Time Of Emergency Department Admission Research Articles

Which one predicts mortality better in acute ischemic stroke: negative vs positive acute-phase reactants

ABSTRACT Aim The aim of the study is to investigate the relationship between negative acute-phase reactants and positive acute-phase reactants with in-hospital mortality in patients diagnosed with acute ischemic stroke (AIS) in the emergency department (ED). Methods and Materials Patients aged 18 and older who presented to the ED of a tertiary hospital with AIS were included in the study. Demographic and clinical characteristics, laboratory parameters, acute-phase reactants, National Institutes of Health Stroke Scale (NIHSS), and outcome data of the included patients were recorded on a standard data form. Results A total of 588 patients were included in the study. When the in-hospital mortality of patients was examined, the mortality rate was 17.7%. In the analysis for predicting mortality, it was determined that albumin had the highest predictive power between the area under the curve (AUC) and the determined predictive values (AUC: 0.759, 95% CI 0.707–0.810, p < 0.001). The analyses of the study data revealed that albumin (<0.001) and TF (p = 0.049), which are negative acute-phase reactants, were independent predictors of mortality. According to our study data, in patients with AIS, for each unit decrease in albumin level at the time of ED admission, the risk of mortality increased by 0.868 times, and for each unit decrease in TF level, the risk of mortality increased by 0.593 times. Conclusion According to the study data, albumin and TF levels, which are negative acute-phase reactants, are independent determinants of in-hospital mortality in patients with acute ischemic stroke in the emergency department.

Application of the National Early Warning Score in patients with suspected COVID‐19 in Korea

AbstractBackgroundCoronavirus disease 2019 (COVID‐19) infection has a wide range of severity, ranging from asymptomatic infection to severe respiratory distress and multiple organ dysfunction. To optimize the utilization of limited resources, a system is needed to rapidly classify the patients requiring monitoring and urgent intervention. The purpose of this study was to determine whether the National Early Warning Score (NEWS) at admission is a useful prediction tool for in‐hospital mortality in patients who visited the emergency department (ED) and required isolation during the COVID‐19 pandemic.MethodsThis study was conducted in adults aged 19 years or older who visited the ED and were preemptively isolated due to fever or respiratory symptoms from January 2021 to December 2021. The NEWS was calculated at the time of ED admission. The primary outcome was all‐cause in‐hospital mortality.ResultsOf the 6304 patients included in the study, 5759 survived and 545 died in the hospital. The NEWS was higher in non‐survivors (6.1 ± 4.2) than in survivors (2.8 ± 2.5). When the NEWS was examined as a continuous variable, the adjusted odds ratio for in‐hospital mortality was 1.176 (95% CI, 1.12–1.23). The area under the curve (AUC) of NEWS for predicting in‐hospital mortality was 0.756 (95% CI, 0.734–0.778).ConclusionsThe NEWS at ED admission was associated with in‐hospital mortality in preemptively isolated patients during the COVID‐19 pandemic. The use of NEWS in patients with suspected COVID‐19 infection would help predict the severity and prognosis of patients.

Can We Predict Length of Stay for CJR Patients Who Sustain a Displaced Femoral Neck Fracture?

AbstractThe Comprehensive Care for Joint Replacement (CJR) model holds hospitals financially accountable for the outcomes of patients undergoing hip and knee replacements. The purpose of this study is to see if a validated inpatient risk assessment tool can be used to predict patients with poor outcomes following hip arthroplasty. We hypothesize that the validated risk prediction tool (Score for Trauma Triage in the Geriatric and Middle-Aged [STTGMA]) can be modeled to stratify these patients at highest risk for poor outcomes at emergency department (ED) presentation. Between October 2018 and September 2020, 237 patients subject to the CJR bundle program were treated for a displaced femoral neck fracture with total hip arthroplasty or hemiarthroplasty and analyzed for demographics, comorbidities, injury details, and outcomes. A poor outcome was considered to be a longer length of inpatient hospital stay, venous thromboembolism (VTE), or readmission within 30, 60, or 90 days. Each patient's STTGMA score was calculated using their demographics, functional status, and injury details at time of ED admission. Patients were divided into risk quartiles based on STTGMA score. The top 25% risk cohort was compared against the bottom 25% risk cohort using chi-square or t-tests as appropriate. Mean STGGMA scores were 0.046 ± 0.028 in the highest risk cohort and 0.007 ± 0.001 in the lowest risk cohort. STTGMA was able to adequately risk stratify patients at risk for a longer length of inpatient hospital stay (p &lt; 0.01). The STTGMA tool was unable to risk stratify patients with postoperative VTE within 90 days (p = 0.986) or readmission within 90 days (p = 0.087). Providers can calculate STTGMA scores on admission for CJR patients to help identify which patients may require a longer length of inpatient hospital stay. These patients can be targeted with strategies to address these deficiencies.

Inpatient boarding definitions and mitigation strategies: A cross-sectional survey of academic emergency departments in the United States

ObjectiveConceptually, inpatient boarding is a result in the delay of admitting patients from the Emergency Department (ED) to inpatient units, but there is no consistent definition across academic EDs. The purpose of this study was to evaluate the definition of boarding across academic EDs, and to identify mitigation strategies used by EDs to alleviate crowd management. MethodsThis was a cross-sectional survey of boarding-related questions (i.e., boarding definitions and practices) that were embedded into the annual benchmarking survey conducted by the Academy of Academic Administrators of Emergency Medicine and the Association of Academic Chairs of Emergency Medicine. Results were descriptively assessed and tabulated. ResultsOf the 130 eligible institutions, 68 participated in the survey. Approximately 70% of institutions reported starting the boarding clock at the time of ED admission, while 19% reported that the clock started with the completion of inpatient orders. Approximately 35% of institutions considered patients boarded within 2 h, while 34% considered patients boarded >4 h after admission decision. In response to ED overcrowding brought on by inpatient boarding, 35% reported using hallway beds for patient care. Surge capacity measures reported included having a high census/surge capacity plan (81%), going on ambulance diversion (54%), and institutional use of a discharge lounge (49%). ConclusionsWe found that definitions for boarding varied widely. Inpatient boarding has serious consequences to patient care and well-being, suggesting the need for standardized definitions to describe inpatient boarding.

The effectiveness of shock indices on prognosis in burn patients admitted to the emergency department.

Shock index (SI) is the ratio of heart rate (HR) to systolic blood pressure (SBP); modified SI (MSI) is the ratio of HR to mean arterial pressure; age SI (ASI) is age multiplied by SI; reverse SI (rSI) is the ratio of SBP to HR; and rSIG is rSI multiplied by Glasgow Coma Scale Score (rSIG). Studies have proven that shock indices are good tools in predicting mortality. This study aimed to evaluate the sensitivity of the shock indices SI, MSI, ASI, rSI, and rSIG in predicting mortality in burn patients. This is a retrospective cross-sectional study. The vital signs of the patients were recorded and their shock indices were calculated at the time of emergency department admission. The effectiveness of the shock indices SI, MSI, ASI, rSI, and rSIG in predict-ing mortality was compared in the burn patients included in the study RESULTS: A total of 913 patients were enrolled. rSIG and MSI were the shock indices with the highest area under the curve (AUC) values in predicting mortality in the burn patients. The AUC values of rSIG and MSI were 0.829 (95% CI: 0.739-0.919, P<0.001) and 0.740 (95% CI: 0.643-0.838, P<0.001), respectively. Vital signs are easily recorded and shock indices are easily calculated at the time of admission of burn patients to the emergency department; they also effectively predict mortality. rSIG and MSI are the best mortality predictors among the shock indices examined in this study.

Early Prediction Model of Acute Aortic Syndrome Mortality in Emergency Departments.

PurposeAcute aortic syndrome is a constellation of life-threatening medical conditions for which rapid assessment and targeted intervention are important for the prognosis of patients who are at high risk of in-hospital death. The current study aims to develop and externally validate an early prediction mortality model that can be used to identify high-risk patients with acute aortic syndrome in the emergency department.Patients and MethodsThis retrospective multi-center observational study enrolled 1088 patients with acute aortic syndrome admitted to the emergency departments of two hospitals in China between January 2017 and March 2021 for model development. A total of 210 patients with acute aortic syndrome admitted to the emergency departments of Peking University Third Hospital between January 2007 and December 2021 was enrolled for model validation. Demographics and clinical factors were collected at the time of emergency department admission. The predictive variables were determined by referring to the results of previous studies and the baseline analysis of this study. The study’s endpoint was in-hospital death. To assess internal validity, we used a fivefold cross-validation method. Model performance was validated internally and externally by evaluating model discrimination using the area under the receiver-operating characteristic curve (AUC). A nomogram was developed based on the binary regression results.ResultsIn the development cohort, 1088 patients with acute aortic syndromes were included, and 88 (8.1%) patients died during hospitalization. In the validation cohort, 210 patients were included, and 20 (9.5%) patients died during hospitalization. The final model included the following variables: digestive system symptoms (OR=2.25; P=0.024), any pulse deficit (OR=7.78; P<0.001), creatinine (µmol/L)(OR=1.00; P=0.018), lesion extension to iliac vessels (OR=4.49; P<0.001), pericardial effusion (OR=2.67; P=0.008), and Stanford type A (OR=10.46; P<0.001). The model’s AUC was 0.838 (95% CI 0.784–0.892) in the development cohort and 0.821 (95% CI 0.750–0.891) in the validation cohort, and the Hosmer–Lemeshow test showed p=0.597. The fivefold cross-validation demonstrated a mean accuracy of 0.94, a mean precision of 0.67, and a mean recall of 0.13.ConclusionThis risk prediction tool uses simple variables to provide robust prediction of the risk of in-hospital death from acute aortic syndrome and validated well in an independent cohort. The tool can help emergency clinicians quickly identify high-risk acute aortic syndrome patients, although further studies are needed for verifying the prospective data and the results of our study.

Relationship between time of emergency department admission and adherence to the Surviving Sepsis Campaign bundle in patients with septic shock

BackgroundNighttime hospital admission is often associated with increased mortality risk in various diseases. This study investigated compliance rates with the Surviving Sepsis Campaign (SSC) 3-h bundle for daytime and nighttime emergency department (ED) admissions and the clinical impact of compliance on mortality in patients with septic shock.MethodsWe conducted an observational study using data from a prospective, multicenter registry for septic shock provided by the Korean Shock Society from 11 institutions from November 2015 to December 2017. The outcome was the compliance rate with the SSC 3-h bundle according to the time of arrival in the ED.ResultsA total of 2049 patients were enrolled. Compared with daytime admission, nighttime admission was associated with higher compliance with the administration of antibiotics within 3 h (adjusted odds ratio (adjOR), 1.326; 95% confidence interval (95% CI), 1.088–1.617, p = 0.005) and with the complete SSC bundle (adjOR, 1.368; 95% CI, 1.115–1.678; p = 0.003), likely to result from the increased volume of all patients and sepsis patients admitted during daytime hours. The hazard ratios of the completion of SSC bundle for 28-day mortality and in-hospital mortality were 0.750 (95% CI 0.590–0.952, p = 0.018) and 0.714 (95% CI 0.564–0.904, p = 0.005), respectively.ConclusionSeptic shock patients admitted to the ED during the daytime exhibited lower sepsis bundle compliance than those admitted at night. Both the higher number of admitted patients and the higher patients to medical staff ratio during daytime may be factors that are responsible for lowering the compliance.

Use of the National Early Warning Score for predicting in-hospital mortality in older adults admitted to the emergency department.

ObjectiveThe National Early Warning Score (NEWS), based on the patients’ vital signs, detects clinical deterioration in critically ill patients and is used to reduce the incidence of in-hospital cardiac arrest. However, although mortality prediction based on vital signs may be difficult in older patients, the effectiveness of the NEWS has not yet been evaluated in this population. This study aimed to test the hypothesis that an elevated NEWS at admission increases the mortality risk in older patients admitted to the emergency department (ED).MethodsWe conducted a single-center retrospective study, including patients admitted to the ED between November 2016 and February 2017. We included patients aged >65 years who were admitted to the ED for any medical problem. The NEWS was calculated at the time of ED admission. The primary outcome was in-hospital mortality.ResultsIn total, 3,169 patients were included in this study. Median age was 75 years (interquartile range [IQR], 70 to 80 years), and 1,557 (49.1%) patients were male. The in-hospital mortality rate was 5.1% (161 patients). Median NEWS was higher in non-survivors than in survivors (5 [IQR, 3–8] vs. 1 [IQR, 0–3], P<0.001). Multivariate logistic analysis showed that the NEWS was associated with in-hospital mortality, after adjusting for other confounders. The area under the curve of the NEWS for predicting in-hospital mortality was 0.820 (95% confidence interval, 0.806 to 0.833).ConclusionOur results show that the NEWS at admission is associated with in-hospital mortality among patients aged >65 years.

288 Predicting Potential Bouncebacks to the Emergency Department: A Machine Learning Approach

Review of patients who return to the emergency department (ED) within 72 hours (ie, bounceback) is a common quality assurance process. Current practice of studying bouncebacks, which relies on manual chart extraction and review, is labor-intensive and limited. In this study, we leverage machine learning methods to automatically extract features from electronic health record (EHR) data, learn patterns among patients who “bounceback,” and develop an EHR-driven risk prediction model. This is a retrospective analysis of EHR data and provider notes of all adult patients who presented to a single-center, urban emergency department (ED) over 4.25 years (1/1/2015—4/1/2019). Two different deep learning approaches have been employed to analyze a combination of structured variables (demographics and vital signs at the time of ED admission) as well as unstructured EHR free text (ED provider notes) to predict patients’ risk of bounceback. Both approaches involved training word embeddings using the EHR free text notes. In the first approach each EHR note was converted to a sequence of word embedding vectors and the sequence was used to train a stacked Long Short-Term Memory Recurrent Neural Network (LSTM-RNN), whereas in the second approach each EHR note was abstracted to a single embedding vector using a Doc2Vec algorithm and it was passed through a fully connected (dense) deep network architecture. The resultant vector in each approach was then concatenated to a vector of structured predictors and passed through multiple fully connected network layers to predict the outcome. The accuracy of predicting the bounceback target variable is characterized by sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC). Of the adult patients (n = 330,407) who presented to the ED during this time period, 4.7% (n = 15,529) subsequently returned within 72 hours. The LSTM model produced a sensitivity and specificity of 66.3% and 59%, respectively (AUROC = 0.686). The sensitivity and specificity improved with the Doc2Vec approach, to 67.9% and 66.8%, respectively. The resulting AUROC was found to be 0.755, indicating the higher distinctive power of the second approach. In this retrospective analysis of EHR data, deep learning models demonstrated promising results as a proof of concept for uncovering predictive local motifs in the ED provider note texts among patients who return within 72 hours. Once fully developed and deployed, these predictive models could aid clinical quality review of bouncebacks in the ED and serve as adjuncts to clinical decision support.

Prognostic accuracy of the sequential organ failure assessment (SOFA) and quick SOFA for mortality in cancer patients with sepsis defined by systemic inflammatory response syndrome (SIRS).

We aimed to assess the prognostic accuracy of SOFA and qSOFA scores in cancer patients with sepsis, and also to determine if the addition of hyperlactatemia to qSOFA increases the accuracy in predicting the 30-day mortality. We consecutively included adult active cancer patients (age ≥ 18years) with sepsis defined by SIRS who visited the emergency department (ED) from May 1st to July 30th, 2017. Data were collected retrospectively through reviewing medical records. The SOFA and qSOFA scores were calculated with the initial variables at the time of ED admission. The primary endpoint was 30-day mortality. Of 1137 screened, 301 were included. The 30-day mortality was 14.3% (43 patients). Among the total 301, the SOFA score was ≥ 2 in 168 and qSOFA ≥ 2 in 23. For those with SOFA ≥ 2 and < 2, the mortality was 23.2% and 3%, respectively (P < 0.001). For those with qSOFA ≥ 2 and < 2, the mortality was 47.8% and 11.5%, respectively (P < 0.001). The AUROC of 30-day mortality for qSOFA was lower than that for SOFA (0.66 (95% CI, 0.56-0.75) vs. 0.79 (95% CI, 0.72-0.87), P = 0.004)). However, the combination of qSOFA with lactate ≥ 2 threshold considerably enhanced a discrimination capacity for mortality with an AUROC 0.77 (95% CI, 0.69-0.85), which was similar to SOFA (P = 0.11). In cancer patients with sepsis, qSOFA was inferior to SOFA in predicting mortality. However, adding lactate to qSOFA resulted in greater prognostic accuracy for short-term mortality, comparable with SOFA.

Mortality and associated risk factors for older adults admitted to the emergency department: a hospital cohort

BackgroundOlder emergency department patients are more vulnerable than younger patients, yet many risk factors that contribute to the mortality of older patients remain unclear and under investigation. This study endeavored to determine mortality and factors associated with mortality in patients over 60 years of age who were admitted to the emergency departments of two general hospitals in Mexico City.MethodsThis is a hospital cohort study involving adults over 60 years of age admitted to the emergency department and who are beneficiaries of the Mexican Institute of Social Security and residents of Mexico City.All causes of mortality from the time of emergency department admission until a follow-up home visit after discharge were measured. Included risk factors were: socio-demographic, health-care related, mental and physical variables, and in-hospital care-related. Survival functions were estimated using Kaplan-Meier curves. Hazard ratios (HR) were derived from Cox regression models in a multivariate analysis.ResultsFrom the 1406 older adults who participated in this study, 306 (21.8%) did not survive. Independent mortality risk factors found in the last Cox model were age (HR = 1.02, 95% CI, 1.005–1.04; p = 0.01), length of stay in the ED (HR = 1.003, 95% CI = 0.99, 1.04; p = 0.006), geriatric care trained residents model in Hospital A (protective factor) (HR = 0.66, 95% CI = 0.46, 0.96; p = 0.031), and the FRAIL scale (HR of 1.34 95% CI, 1.02–1.76; p = 0.033).ConclusionsRisk factors for mortality in patients treated at Mexican emergency departments are length of stay and variables related to frailty status.

Levels of serum uric acid at admission for hypoglycaemia predict 1-year mortality.

Hypoglycaemia represents a critical burden with clinical and social consequences in the management of diabetes. Serum uric acid (SUA) has been associated with cardiovascular diseases (CVD), but no conclusive findings are available nowadays in patients suffering from hypoglycaemia. We investigated whether SUA levels at the time of hypoglycaemia could predict all-cause mortality after 1-year follow-up. In total, 219 patients admitted to the Emergency Department (ED) of Ospedale Policlinico S. Martino of Genoa (Italy) have been enrolled between January 2011 and December 2014. The primary endpoint of the study consisted in determining whether SUA levels at the time of ED admission could predict the occurrence of death after 1year. The majority of patients were diabetic, especially type 2. CVD and chronic kidney disease were prevalent comorbidities. By a cut-off value obtained by the receiver operating characteristic curve analysis, a Kaplan-Meier analysis demonstrated that patients with SUA levels>5.43mg/dL were more prone to death after 1year compared to those with lower SUA levels. The risk of death increased with high SUA levels both in the univariate and the multivariate models including estimated glomerular filtration rate, C-reactive protein, type of diabetes, and age-adjusted Charlson comorbidity index. SUA could be useful as a predictor of 1-year mortality in hypoglycaemic patients, irrespective of severe comorbidities notably increasing the risk of death in these frail patients.

Gut, microbiota-dependent trimethylamine-N-oxide is associated with long-term all-cause mortality in patients with exacerbated chronic obstructive pulmonary disease.

The gut, microflora-dependent metabolite trimethylamine-N-oxide (TMAO) has emerged as a dietary-associated risk factor for incident cardiovascular events. Chronic obstructive pulmonary disease (COPD) is a prevalent disease worldwide with a high associated risk for cardiovascular disease and death due to an infectious cause. To study whether TMAO is predictive for adverse clinical outcomes in patients with exacerbated COPD. A total of 189 patients with COPD exacerbation were prospectively followed for a median of 6.1y. TMAO plasma levels at the time of emergency department admission were measured by liquid chromatography coupled with tandem mass spectrometry. Cox and linear regression models were used to investigate associations of TMAO with all-cause mortality and different comorbidities. All-cause mortality was 55.6% after 6y. The deceased patients showed significantly higher median admission TMAO (μmol/L) levels compared with survivors (3.9 [interquartile range: 2.3-7.1] versus 2.9 [interquartile range: 1.8-4.7]; P=0.01), which resulted in an unadjusted hazard ratio of 1.8 ([95% confidence interval: 1.2-3.0], P=0.01). This association was no longer significant after multivariate adjustment. Median TMAO levels were similar in nonpneumonic and pneumonic COPD exacerbation. Higher age, higher body mass index, diabetes mellitus, and chronic kidney disease were predictors for increased plasma TMAO levels in linear regression analysis. Increased circulating TMAO levels per se were associated with long-term all-cause mortality in patients with COPD independent of type of exacerbation. However, this association was largely explained by comorbidities and age. Whether TMAO levels can additionally be influenced by nutritional interventions should be addressed in future studies.

Screening for hereditary angioedema (HAE) at 13 emergency centers in Osaka, Japan: A prospective observational study.

Hereditary angioedema (HAE) with deficiency of C1 inhibitor (C1-INH) is an autosomal-dominant disease characterized by recurrent episodes of potentially life-threatening angioedema. The objective is to study the incidence of HAE among patients who visit the emergency department.This was a 3-year prospective observational screening study involving 13 urban tertiary emergency centers in Osaka prefecture, Japan. Patients were included if they met the following criteria: unexplained edema of the body, upper airway obstruction accompanied by edema, anaphylaxis, acute abdomen with intestinal edema (including ileus and acute pancreatitis), or asthma attack. C1-INH activity and C4 level were measured at the time of emergency department admission during the period between July 2011 and June 2014.This study comprised 66 patients with a median age of 54.0 (IQR: 37.5-68.3) years. Three patients were newly diagnosed as having HAE, and 1 patient had already been diagnosed as having HAE. C1-INH activity levels of the patients with HAE were below the detection limit (<25%), whereas those of non-HAE patients (n = 62) were 106% (IQR: 85.5%-127.0%) (normal range, 70%-130%). The median level of C4 was significantly lower in the patients with HAE compared with those without HAE (1.2 [IQR: 1-3] mg/dL vs 22 [IQR: 16.5-29.5] mg/dL, P < 0.01) (normal range, 17-45 mg/dL).Three patients with undiagnosed HAE were diagnosed as having HAE in the emergency department during the 3-year period. If patients have signs and symptoms suspicious of HAE, the levels of C1-INH activity and C4 should be measured.

Evaluation of intoxicated patients hospitalized in a newly-opened level two pediatric intensive care unit.

The study aimed to retrospectively examine the demographic and etiological characteristics, prognosis and length of stay in intensive care unit of intoxicated patients hospitalized in Level two Pediatric Intensive Care Unit in Maternity and Child Health Hospital of Samsun. The study retrospectively examined the records of patients hospitalized between 14(th) March 2014 and 14(th) March 2015 in Level two Pediatric Intensive Care Unit in Maternity and Child Health Hospital of Samsun with respect to age, gender, cause of poisoning, time of emergency department admission, length of hospitalization and prognosis. Of 82 patients admitted to the Intensive Care Unit, 29 (35.3%) were male and 53 (64.6%) were female. The mean age of the male and female patients was 7.89±6.3 years and 11.2±5.7 years, respectively and the mean age of the study group was 10.04±6.1. Twenthy one (39,6%) of the female patients were at the age group of 0-14 years and 32 (60.4%) were at the age group of 14-18 years. Twenthy (68.9%) of the male patients were at the age group of 0-14 years and nine (31.1%) were at the age group of 14-18 years. The cause of poisoning was drug intoxication (antidepressants, antibiotics, painkillers and other drugs) in 64 patients (78%) and the remaining 18 patients (22%) were admitted to hospital for other causes (rat poison, mushroom, carbonmonoxide, scorpion stings, bonzai and pesticides). Thirthy eight (46.3%) of all the patients used such substances for suicidal purpose. Thirthy three (62.2%) of these were female and 32 were at the age group of 14-18 years. Fourty (48.7%) of the patients who ingested medication ingested one drug, while 24 (29.2%) ingested multiple drugs. Antidepressants were found to be the most commonly used drugs (31.2%). The mean hospital admission time was 3.41±2 hours and the mean time of intensive care unit stay was 2.89±1.04 days. No mortality was recorded. Thirthy patients (36.5%) were referred to the Pediatric Psychiatric Unit as outpatients after discharge and three patients (3.6%) were referred to Alcohol and Substance Abuse Treatment and Research Centre. Because the rate of drug intoxication was found to be substantially high in this study, we think that politics related with education of parents on this issue, packaging of drugs in such a way that children can not open these packages and drug supply should be reviewed.

Hypoalbuminemia, Low Base Excess Values, and Tachypnea Predict 28-Day Mortality in Severe Sepsis and Septic Shock Patients in the Emergency Department.

PurposeThe objective of this study was to develop a new nomogram that can predict 28-day mortality in severe sepsis and/or septic shock patients using a combination of several biomarkers that are inexpensive and readily available in most emergency departments, with and without scoring systems.Materials and MethodsWe enrolled 561 patients who were admitted to an emergency department (ED) and received early goal-directed therapy for severe sepsis or septic shock. We collected demographic data, initial vital signs, and laboratory data sampled at the time of ED admission. Patients were randomly assigned to a training set or validation set. For the training set, we generated models using independent variables associated with 28-day mortality by multivariate analysis, and developed a new nomogram for the prediction of 28-day mortality. Thereafter, the diagnostic accuracy of the nomogram was tested using the validation set.ResultsThe prediction model that included albumin, base excess, and respiratory rate demonstrated the largest area under the receiver operating characteristic curve (AUC) value of 0.8173 [95% confidence interval (CI), 0.7605–0.8741]. The logistic analysis revealed that a conventional scoring system was not associated with 28-day mortality. In the validation set, the discrimination of a newly developed nomogram was also good, with an AUC value of 0.7537 (95% CI, 0.6563–0.8512).ConclusionOur new nomogram is valuable in predicting the 28-day mortality of patients with severe sepsis and/or septic shock in the emergency department. Moreover, our readily available nomogram is superior to conventional scoring systems in predicting mortality.

Prognostic value of serum pregnancy-associated plasma protein A level at the initial ED presentation in elderly patients with CAP

ObjectiveThis study aims to compare serum pregnancy-associated plasma protein A (PAPP-A) levels in surviving and nonsurviving elderly patients with community-acquired pneumonia (CAP), investigating whether PAPP-A is correlated with CAP prediction scores and whether PAPP-A can successfully predict 28-day mortality rates in elderly patients. MethodsThis prospective, observational, single-center, cross-sectional study was conducted at the emergency department (ED) of Celal Bayar University Hospital in Manisa, Turkey, between January and September 2014. All patients underwent follow-up evaluations 28 days after admission. The end point was defined as all-cause mortality. ResultsA total of 100 elderly patients (mean age, 77.3 ± 7.6 years [range, 65-94 years]); 60% men) with CAP were enrolled in this study. All-cause mortality at the 28-day follow-up evaluation was 22%. Admission PAPP-A levels were significantly higher in nonsurvivors compared with 28-day survivors (10.3 ± 4.5 vs 3.8 ± 2.6 ng/mL, P < .001). A significant and positive correlation between admission PAPP-A levels and pneumonia severity index; confusion, oxygen saturation, respiratory rate, blood pressure, and age 75 years or older; and confusion, urea, respiratory rate, blood pressure, and age older than 65 years scores was found (r = .440, P < .001; r = .395, P < .001; and r = .359, P < .001, respectively). Moreover, we determined that the optimal PAPP-A cutoff for predicting 28-day mortality at the time of ED admission was 5.1 ng/mL, with 77.3% sensitivity and 77.9% specificity. ConclusionsSerum PAPP-A level is valuable for predicting mortality and the severity of the disease among elderly patients with CAP at ED admission. Thus, PAPP-A might play a further role in the clinical assessment of the severity of CAP.

A clinical prediction model to identify patients at high risk of death in the emergency department.

PurposeRapid assessment and intervention is important for the prognosis of acutely ill patients admitted to the emergency department (ED). The aim of this study was to prospectively develop and validate a model predicting the risk of in-hospital death based on all available information available at the time of ED admission and to compare its discriminative performance with a non-systematic risk estimate by the triaging first health-care provider.MethodsProspective cohort analysis based on a multivariable logistic regression for the probability of death.ResultsA total of 8,607 consecutive admissions of 7,680 patients admitted to the ED of a tertiary care hospital were analysed. Most frequent APACHE II diagnostic categories at the time of admission were neurological (2,052, 24 %), trauma (1,522, 18 %), infection categories [1,328, 15 %; including sepsis (357, 4.1 %), severe sepsis (249, 2.9 %), septic shock (27, 0.3 %)], cardiovascular (1,022, 12 %), gastrointestinal (848, 10 %) and respiratory (449, 5 %). The predictors of the final model were age, prolonged capillary refill time, blood pressure, mechanical ventilation, oxygen saturation index, Glasgow coma score and APACHE II diagnostic category. The model showed good discriminative ability, with an area under the receiver operating characteristic curve of 0.92 and good internal validity. The model performed significantly better than non-systematic triaging of the patient.ConclusionsThe use of the prediction model can facilitate the identification of ED patients with higher mortality risk. The model performs better than a non-systematic assessment and may facilitate more rapid identification and commencement of treatment of patients at risk of an unfavourable outcome.Electronic supplementary materialThe online version of this article (doi:10.1007/s00134-015-3737-x) contains supplementary material, which is available to authorized users.

Combination of mean platelet volume and the CURB-65 score better predicts 28-day mortality in patients with community-acquired pneumonia

ObjectiveThis study aims to investigate whether mean platelet volume (MPV) is correlated with the CURB-65 (Confusion, Urea, Respiratory rate, Blood pressure, >65 years of age) score, and whether a combination of the CURB-65 score with MPV could better predict the 28-day mortality in patients with community-acquired pneumonia (CAP). MethodsThis prospective, observational, single-center, and cross-sectional study was conducted at emergency department (ED) between September 1, 2013, and July 31, 2014. All patients underwent follow-up evaluations 28 days after admission. The end point was defined as all-cause mortality. ResultsA total of 174 patients (mean age, 66.7 ± 15.8 years; 66.1% men) with CAP were enrolled in this study. All-cause mortality at the 28-day follow-up evaluation was 16.1%. A significant and inverse correlation between MPV and CURB-65 score was found (R = −.58, P < .001). We determined that the optimal MPV cutoff for predicting 28-day mortality at the time of ED admission was 8.55 fL, with a 75.0% sensitivity and a 75.3% specificity. For the prediction of 28-day mortality, the area under the receiver operating characteristic curve was 0.819 (95% confidence interval [CI], 0.740-0.898; P < .001) when the CURB-65 score was used alone, whereas it increased to 0.895 (95% CI, 0.819-0.936; P < .001) with the addition of MPV to the score. ConclusionsMean platelet volume level is valuable for predicting mortality and the severity of disease among patients with CAP at ED admission. Furthermore, a combination of CURB-65 score and MPV can enhance the predictive accuracy of 28-day mortality.

Decreased levels of alpha-1-acid glycoprotein are related to the mortality of septic patients in the emergency department

OBJECTIVE:To determine the validity of alpha-1-acid glycoprotein as a novel biomarker for mortality in patients with severe sepsis.METHODS:We prospectively included patients with severe sepsis or septic shock at the emergency department at a single tertiary referral teaching hospital. All of the patients were enrolled within the first 24 hours of emergency department admission, and clinical data and blood samples were obtained. As the primary outcome, we investigated the association of serum levels of alpha-1-acid glycoprotein and 96-hour mortality with logistic regression analysis and generalized estimating equations adjusted for age, sex, shock status and Acute Physiology and Chronic Health Evaluation II score.RESULTS:Patients with septic shock had lower alpha-1-acid glycoprotein levels at the time of emergency department admission compared to patients without shock (respectively, 149.1±42.7 vs. 189.8±68.6; p = 0.005). Similarly, non-survivors in the first 96 hours were also characterized by lower levels of alpha-1-acid glycoprotein at the time of emergency department admission compared to survivors (respectively, 132.18±50.2 vs. 179.8±61.4; p = 0.01). In an adjusted analysis, alpha-1-acid glycoprotein levels ≤120 mg/dL were significantly associated with 96-hour mortality (odds ratio = 14.37; 95% confidence interval = 1.58 to 130.21).CONCLUSION:Septic shock patients exhibited lower circulating alpha-1-acid glycoprotein levels than patients without shock. Alpha-1-acid glycoprotein levels were independently associated with 96-hour mortality in individuals with severe sepsis.