Rapid Emergency Medicine Score Can Predict Long-term Mortality in Nonsurgical Emergency Department Patients

OBJECTIVES: To examine the Rapid Emergency Medicine Score (REMS) as a predictor of long-term (4.7 years) mortality in the nonsurgical emergency department (ED). METHODS: This was a prospective cohort study. A total of 12,006 nonsurgical patients consecutively presenting to an adult ED at a 1,200-bed university hospital during a period of one year were enrolled. REMS (including blood pressure, respiratory rate, pulse rate, Glasgow Coma Scale score, peripheral oxygen saturation, and patient age) was calculated for all patients admitted to the ED. The statistical associations between REMS and long-term mortality were examined. RESULTS: REMS could predict mortality over 4.7 years (hazard ratio, 1.26; p < 0.0001). Similar results were obtained in the major patient groups (chest pain, stroke, coma, dyspnea, and diabetes). CONCLUSIONS: REMS was a powerful predictor of long-term mortality in patients attending the ED for a wide range of common nonsurgical disorders.     

Critical Care in the Emergency Department A Physiologic Assessment and Outcome Evaluation

OBJECTIVES: The changing landscape of health care in this country has seen an increase in the delivery of care to critically ill patients in the emergency department (ED). However, methodologies to assess care and outcomes similar to those used in the intensive care unit (ICU) are currently lacking in this setting. This study examined the impact of ED intervention on morbidity and mortality using the Acute Physiology and Chronic Health Evaluation (APACHE II), the Simplified Acute Physiology Score (SAPS II), and the Multiple Organ Dysfunction Score (MODS). METHODS: This was a prospective, observational cohort study over a three-month period. Critically ill adult patients presenting to a large urban ED and requiring ICU admission were enrolled. APACHE II, SAPS II, and MODS scores and predicted mortality were obtained at ED admission, ED discharge, and 24, 48, and 72 hours in the ICU. In-hospital mortality was recorded. RESULTS: Eighty-one patients aged 64 +/- 18 years were enrolled during the study period, with a 30.9% in-hospital mortality. The ED length of stay was 5.9 +/- 2.7 hours and the hospital length of stay was 12.2 +/- 16.6 days. Nine (11.1%) patients initially accepted for ICU admission were later admitted to the general ward after ED intervention. Septic shock was the predominant admitting diagnosis. At ED admission, there was a significantly higher APACHE II score in nonsurvivors (23.0 +/- 6.0) vs survivors (19.8 +/- 6.5, p = 0.04), while there was no significant difference in SAPS II or MODS scores. The APACHE II, SAPS II, and MODS scores were significantly lower in survivors than nonsurvivors throughout the hospital stay (p 相似文献   

Prediction of mortality among emergency medical admissions

Background

The Rapid Acute Physiology Score (RAPS) and Rapid Emergency Medicine Score (REMS) are risk adjustment methods for emergency medical admissions developed for use in audit, research, and clinical practice. Each predicts in hospital mortality using four (RAPS) or six (REMS) variables that can be easily recorded at presentation. We aimed to evaluate the predictive value of REMS, RAPS, and their constituent variables.

Methods

Age, heart rate, respiratory rate, blood pressure, Glasgow Coma Score (GCS) and oxygen saturation were recorded for 5583 patients who were transported by emergency ambulance, admitted to hospital and then followed up to determine in hospital mortality. The discriminant power of each variable, RAPS, and REMS were compared using the area under the receiver operator characteristic curve (AROCC). Multivariate analysis was used to identify which variables were independent predictors of mortality.

Results

REMS (AROCC 0.74; 95% CI 0.70 to 0.78) was superior to RAPS (AROCC 0.64; 95% CI 0.59 to 0.69) as a predictor of in hospital mortality. Although all the variables, except blood pressure, were associated with mortality, multivariate analysis showed that only age (odds ratio 1.74, p<0.001), GCS (2.10, p<0.001), and oxygen saturation (OR 1.36, p = 0.01) were independent predictors. A combination of age, oxygen saturation, and GCS (AROCC 0.80, 95% CI 0.77 to 0.83) was superior to REMS in our population.

Conclusion

REMS is a better predictor of mortality in emergency medical admissions than RAPS. Age, GCS, and oxygen saturation appear to be the most useful predictor variables. Inclusion of other variables in risk adjustment scores, particularly blood pressure, may reduce their value.     

Emergency Department Triage Early Warning Score (TREWS) predicts in-hospital mortality in the emergency department

AimThe purpose is to assess the adequacy of the National Early Warning Score (NEWS) in the emergency department (ED) and the usefulness of the Triage in Emergency Department Early Warning Score (TREWS) that has been developed using the NEWS in the ED.MethodsIn this retrospective observational cohort study, we performed univariable and multivariable regression analyses with 81,520 consecutive ED patients to develop a new scoring system, the TREWS. The primary outcome was in-hospital mortality within 24 h, and secondary outcomes were in-hospital mortality within 48 h, 7 days, and 30 days. The prognostic properties of the TREWS were compared with those of the NEWS, Modified Early Warning Score (MEWS), and Rapid Emergency Medicine Score (REMS) using the area under the receiver operating characteristic curve (AUC) technique.ResultsThe AUC of the TREWS for in-hospital mortality within 24 h was 0.906 (95% CI, 0.903–0.908), those of the NEWS, MEWS, and REMS were 0.878 (95% CI, 0.875–0.881), 0.857 (95% CI, 0.854–0.860), and 0.834 (95% CI, 0.831–0.837), respectively. Differences in the AUC between the TREWS and NEWS, the TREWS and MEWS, and the TREWS and REMS were 0.028 (95% CI, 0.022–0.033; p < .001), 0.049 (95% CI, 0.041–0.057; p < .001), and 0.072 (95% CI, 0.063–0.080; p < .001), respectively. The TREWS showed significantly superior performance in predicting secondary outcomes.ConclusionThe TREWS predicts in-hospital mortality within 24 h, 48 h, 7 days, and 30 days better than the NEWS, MEWS, and REMS for patients arriving at the ED.     

Charlson Comorbidity Index can add prognostic information to Rapid Emergency Medicine Score as a predictor of long-term mortality.

OBJECTIVES: To investigate whether co-existing medical disorders, summed up in a comorbidity index, in nonsurgical patients attending the emergency department could predict short-term and long-term mortality, and whether the index could add prognostic information to the Rapid Emergency Medicine Score. METHODS: This was a prospective cohort study. In all, 885 nonsurgical patients, presenting to an adult emergency department and admitted to a medical department of a 1200-bed university hospital during 2 months, were enrolled consecutively. The Rapid Emergency Medicine Score (including blood pressure, oxygen saturation, respiratory rate, pulse rate, age and Glasgow coma scale) was calculated within 20 min in all those admitted to the emergency department. The history of coexisting disorders (Charlson Comorbidity Index) was collected from the medical records. RESULTS: In a univariate analysis, the Charlson Comorbidity Index could predict both short-term and long-term mortality in nonsurgical emergency department patients. An increase of one point in the 16-point Charlson Comorbidity Index scale was associated with a hazard ratio of 1.15 (95% CI 1.04-1.28, P<0.0001) for 7-day mortality and 1.28 (95% CI 1.23-1.33, P<0.0001) for 5-year mortality. The Rapid Emergency Medicine Score could also predict both short-term and long-term mortality (hazard ratio for an increase of one point in the 26-point Rapid Emergency Medicine Score scale was 1.33 (95% CI 1.28-1.39, P<0.0001) for 7-day mortality and 1.25 (95% CI 1.22-1.28, P<0.0001) for 5-year mortality. The Charlson Comorbidity Index could also add prognostic information to the Rapid Emergency Medicine Score as a predictor of long-term mortality, but it could not independently predict short-term (3-day, 7-day) mortality when forced into the same multivariate logistic model as the Rapid Emergency Medicine Score (hazard ratio for one point increase in the Charlson Comorbidity Index was 1.20 for 5-year mortality (95% CI 1.15-1.25, P<0.0001). CONCLUSION: Information on coexisting disorders (Charlson Comorbidity Index) can prognosticate both short-term and long-term mortality in the nonsurgical emergency department. It can also add prognostic information to the Rapid Emergency Medicine Score as a predictor of long-term mortality.     

Rapid acute physiology scoring in transport systems

A multi-institutional study was undertaken to define the predictive power for mortality of the Rapid Acute Physiology Score (RAPS) in a large and diverse group of transported patients. RAPS is a truncated version of the Acute Physiology and Chronic Health Evaluation (APACHE II) score that uses definitions and weighting consistent with APACHE II, but is modified to provide a consistent score just before transport, just after transport, and to use the most deranged (worst) physiologic values during the initial 4 h after arrival at the receiving hospital. During an 8-month period, 1,927 patients transported by six helicopter emergency medical service programs were studied. Over 97% (1,881) of the patients had RAPS obtained before and after transport to the receiving hospital and 92.6% (1,785) had APACHE II scoring completed after hospital admission. Receiver operating curves demonstrate similar predictive power for RAPS and APACHE II (both based on the most deranged physiologic values during the initial 24 h after admission). Before- and after-transport RAPS were also highly predictive of mortality. RAPS appears to be a reliable and highly predictive measure of patient severity/physiologic stability before and after transport to critical care.     

Prognostic importance of neutrophil-lymphocyte ratio in critically ill patients: short- and long-term outcomes

Study objectiveThe number of critically ill patients admitted to the emergency department increases daily. To decrease mortality, interventions and treatments should be conducted in a timely manner. It has been found that the neutrophil-lymphocyte ratio (NLR) is related to mortality in some disease groups, such as acute coronary syndrome and pulmonary emboli. The effect of the NLR on mortality is unknown in critically ill patients who are admitted to the emergency department. Our aim in this study is to evaluate the effect of the NLR on mortality in critically ill patients.MethodsThis study was planned as a prospective, observational cohort study. Patients who were admitted to the emergency department because they were critically ill and required the intensive care unit were included in the study. Demographic characteristics, Acute Physiology and Chronic Health Evaluation II (APACHE II), Sepsis-related Organ Failure Assessment, Glasgow Coma Score, and NLR values were recorded upon emergency department admission. The patients were followed up for sepsis, ventilator-associated pneumonia, multiorgan failure, in-hospital mortality, and 6-month mortality.ResultsThe median (interquartile range) age of the 373 patients was 74 (190) years, and 54.4% were men. Neutrophil-lymphocyte ratio values were divided into quartiles, as follows: less than 3.48, 3.48 to 6.73, 6.74-13.6, and more than 13.6. There was no difference among these 4 groups regarding demographic characteristics, APACHE II score, Sepsis-related Organ Failure Assessment score, Glasgow Coma Score, and length of hospital stay (P > .05). In the multivariable Cox regression model, in-hospital mortality and 6-month mortality NLR were hazard ratio (HR), 1.63 (1.110-2.415; P = .01) and HR, 1.58 (1.136-2.213; P = .007), respectively, and APACHE II scores were detected as independent indicators.ConclusionThe NLR is a simple, cheap, rapidly available, and independent indicator of short- and long-term mortalities. We suggest that the NLR can provide direction to emergency department physicians for interventions, particularly within a few hours after admission, in the critically ill patient group.     

Evaluation of the performance of a modified Acute Physiology and Chronic Health Evaluation (APACHE II) scoring system for critically ill patients in emergency departments in Hong Kong

INTRODUCTION: Numerous prognostic predictive models have been developed for critically ill patients, many of which are primarily designed for use in intensive care units. The objective of this study was to evaluate the accuracy of a modified Acute Physiology and Chronic Health Evaluation (APACHE II) scoring system in predicting the mortality for critically ill patients managed in emergency department (ED) resuscitation rooms in Hong Kong. METHOD: A multi-centre, prospective study was conducted for patients managed in the resuscitation rooms of the EDs of four major hospitals, including one university teaching hospital. The primary outcome measure was 14 day all-cause mortality and the secondary outcome measure was the length of stay in hospital. RESULTS: Of 867 patients recruited between 4 and 30 April 2004, 106 (12.2%) patients died. The modified APACHE II score was found to be significantly higher in non-survivors compared to survivors (mean+/-S.D.: 21.2+/-7.7 versus 14.4+/-7.1, p<0.001). The area under the curve for modified APACHE II in predicting mortality was 0.743 (95% CI, 0.696-0.790). CONCLUSION: The modified APACHE II score is only a moderate predictor of mortality for critically ill patients managed in the resuscitation rooms of EDs in Hong Kong. A more ED specific scoring method is required.     

Mortality predictions using current physiologic scoring systems in patients meeting criteria for early goal-directed therapy and the severe sepsis resuscitation bundle

Physiologic scoring systems are often used to prognosticate mortality in critically ill patients. This study examined the performance of Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II, Mortality in Emergency Department Sepsis (MEDS), and Mortality Probability Models (MPM) II0 in predicting in-hospital mortality of patients in the emergency department meeting criteria for early goal-directed therapy and the severe sepsis resuscitation bundle. The discrimination and calibration characteristics of APACHE II, SAPS II, MEDS, and MPM II0 were evaluated. Data are presented as median and quartiles (25th, 75th). Two-hundred forty-six patients aged 68 (52, 81) years were analyzed from a prospectively maintained sepsis registry, with 76.0% of patients in septic shock, 45.5% blood culture positive, and 35.0% in-hospital mortality. Acute Physiology and Chronic Health Evaluation II, SAPS II, and MEDS scores were 29 (21, 37), 54 (40, 70), and 13 (11, 16), with predicted mortalities of 64% (40%, 85%), 58% (25%, 84%), and 16% (9%, 39%), respectively. Mortality Probability Models II0 showed a predicted mortality of 60% (27%, 80%). The area under the receiver operating characteristic curves was 0.73 for APACHE II, 0.71 for SAPS II, 0.60 for MEDS, and 0.72 for MPM II0. The standardized mortality ratios were 0.59, 0.63, 1.68, and 0.64, respectively. Thus, APACHE II, SAPS II, MEDS, and MPM II0 have variable abilities to discriminate early and estimate in-hospital mortality of patients presenting to the emergency department requiring the severe sepsis resuscitation bundle. Adoption of these prognostication tools in this setting may influence therapy and resource use for these patients.     

Effectiveness of the rapid emergency medicine score and the rapid acute physiology score in prognosticating mortality in patients presenting to the emergency department with COVID-19 symptoms

ObjectiveWe investigated the effectiveness of the Rapid Emergency Medicine Score and the Rapid Acute Physiology Score in identifying critical patients among those presenting to the emergency department with COVID-19 symptoms.Material and methodsThis prospective, observational, cohort study included patients with COVID-19 symptoms presenting to the emergency department over a two-month period. Demographics, clinical characteristics, and the data of all-cause mortality within 30 days after admission were noted, and the Rapid Emergency Medicine Score and the Rapid Acute Physiology Score were calculated by the researchers. The receiver operating characteristic curve analysis was performed to determine the discriminative ability of the scores.ResultsA total of 555 patients with a mean of age of 49.4 ± 16.8 years were included in the study. The rate of 30-day mortality was 3.9% for the whole study cohort, 7.2% for the patients with a positive rt-PCR test result for SARS-CoV-2, and 1.2% for those with a negative rt-PCR test result for SARS-CoV-2. In the group of patients with COVID-19 symptoms, according to the best Youden's index, the cut-off value for the Rapid Emergency Medicine Score was determined as 3.5 (sensitivity: 81.82%, specificity: 73.08%), and the area under curve (AUC) value was 0.840 (95% confidence interval 0.768–0.913). In the same group, according to the best Youden's index, the cut-off value for the Rapid Acute Physiology Score was 2.5 (sensitivity: 90.9%, specificity: 97.38%), and the AUC value was 0.519 (95% confidence interval 0.393–0.646).ConclusionREMS is able to predict patients with COVID-19-like symptoms without positive rt-PCR for SARS-CoV-2 that are at a high-risk of 30-day mortality. Prospective multicenter cohort studies are needed to provide best scoring system for triage in pandemic clinics.     

Operational performance of validated physiologic scoring systems for predicting in-hospital mortality among critically ill emergency department patients

OBJECTIVES: New Simplified Acute Physiology Score (SAPS) II, Morbidity Probability Model at admission (MPM0 II), and Logistic Organ Dysfunction System (LODS) have all demonstrated high accuracy for predicting mortality in intensive care unit populations. We tested the prognostic accuracy of these instruments for predicting mortality among a cohort of critically ill emergency department patients. DESIGN: Secondary analysis of a randomized controlled trial. SETTING: Urban, tertiary emergency department, census >100,000. PATIENTS: Nontrauma emergency department patients admitted to an intensive care unit, aged >17 yrs, with initial emergency department vital signs consistent with shock (systolic blood pressure <100 mm Hg or shock index >1.0), and with agreement of two independent observers for at least one sign and symptom of inadequate tissue perfusion. INTERVENTIONS: Emergency department variables needed for calculation of each scoring system were prospectively collected, and published formulas were used to calculate the probability of in-hospital death for each scoring system. The main outcome was actual in-hospital mortality. The area under the receiver operating characteristic curve was used to evaluate the predictive ability of each scoring system. MEASUREMENTS AND MAIN RESULTS: Ninety-one of 202 patients (45%) were included. The mean age was 56 +/- 16 yrs, 42% were female, the mean initial systolic blood pressure was 84 +/- 13 mm Hg, and the average length of stay in the emergency department was 4.2 +/- 2.0 hrs. The in-hospital mortality rate was 21%. The area under the receiver operating characteristic curve for calculated probability of in-hospital mortality for SAPS II was 0.72 (95% confidence interval, 0.57-0.87), for MPM0 II 0.69 (95% confidence interval, 0.54-0.84), and for LODS 0.60 (95% confidence interval, 0.45-0.76). CONCLUSIONS: Using variables available in the emergency department, three previously validated intensive care unit scoring systems demonstrated moderate accuracy for predicting in-hospital mortality.     

Derivation of a prognostic score for identifying critically ill patients in an emergency department resuscitation room

Introduction

Several prognostic scores exist for critically ill patients, including APACHE II, Revised Trauma Score (RTS), Rapid Emergency Medicine Score (REMS) and Modified Early Warning Score (MEWS). However, there is no widely used score specifically designed to predict the likelihood of early intensive care unit (ICU) admission or death in undifferentiated emergency department (ED) resuscitation room patients. We aimed to derive such a score and compare it with other similar scores.

Methods

This was a single centre study of consecutive adult resuscitation room patients over one month. Physiological and blood test variables were compared according to the composite primary outcome: admission to ICU or death within 7 days of attendance. Multivariate logistic regression was used to derive a prediction score which was compared with other scores using ROC (receiver operating characteristic) analysis.

Results

330 patients were included in the study, of whom 77 were admitted to ICU or died within 7 days. A prediction score was derived using the following parameters: systolic blood pressure; Glasgow coma score; blood glucose; bicarbonate; white cell count; and a history of metastates. This score significantly out-performed APACHE II, RTS, REMS and MEWS with an area under the ROC curve of 0.909 (95% CI 0.872–0.938).

Conclusion

The Prince of Wales Emergency Department Score (PEDS) is a new prognostic score to predict the likelihood of early ICU admission or death in undifferentiated resuscitation room patients. Further studies are needed to validate and refine this potentially useful tool.     

Prognostic utilization of models based on the APACHE II,APACHE IV,and SAPS II scores for predicting in-hospital mortality in emergency department

BackgroundThis study was designed to evaluate and compare the prognostic value of the APACHE II, APACHE IV, and SAPSII scores for predicting in-hospital mortality in the ED on a large sample of patients. Earlier studies in the ED setting have either used a small sample or focused on specific diagnoses.MethodsA prospective study was conducted to include patients with higher risk of mortality from March 2016 to March 2017 in the ED of Emam Reza Hospital, northeast of Iran. Logistic regression was used to develop three models. Evaluation was performed in terms of the overall performance (Brier Score, BS, and Brier Skill Score, BSS), discrimination (Area Under the Curve, AUC), and calibration (calibration graph).ResultsA total of 2205 patients met the study criteria (53% male and median age of 64, IQR: 50–77). In-hospital mortality amounted to 19%. For APACHE II, APACHE IV, and SAPS II the BS was 0.132, 0.125 and 0.133 and the BSS was 0.156, 0.2, and 0.144, respectively. The AUC was 0.755 (0.74 to 0.779) for APACHE II, 0.794 (0.775 to 0.818) for APACHE IV, and 0.751 (0.727 to 0.776) for SAPS II. The APACHE IV showed significantly greater AUC in comparison to the APACHE II and SAPS II. The graphical evaluation revealed good calibration of the APACHE IV model.ConclusionAPACHEIV outperformed APACHEII and SAPSII in terms of discrimination and calibration. More validation is needed for using these models for decision-making about individual patients, although they would perform best at a cohort level.     

Assessing prognosis with modified early warning score,rapid emergency medicine score and worthing physiological scoring system in patients admitted to intensive care unit from emergency department

IntroductionIn this study our purpose is to examine the effectiveness and reliability of MEWS (Modified Early Warning Score), REMS (Rapid Emergency Medicine Score) and WPS (Worthing Physiological Scoring System) scoring systems for prediction of the prognosis and mortality rate of critically ill patients scheduled to be admitted to intensive care unit (ICU) among emergency department (ED) patients.MethodsThis single-centered retrospective study was performed on medical, surgical and trauma patients referred to the ED and admitted to ICU of University Hospital between 23 July 2013 and 26 November 2015.ResultsMortality and the duration of stay in ICU were significantly correlated with systolic blood pressure (SBP) and WPS score compared to other variables (p = 0.014, p = 0.010 respectively). The decrease in SBP increased the mortality by 2 (OR: %95 CI 1.1–3.5) fold and the increase in WPS increased the mortality by 2.4 (OR: %95 CI 1.2–4.5) fold.ConclusionsIn our study, there was a more significant correlation between WPS score and mortality and duration of stay in ICU compared to other scores.     

Comparison of three severity scores for critically ill cancer patients

Objective To compare three scoring systems, the Acute Physiology and Chronic Health Evaluation (APACHE) II, the Simplified Acute Physiology Score (SAPS) II and a modified Mortality Probability Model II (ICU cancer mortality model, ICMM) for their prognostic value for mortality during hospital stay in a group of cancer patients admitted to a medical ICU.Design Prospective cohort study.Setting Medical ICU of a tertiary care hospital.Patients Two hundred forty-two consecutive cancer patients admitted to the ICU.Measurements and results Variables included in APACHE II, SAPS II and the ICMM scores as well as demographic data were assessed during the first 24 h of stay in the ICU. Hospital mortality was measured; it was 44%. Calibration for all three scoring systems was acceptable, SAPS II yielded a significantly superior discrimination between survivors and non-survivors. The areas under the receiver operating characteristic curves were 0.776 for APACHE II, 0.825 for SAPS II and 0.698 for the ICMM.Conclusion The SAPS II was superior to APACHE II and ICMM. The newly developed ICMM does not improve mortality prediction in critically ill cancer patients.     

Emergency Severity Index as a predictor of in-hospital mortality in suspected sepsis patients in the emergency department

ObjectivesTo demonstrate the accuracy, sensitivity, and specificity of the Emergency Severity Index (ESI), quick Sepsis-related Organ Failure Assessment (qSOFA), Systemic Inflammatory Response Syndrome (SIRS) criteria, and National Early Warning Score (NEWS) for predicting in-hospital mortality and intensive care unit (ICU) admission in suspected sepsis patients.MethodsA retrospective cohort study conducted at a tertiary care hospital, Thailand. Suspected sepsis was defined by a combination of (1) hemoculture collection and (2) the initiation of intravenous antibiotics therapy during the emergency department (ED) visit. The accuracy of each scoring system for predicting in-hospital mortality and ICU admission was analyzed.ResultsA total of 8177 patients (median age: 62 years, 52.3% men) were enrolled in the study, 509 (6.2%) of whom died and 1810 (22.1%) of whom were admitted to the ICU. The ESI and NEWS had comparable accuracy for predicting in-hospital mortality (AUC of 0.70, 95% confidence interval [CI] 0.68 to 0.73 and AUC of 0.73, 95% CI 0.70 to 0.75) and ICU admission (AUC of 0.75, 95% CI 0.74 to 0.76 and AUC of 0.74, 95% CI 0.72 to 0.75). The ESI level 1–2 had the highest sensitivity for predicting in-hospital mortality (96.7%), and qSOFA ≥2 had the highest specificity (86.6%).ConclusionThe ESI was accurate and had the highest sensitivity for predicting in-hospital mortality and ICU admission in suspected sepsis patients in the ED. This confirms that the ESI is useful in both ED triage and predicting adverse outcomes in these patients.     

Is a specific oncological scoring system better at predicting the prognosis of cancer patients admitted for an acute medical complication in an intensive care unit than general gravity scores?

Objective To evaluate the effectiveness of a specific oncologic scoring system—the ICU Cancer Mortality model (ICM)—in predicting hospital mortality in comparison to two general severity scores—the Acute Physiology and Chronic Health Evaluation (APACHE II) and the Simplified Acute Physiology Score (SAPS II).Patients and methods All 247 patients admitted for a medical acute complication over an 18-month period in an oncological medical intensive care unit were prospectively registered. Their data, including type of complication, vital status at discharge and cancer characteristics as well as other variables necessary to calculate the three scoring systems were retrospectively assessed.Results Observed in-hospital mortality was 34%. The predicted in-hospital mortality rate for APACHE II was 32%; SAPS II, 24%; and ICM, 28%. The goodness of fit was inadequate except for the ICM score. Comparison of the area under the ROC curves revealed a better fit for ICM (area 0.79). The maximum correct classification rate was 72% for APACHE II, 74% for SAPS II and 77% for ICM. APACHE II and SAPS II were better at predicting outcome for survivors to hospital discharge, although ICM was better for non-survivors. Two variables were independently predicting the risk of death during hospitalisation: ICM (OR=2.31) and SAPS II (OR=1.05).Conclusions Gravity scores were the single independent predictors for hospital mortality, and ICM was equivalent to APACHE II and SAPS II.     

Emergency physician-based intensive care unit for critically ill patients visiting emergency department

BackgroundTo provide a prompt and optimal intensive care to critically ill patients visiting our emergency department (ED), we set up and ran a specific type of emergency intensive care unit (EICU) managed by emergency physician (EP) intensivists. We investigated whether this EICU reduced the time interval from ED arrival to ICU transfer (ED-ICU interval) without altering mortality.MethodsThis was a retrospective study conducted in a tertiary referral hospital. We collected data from ED patients who were admitted to the EICU (EICU group) and other ICUs including medical, surgical, and cardiopulmonary ICUs (other ICUs group), from August 2014 to July 2017. We compared these two groups with respect to demographic findings, including the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, ED-ICU interval, ICU mortality, and hospital mortality.ResultsAmong the 3440 critically ill patients who visited ED, 1815 (52.8%) were admitted to the EICU during the study period. The ED-ICU interval for the EICU group was significantly shorter than that for the other ICUs group by 27.5% (5.0 ± 4.9 vs. 6.9 ± 5.4 h, p < 0.001). In multivariable analysis, the ICU mortality (odds ratio = 1.062, 95% confidence interval 0.862–1.308, p = 0.571) and hospital mortality (odds ratio = 1.093, 95% confidence interval 0.892–1.338, p = 0.391) of the EICU group were not inferior to those of the other ICUs group.ConclusionsThe EICU run by EP intensivists reduced the time interval from ED arrival to ICU transfer without altering hospital mortality.     

Early Goal-directed Therapy, Corticosteroid, and Recombinant Human Activated Protein C for the Treatment of Severe Sepsis and Septic Shock in the Emergency Department

Objectives: To describe our experience with early goal‐directed therapy (EGDT), corticosteroid administration, and recombinant human activated protein C (rhAPC) administration in patients with severe sepsis or septic shock and an Acute Physiology and Chronic Health Evaluation (APACHE) II score ≥25 in the emergency department (ED). Methods: This was a retrospective case series of a prospectively maintained ED sepsis registry. Data are presented as median (25th, 75th percentile). The setting was an academic tertiary ED with approximately 60,000 annual patient visits. Patients with severe sepsis or septic shock and an APACHE II score ≥25 entered in an ED sepsis registry over a four‐month period were included. Patients who received rhAPC in the intensive care unit were excluded. Central venous catheterization for central venous pressure and central venous oxygen saturation monitoring, antibiotics, fluid resuscitation, mechanical ventilation, vasopressors, inotropes, corticosteroids, and rhAPC were initiated by the emergency physicians and continued in the intensive care unit by intensivists. Results: Twenty‐four patients were enrolled. Patient characteristics were as follows: age, 79.5 (68.0, 83.5) years; APACHE II score, 31.5 (29.8, 36.0); ED length of stay, 6.5 (4.0, 10.5) hours; predicted mortality, 76.7% (71.9, 86.4); and in‐hospital mortality, 45.8%. All patients received broad‐spectrum antibiotics, 54.2% completed EGDT, 33.3% received corticosteroids, and 33.3% received rhAPC. Time of antibiotic administration was 1.5 (1.0, 2.0) hours, time of central venous pressure/central venous oxygen saturation monitoring was 1.0 (0.5, 2.5) hour, and time of rhAPC administration was 9.5 (6.8, 10.5) hours after patients met criteria for severe sepsis or septic shock. In‐hospital mortality of patients who received rhAPC in addition to other therapies was 25.0%. Conclusions: EGDT, corticosteroid administration, and rhAPC administration are feasible in the ED setting. While these evidence‐based therapies individually have been shown to improve outcomes for patients with severe sepsis or septic shock, further studies are needed to examine their combined effectiveness during the early stages of this disease.     

Association of pulmonary artery catheter use with in-hospital mortality

OBJECTIVE: To determine the association of pulmonary artery catheter (PAC) use with in-hospital mortality. DESIGN: Prospective, observational study. SETTING: The medical intensive care units (MICU) of two teaching hospitals. METHODS: The study included 751 adults who were admitted to the MICU, excluding those who stayed for <24 hrs. Demographics and the worst Acute Physiology and Chronic Health Evaluation (APACHE) II score within the first 24 hrs of MICU admission were obtained. Daily logistic organ dysfunction system (LODS) scores were calculated. The associations of in-hospital mortality with the admission source, admission disease category, APACHE II scores, the worst LODS scores, mechanical ventilation, and PAC use were determined using chi-square, Mann-Whitney U, and multiple logistic regression analysis tests. p Values < 0.05 were considered significant. RESULTS: Mean patient age was 52.6 +/- 17.1 yrs; 425 (57%) were male; 464 (62%) were African-American, 275 (37%) Caucasian, 6 (1%) Asian, and 6 (1%) Hispanic. PAC was used in 119/751 (16%). The median APACHE II and worst LODS scores were 19 and 4, respectively. The in-hospital mortality rate was 159/751 (21%). The median APACHE II score for survivors was 17.5, compared with 28.0 for nonsurvivors (p <.0001). The worst median LODS score was 4 for survivors, compared with 11 for nonsurvivors (p <.0001). Sixty-four (54%) of the 119 patients with PAC died, compared with 95 (15%) of the 632 without PAC (p <.0001). Multiple logistic regression analysis showed that higher APACHE II-predicted mortality rate (p =.0088) and worst daily LODS score (p <.0001) were associated with increased mortality. The admission source, admission disease category, PAC use, and mechanical ventilation were not associated with in-hospital mortality. CONCLUSIONS: This study could not detect an association between PAC use and mortality. The APACHE II-predicted mortality rate and the development of multiple organ dysfunction were the main determinants of poor outcome in critically ill patients admitted to MICU.