. COPE was well calibrated and showed good discrimination for mortality in second-wave patients (AUC in four hospitals: 0.82 (95% CI 0.78 to 0.86); 0.82 (95% CI 0.74 to 0.90); 0.79 (95% CI 0.70 to 0.88); 0.83 (95% CI 0.79 to 0.86)). COPE was also able to identify patients at high risk of needing ICU admission in second-wave patients (AUC in two hospitals: 0.84 (95% CI 0.78 to 0.90); 0.81 (95% CI 0.66 to 0.95)).ConclusionsCOPE is a simple tool that is well able to predict mortality and need for ICU admission in patients who present to the ED with suspected COVID-19 and may help patients and doctors in decision making.

Multicenter outcome study of cancer patients admitted to the intensive care unit: a probability of mortality model.

1998 ◽  
Vol 16 (2) ◽  
pp. 761-770 ◽  
Author(s):  
J S Groeger ◽  
S Lemeshow ◽  
K Price ◽  
D M Nierman ◽  
P White ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Logistic Regression ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Cancer Patients ◽  
The United States ◽  
Categorical Variables ◽  
Allogeneic Bone ◽  
Icu Admission ◽  
Hospital Survival

PURPOSE To develop prospectively and validate a model for probability of hospital survival at admission to the intensive care unit (ICU) of patients with malignancy. PATIENTS AND METHODS This was an inception cohort study in the setting of four ICUs of academic medical centers in the United States. Defined continuous and categorical variables were collected on consecutive patients with cancer admitted to the ICU. A preliminary model was developed from 1,483 patients and then validated on an additional 230 patients. Multiple logistic regression modeling was used to develop the models and subsequently evaluated by goodness-of-fit and receiver operating characteristic (ROC) analysis. The main outcome measure was hospital survival after ICU admission. RESULTS The observed hospital mortality rate was 42%. Continuous variables used in the ICU admission model are PaO2/FiO2 ratio, platelet count, respiratory rate, systolic blood pressure, and days of hospitalization pre-ICU. Categorical entries include presence of intracranial mass effect, allogeneic bone marrow transplantation, recurrent or progressive cancer, albumin less than 2.5 g/dL, bilirubin > or = 2 mg/dL, Glasgow Coma Score less than 6, prothrombin time greater than 15 seconds, blood urea nitrogen (BUN) greater than 50 mg/dL, intubation, performance status before hospitalization, and cardiopulmonary resuscitation (CPR). The P values for the fit of the preliminary and validation models are .939 and .314, respectively, and the areas under the ROC curves are .812 and .802. CONCLUSION We report a disease-specific multivariable logistic regression model to estimate the probability of hospital mortality in a cohort of critically ill cancer patients admitted to the ICU. The model consists of 16 unambiguous and readily available variables. This model should move the discussion regarding appropriate use of ICU resources forward. Additional validation in a community hospital setting is warranted.

scholarly journals NT-ProBNP Predicts Total Mortality, Emergency Department Visits, Hospitalization, Intensive-Care Unit Admission, and Cardiovascular Events in Hemodialysis Patients

2019 ◽  
Vol 8 (2) ◽  
pp. 238
Author(s):  
Yi-Hsin Chen ◽  
Yun-Ching Fu ◽  
Ming-Ju Wu
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Cardiovascular Events ◽  
Predictive Ability ◽  
Hemodialysis Patients ◽  
Emergency Department Visits ◽  
Time Dependent ◽  
Icu Admission ◽  
Ed Visits

N-terminal pro b-type natriuretic peptide (NT-proBNP) was considered a prognostic factor for mortality in hemodialysis patients in previous studies. However, NT-proBNP has not been fully explored in terms of predicting other clinical outcomes in hemodialysis patients. This study aimed to investigate if NT-proBNP could predict emergency department (ED) visits, hospitalization, admission to intensive-care unit (ICU), and cardiovascular incidents in hemodialysis patients. Serum NT-proBNP and other indicators were collected in 232 hemodialysis patients. Patients were followed up for three years or until mortality. Outcomes included mortality, number of ED visits, hospitalizations, admissions to ICU, and cardiovascular events. NT-proBNP was found to predict recurrent ER visits, hospitalization, admission to ICU, cardiovascular events, and mortality, after adjusting for covariates. Time-dependent area under the curve (AUC) was used to evaluate the NT-proBNP predicting ability. Using time-dependent AUC, NT-proBNP has good predictive ability for mortality, ED visit, hospitalization, ICU admission, and cardiovascular events with the best predictive ability occurring at approximately 1 year, and 5th, 62nd, 63rd, and 63rd days respectively. AUC values for predicting mortality, hospitalization, and ICU admission decreased significantly after one year. NT-proBNP can be applied in predicting ED visits but is only suitable for the short-term. NT-proBNP may be used for predicting mortality in the long term.

scholarly journals SAPS 3—From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission

2005 ◽  
Vol 31 (10) ◽  
pp. 1345-1355 ◽  
Author(s):  
Rui P. Moreno ◽  
Philipp G. H. Metnitz ◽  
Eduardo Almeida ◽  
Barbara Jordan ◽  
Peter Bauer ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Prognostic Model ◽  
Saps 3 ◽  
Icu Admission

scholarly journals Factors contributing to delay intensive care unit admission of critically ill patients from the adult emergency Department in Tikur Anbessa Specialized Hospital

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Helen Teklie ◽  
Hywet Engida ◽  
Birhanu Melaku ◽  
Abdata Workina
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Intensive Care Unit Admission ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Transfer Time ◽  
Multivariate Logistic Regression ◽  
Icu Admission ◽  
Specialized Hospital

Abstract Background The transfer time for critically ill patients from the emergency department (ED) to the Intensive care unit (ICU) must be minimal; however, some factors prolong the transfer time, which may delay intensive care treatment and adversely affect the patient’s outcome. Purpose To identify factors affecting intensive care unit admission of critically ill patients from the emergency department. Patients and methods A cross-sectional study design was conducted from January 13 to April 12, 2020, at the emergency department of Tikur Anbesa Specialized Hospital. All critically ill patients who need intensive care unit admission during the study period were included in the study. A pretested structured questionnaire was adapted from similar studies. The data were collected by chart review and observation. Then checked data were entered into Epi-data version 4.1 and cleaned data was exported to SPSS Version 25 for analysis. Descriptive statistics, bivariate and multivariate logistic regression were used to analyze the data. Result From the total of 102 critically ill patients who need ICU admission 84.3% of them had prolonged lengths of ED stay. The median length of ED stay was 13.5 h with an IQR of 7–25.5 h. The most common reasons for delayed ICU admission were shortage of ICU beds 56 (65.1%) and delays in radiological examination results 13(15.1%). On multivariate logistic regression p < 0.05 male gender (AOR = 0.175, 95% CI: (0.044, 0.693)) and shortage of ICU bed (AOR = 0.022, 95% CI: (0.002, 0.201)) were found to have a significant association with delayed intensive care unit admission. Conclusion there was a delay in ICU admission of critically ill patients from the ED. Shortage of ICU bed and delay in radiological investigation results were the reasons for the prolonged ED stay.

scholarly journals Disparities in Intensive Care Unit Admission and Mortality Among Patients With Schizophrenia and COVID-19: A National Cohort Study

2020 ◽  
Author(s):  
Guillaume Fond ◽  
Vanessa Pauly ◽  
Marc Leone ◽  
Pierre-Michel Llorca ◽  
Veronica Orleans ◽  
...  
Keyword(s):  
Health Care ◽  
Intensive Care Unit ◽  
Mental Illness ◽  
Cohort Study ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Severe Mental Illness ◽  
Vulnerable Population ◽  
Icu Admission ◽  
Risk Of Death

Abstract Patients with schizophrenia (SCZ) represent a vulnerable population who have been understudied in COVID-19 research. We aimed to establish whether health outcomes and care differed between patients with SCZ and patients without a diagnosis of severe mental illness. We conducted a population-based cohort study of all patients with identified COVID-19 and respiratory symptoms who were hospitalized in France between February and June 2020. Cases were patients who had a diagnosis of SCZ. Controls were patients who did not have a diagnosis of severe mental illness. The outcomes were in-hospital mortality and intensive care unit (ICU) admission. A total of 50 750 patients were included, of whom 823 were SCZ patients (1.6%). The SCZ patients had an increased in-hospital mortality (25.6% vs 21.7%; adjusted OR 1.30 [95% CI, 1.08–1.56], P = .0093) and a decreased ICU admission rate (23.7% vs 28.4%; adjusted OR, 0.75 [95% CI, 0.62–0.91], P = .0062) compared with controls. Significant interactions between SCZ and age for mortality and ICU admission were observed (P = .0006 and P &lt; .0001). SCZ patients between 65 and 80 years had a significantly higher risk of death than controls of the same age (+7.89%). SCZ patients younger than 55 years had more ICU admissions (+13.93%) and SCZ patients between 65 and 80 years and older than 80 years had less ICU admissions than controls of the same age (−15.44% and −5.93%, respectively). Our findings report the existence of disparities in health and health care between SCZ patients and patients without a diagnosis of severe mental illness. These disparities differed according to the age and clinical profile of SCZ patients, suggesting the importance of personalized COVID-19 clinical management and health care strategies before, during, and after hospitalization for reducing health disparities in this vulnerable population.

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