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.     

A comparison of severity of illness scoring systems for elderly patients with severe pneumonia

OBJECTIVE: To evaluate the predictive ability of three severity of illness scoring systems in elderly patients with severe pneumonia requiring mechanical ventilation compared to a younger age group. DESIGN: Prospective cohort study. SETTING: Two university-affiliated tertiary care hospitals. PATIENTS AND PARTICIPANTS: One hundred four patients 75 years of age and older and 253 patients younger than 75 years of age enrolled from medical intensive care units. MEASUREMENTS AND RESULTS: Probabilities of hospital death for patients were estimated by the Acute Physiology and Chronic Health Evaluation (APACHE) II, the Mortality Probability Model (MPM) II and the Simplified Acute Physiology Score (SAPS) II. Predicted risks of hospital death were compared with observed outcomes using three methods of assessing the overall goodness of fit. The actual mortality of the elderly group was 54.87 % (95 % confidence interval [CI]: 45.2-64.4 %) compared to 28.9 % (95 % CI, 23.3-34.4 %) in the younger age group. There was a significant difference in the predictive accuracy of the scoring systems as assessed by the c-index, which is equivalent to the area under the receiver operator characteristics (ROC) curve, between the two groups, but not within individual groups. Calibration was insufficient for APACHE II and SAPS II in the elderly cohort as in-hospital mortality was lower than the predicted mortality for both models. CONCLUSIONS: Although the three severity of illness scoring systems (APACHE II, MPM II and SAPS II) demonstrated average discrimination when applied to estimate hospital mortality in the elderly patients with severe pneumonia, MPM II had the closest fit to our database. Alternative modeling approaches might be needed to customize the model coefficients to the elderly population for more accurate probabilities or to develop specialized models targeted to the designed population.     

Comparison of the Rapid Emergency Medicine Score and APACHE II in Nonsurgical Emergency Department Patients

OBJECTIVES: To improve the Rapid Acute Physiology Score (RAPS) as a predictor of in-hospital mortality in the nonsurgical emergency department (ED) by including age and oxygen saturation, and to compare this new system, Rapid Emergency Medicine Score (REMS), with the Acute Physiology and Chronic Health Examination (APACHE II) with reference to predictive accuracy. METHODS: This was a prospective cohort study. One hundred sixty-two critically ill patients consecutively admitted to the intensive care unit (ICU) during the period of one year, and 865 nonsurgical patients presenting to an adult emergency department (ED) and admitted to a medical department of a 1200-bed university hospital during two months, were enrolled. For all entries to the ED, RAPS was calculated and developed to include noninvasive peripheral oxygen saturation and patient age (REMS), as well as laboratory tests (APACHE II). These scores were calculated for each patient. RESULTS: REMS was found to be superior to RAPS in predicting in-hospital mortality both in the critically ill patients admitted to the ICU and in the total sample (area under receiver-operating characteristic curve [AUC] 0.910 +/- 0.015 for REMS compared with 0.872 +/- 0.022 for RAPS, p < 0.001). An increase of 1 point in the 26-point REMS scale was associated with an odds ratio of 1.40 for in-hospital death (95% confidence interval = 1.36 to 1.45, p < 0.0001). The more advanced APACHE II was not found to be superior to REMS (AUC: 0.901 +/- 0.015, p = 0.218). CONCLUSIONS: RAPS could be improved as a predictor of in-hospital mortality in the nonsurgical ED by including oxygen saturation and patient age to the system. This new scoring system, REMS, had the same predictive accuracy as the well-established, but more complicated, APACHE II.     

Characteristics associated with analgesia ordering in the intensive care unit and relationships with outcome

OBJECTIVE: To describe clinical characteristics associated with analgesia utilization in the intensive care unit. DESIGN: A prospective cohort study of adult patients admitted to a medical intensive care unit. SUBJECTS: Four hundred adult patients. SETTING: Twelve-bed medical intensive care unit of an inner-city, university-affiliated hospital. MEASUREMENTS AND MAIN RESULTS: Collected data included demographics, sedation and neuromuscular blocking agents used, mechanical ventilation, hemodynamic monitoring, Therapeutic Intervention Scoring System score, Logistic Organ Dysfunction System (LODS) score, and Acute Physiology and Chronic Health Evaluation (APACHE) II score. Hospital outcome was noted. The odds ratio and 95% confidence intervals were determined by using multiple logistic regression analyses. Patients' mean age (+/-sd) was 47.8 +/- 17.1 yrs; 58% were male, 84% African-American. Their APACHE II-predicted hospital mortality rate was 33%. Analgesics were used in 36% of patients. There were no differences in demographics, initial LODS score, APACHE II score, and mechanical ventilation use between patients who did and did not receive analgesics. Multiple logistic regression analysis showed that analgesic use was independently associated with sedation (odds ratio, 2.47; 95% confidence interval, 1.47-4.14), neuromuscular blockade (odds ratio, 4.98; 95% confidence interval, 1.85-13.41), and pulmonary artery flotation catheter utilization (odds ratio, 2.31; 95% confidence interval, 1.27-4.20). The median duration of mechanical ventilation was 5 days for those who received analgesia compared with 2 for those who did not (p =.0001). The median length of stay in the intensive care unit (4 vs. 2, p <.0001) and hospital (11 vs. 7, p <.0001) was higher in patients who received analgesics. There were no significant differences in intensive care unit and hospital mortality rates between patients who did and did not receive analgesics. CONCLUSIONS: Intensive care unit patients for whom analgesics were prescribed have a higher frequency of hemodynamic monitoring and use of sedative and neuromuscular blocking agents, more mechanical ventilation days, and longer intensive care unit and hospital lengths of stay.     

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.     

Early lactate clearance is associated with improved outcome in severe sepsis and septic shock

OBJECTIVE: Serial lactate concentrations can be used to examine disease severity in the intensive care unit. This study examines the clinical utility of the lactate clearance before intensive care unit admission (during the most proximal period of disease presentation) as an indicator of outcome in severe sepsis and septic shock. We hypothesize that a high lactate clearance in 6 hrs is associated with decreased mortality rate. DESIGN: Prospective observational study. SETTING: An urban emergency department and intensive care unit over a 1-yr period. PATIENTS: A convenience cohort of patients with severe sepsis or septic shock. INTERVENTIONS: Therapy was initiated in the emergency department and continued in the intensive care unit, including central venous and arterial catheterization, antibiotics, fluid resuscitation, mechanical ventilation, vasopressors, and inotropes when appropriate. MEASUREMENTS AND MAIN RESULTS: Vital signs, laboratory values, and Acute Physiology and Chronic Health Evaluation (APACHE) II score were obtained at hour 0 (emergency department presentation), hour 6, and over the first 72 hrs of hospitalization. Therapy given in the emergency department and intensive care unit was recorded. Lactate clearance was defined as the percent decrease in lactate from emergency department presentation to hour 6. Logistic regression analysis was performed to determine independent variables associated with mortality. One hundred and eleven patients were enrolled with mean age 64.9 +/- 16.7 yrs, emergency department length of stay 6.3 +/- 3.2 hrs, and overall in-hospital mortality rate 42.3%. Baseline APACHE II score was 20.2 +/- 6.8 and lactate 6.9 +/- 4.6 mmol/L. Survivors compared with nonsurvivors had a lactate clearance of 38.1 +/- 34.6 vs. 12.0 +/- 51.6%, respectively (p =.005). Multivariate logistic regression analysis of statistically significant univariate variables showed lactate clearance to have a significant inverse relationship with mortality (p =.04). There was an approximately 11% decrease likelihood of mortality for each 10% increase in lactate clearance. Patients with a lactate clearance> or =10%, relative to patients with a lactate clearance <10%, had a greater decrease in APACHE II score over the 72-hr study period and a lower 60-day mortality rate (p =.007). CONCLUSIONS: Lactate clearance early in the hospital course may indicate a resolution of global tissue hypoxia and is associated with decreased mortality rate. Patients with higher lactate clearance after 6 hrs of emergency department intervention have improved outcome compared with those with lower lactate clearance.     

Application of mortality prediction systems to individual intensive care units

Objective: To evaluate the predictive accuracy of the severity of illness scoring systems in a single institution. Design: A prospective study conducted by collecting data on consecutive patients admitted to the medical intensive care unit over 20 months. Surgical and coronary care admissions were excluded. Setting: Veterans Affairs Medical Center at Buffalo, New York. Patients and participants: Data collected on 302 unique, consecutive patients admitted to the medical intensive care unit. Interventions: None. Measurements and results: Data required to calculate the patients' predicted mortality by the Mortality Probability Model (MPM) II, Acute Physiology and Chronic Health Evaluation (APACHE) II and Simplified Acute Physiology Score (SAPS) II scoring systems were collected. The probability of mortality for the cohort of patients was analyzed using confidence interval analyses, receiver operator characteristic (ROC) curves, two by two contingency tables and the Lemeshow–Hosmer chi-square statistic. Predicted mortality for all three scoring systems lay within the 95 % confidence interval for actual mortality. For the MPM II, SAPS II and APACHE II, the c-index (equivalent to the area under the ROC curve) was 0.695 ± 0.0307 SE, 0.702 ± 0.063 SE and 0.672 ± 0.0306 SE, respectively, which were not statistically different from each other but were lower than values obtained in previous studies. Conclusion: Although the overall mortality was consistent with the predicted mortality, the poor fit of the data to the model impairs the validity of the result. The observed outcoume could be due to erratic quality of care, or differences between the study population and the patient population in the original studies. The data cannot be used to distinguish between these possibilities. To increase predictive accuracy when studying individual intensive care units and enhance quality of care assessments it may be necessary to adapt the model to the patient population. Received: 21 December 1998 Final revision received: 26 May 1999 Accepted: 1 June 1999     

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   

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.     

Assessment of the performance of five intensive care scoring models within a large Scottish database

OBJECTIVE: To assess and compare the performance of five severity of illness scoring systems used commonly for intensive care unit (ICU) patients in the United Kingdom. The five models analyzed were versions II and III of the Acute Physiology and Chronic Health Evaluation (APACHE) system, a version of APACHE II using United Kingdom (UK)-derived coefficients (UK APACHE II), version II of the Simplified Acute Physiology Score (SAPS), and version II of the Mortality Probability Model, computed at admission (MPM0) and after 24 hrs in the ICU (MPM24). DESIGN: A 2-yr prospective cohort study of consecutive admissions to intensive care units. SETTING: A total of 22 general ICUs in Scotland PATIENTS: A total of 13,291 admissions to the study, which after prospectively agreed exclusions left a total of 10,393 patients for the analysis. OUTCOME MEASURES: Death or survival at hospital discharge. MEASUREMENTS AND MAIN RESULTS: All the models showed reasonable discrimination using the area under the receiver operating characteristic curve (APACHE III, 0.845; APACHE II, 0.805; UKAPACHE II, 0.809; SAPS II, 0.843; MPM0, 0.785; MPM24, 0.799). The levels of observed mortality were significantly different than that predicted by all models, using the Hosmer-Lemeshow goodness-of-fit C test (p < .001), with the results of the test being confirmed by calibration curves. When excluding patients discharged in the first 24 hrs to allow for comparisons using the same patient group, APACHE III, MPM24, and SAPS II (APACHE III, 0.795; MPM24, 0.791; SAPS II, 0.784) showed significantly better discrimination than APACHE II, UK APACHE II, and MPM0 (APACHE II, 0.763; UK APACHE II, 0.756; MPM0, 0.741). However, calibration changed little for all models with observed mortality still significantly different from that predicted by the scoring systems (p < .001). For equivalent data sets, APACHE II demonstrated superior calibration to all the models using the chi-squared value from the Hosmer-Lemeshow test for both populations (APACHE III, 366; APACHE II, 67; UKAPACHE II, 237; SAPS II, 142; MPM0, 452; MPM24, 101). CONCLUSIONS: SAPS II demonstrated the best overall performance, but the superior calibration of APACHE II makes it the most appropriate model for comparisons of mortality rates in different ICUs. The significance of the Hosmer-Lemeshow C test in all the models suggest that new logistic regression coefficients should be generated and the systems retested before they could be used with confidence in Scottish ICUs.     

Identifying quality outliers in a large,multiple-institution database by using customized versions of the Simplified Acute Physiology Score II and the Mortality Probability Model II0

OBJECTIVE: To assess whether customized versions of the Simplified Acute Physiology Score (SAPS) II and the Mortality Probability Model (MPM) II0 agree on the identity of intensive care unit quality outliers within a multiple-center database. DESIGN: Retrospective database analysis. SETTING AND PATIENTS: Patient subset of the Project IMPACT database consisting of 39,617 adult patients admitted to surgical, medical, and mixed surgical-medical intensive care units at 54 hospitals between 1995 and 1999 who met inclusion criteria for SAPS II and MPM II0. INTERVENTIONS: Customized versions of SAPS II and MPM II0 were obtained by fitting new logistic regressions to the data by using the risk score as the independent variable and outcome at hospital discharge as the dependent variable. The data set was divided randomly into a training set and a validation set. Each model was customized by using the training set; model performance was then assessed in the validation set by using the area under the receiver operating characteristic curve and the Hosmer-Lemeshow statistic. The final models were based on the entire data set. The level of agreement between the customized models on the identity of quality outliers was evaluated by using kappa analysis. MEASUREMENTS AND MAIN RESULTS: Both customized models exhibited good discrimination and good calibration in this database. The area under the receiver operating characteristic curve was 0.83 for MPM II0 and 0.872 for SAPS II following model customization. The Hosmer-Lemeshow statistic was 12.3 ( >.14) for MPM II0, and 8.17 (p >.42) for SAPS II, after customization. Kappa analysis showed only fair agreement between the two customized models with regard to the identity of the quality outliers: kappa = 0.44 (95% confidence interval, 0.24, 0.65). CONCLUSIONS: Customization of SAPS II and MPM II0 to the Project IMPACT database resulted in well-calibrated models. Despite this, the models exhibited only a moderate level of agreement in which hospitals were designated as quality outliers. Seventeen of the 54 hospitals were categorized differently depending on which of the two scoring systems was used. Therefore, the rating of quality of care appears, in part, to be a function of the prediction model used.     

Predictors of intensive care unit and hospital length of stay in diabetic ketoacidosis

OBJECTIVE: To determine the predictive value for prolonged intensive care unit (ICU) and hospital length of stay (LOS) in patients with diabetic ketoacidosis (DKA) of the Acute Physiology and Chronic Health Evaluation II (APACHE II) score and Logistic Organ Dysfunction System (LODS), and to identify associated characteristics. DESIGN: Prospective cohort, 18-month observation. SUBJECTS AND SETTING: All admissions to a 12-bed, inner-city, university-affiliated hospital, medical ICU from July 1999 to December 2000. MEASUREMENTS: Data for APACHE II and LODS scoring systems were collected within 24 hours of admission. Lengths of ICU and hospital stay were the primary outcomes. Prolonged ICU and hospital LOS were defined as 3 or more and 6 or more days. RESULTS: A total of 584 patients, mean age 49, 56% men, 82% African American were admitted to the ICU. At admission they had (mean +/-SD) APACHE II (18 +/- 10), LODS (5 +/- 4), and predicted mortality of 32% +/- 29%. DKA was the admitting diagnosis in 42 (7.6%) patients; they had lower APACHE II (12 +/- 6), LODS (2 +/- 1), and predicted mortality 5% +/- 5% than the general ICU population (all, P <.001). Hospital mortality in non-DKA patients was 18%; there were no deaths in patients with DKA. Among DKA patients, those with insulin noncompliance had a shorter hospital stay (2.8 +/- 1 d) than those with an underlying illness as the DKA trigger (4.8 +/- 3, P =.02). Between patients with DKA, regardless of the LOS, there were no significant differences in APACHE II, LODS, or predicted mortality. CONCLUSIONS: ICU-admitted patients with DKA are less ill, and have lower disease severity scores, mortality, and shorter length of ICU and hospital stay than non-DKA patients. Disease severity scores are not, but precipitating cause is, predictor associated with prolonged hospital LOS in patients with DKA.     

Impact of exclusion criteria on case mix, outcome, and length of stay for the severity of disease scoring methods in common use in critical care

OBJECTIVE: To identify the exclusion criteria for the major severity of disease scoring methods in critical care and to investigate the impact of the exclusion criteria on the case mix, outcomes and length of stay for admissions to intensive care units (ICUs) in England, Wales and Northern Ireland. DESIGN: Cohort study-analysis of prospectively collected data. SETTING: 127 adult, general (mixed medical/surgical) ICUs in England, Wales and Northern Ireland. PATIENTS: 120,503 admissions between 1995 and 2001. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Thirteen different exclusion criteria were identified from the original methodological/validation papers and data collection manuals for APACHE II, APACHE III, SAPS II and MPM II. Application of the original exclusion criteria for the four, major severity of disease scoring methods resulted in exclusion of between 11.5% and 14.6% of admissions. Hospital mortality for the overall cohort was 29.0% but ranged from 4.7% to 50.1% among those groups excluded. After application of the exclusion criteria for each scoring method, there was little difference in overall hospital mortality or median ICU and hospital length of stay for the included admissions when compared with the original cohort. At the level of individual ICUs, there were differences in hospital mortality before and after exclusions-minimum -3.1% to maximum 9.5% (APACHE II), minimum -2.8% to maximum 9.4% (APACHE III), minimum -3.1% to maximum 16.1% (SAPS II) and minimum -3.1% to maximum 16.5% (MPM II). The mean difference across individual ICUs was -0.5 % (95% CI -0.7% to -0.2%) for APACHE II, -0.2% (95% CI -0.2% to 0.1%) for APACHE III, 2.0% (95% CI 1.7% to 2.4%) for SAPS II and 2.1% (95% CI 1.7% to 2.5%) for MPM II. SAPS II and MPM II showed systematic variation. A survey of the literature found wide variation in the exclusion criteria reported in subsequent, published research using a single severity of disease scoring method (APACHE II). CONCLUSIONS: Exclusion criteria used in critical care research are often ill-defined and poorly reported. More attention to the choice of exclusion criteria and their effect on the reported results is essential. We hope this study will raise the need for both better reporting of exclusion criteria applied in studies and promote the need for a common set of explicit exclusion criteria for these methods.     

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.     

Implementation of a bundle of quality indicators for the early management of severe sepsis and septic shock is associated with decreased mortality

OBJECTIVE: The purpose of this study was to examine the outcome implications of implementing a severe sepsis bundle in an emergency department as a quality indicator set with feedback to modify physician behavior related to the early management of severe sepsis and septic shock. DESIGN: Two-year prospective observational cohort. SETTING: Academic tertiary care facility. PATIENTS: Patients were 330 patients presenting to the emergency department who met criteria for severe sepsis or septic shock. INTERVENTIONS: Five quality indicators comprised the bundle for severe sepsis management in the emergency department: a) initiate central venous pressure (CVP)/central venous oxygen saturation (Scvo2) monitoring within 2 hrs; b) give broad-spectrum antibiotics within 4 hrs; c) complete early goal-directed therapy at 6 hrs; d) give corticosteroid if the patient is on vasopressor or if adrenal insufficiency is suspected; and e) monitor for lactate clearance. MEASUREMENTS AND MAIN RESULTS: Patients had a mean age of 63.8 +/- 18.5 yrs, Acute Physiology and Chronic Health Evaluation II score 29.6 +/- 10.6, emergency department length of stay 8.5 +/- 4.4 hrs, hospital length of stay 11.3 +/- 12.9 days, and in-hospital mortality 35.2%. Bundle compliance increased from zero to 51.2% at the end of the study period. During the emergency department stay, patients with the bundle completed received more CVP/Scvo2 monitoring (100.0 vs. 64.8%, p < .01), more antibiotics (100.0 vs. 89.7%, p = .04), and more corticosteroid (29.9 vs. 16.2%, p = .01) compared with patients with the bundle not completed. In a multivariate regression analysis including the five quality indicators, completion of early goal-directed therapy was significantly associated with decreased mortality (odds ratio, 0.36; 95% confidence interval, 0.17-0.79; p = .01). In-hospital mortality was less in patients with the bundle completed compared with patients with the bundle not completed (20.8 vs. 39.5%, p < .01). CONCLUSIONS: Implementation of a severe sepsis bundle using a quality improvement feedback to modify physician behavior in the emergency department setting was feasible and was associated with decreased in-hospital mortality.     

Impact of delayed transfer of critically ill patients from the emergency department to the intensive care unit

OBJECTIVE: Numerous factors can cause delays in transfer to an intensive care unit for critically ill emergency department patients. The impact of delays is unknown. We aimed to determine the association between emergency department "boarding" (holding admitted patients in the emergency department pending intensive care unit transfer) and outcomes for critically ill patients. DESIGN: This was a cross-sectional analytical study using the Project IMPACT database (a multicenter U.S. database of intensive care unit patients). Patients admitted from the emergency department to the intensive care unit (2000-2003) were included and divided into two groups: emergency department boarding >or=6 hrs (delayed) vs. emergency department boarding <6 hrs (nondelayed). Demographics, intensive care unit procedures, length of stay, and mortality were analyzed. Groups were compared using chi-square, Mann-Whitney, and unpaired Student's t-tests. SETTING: Emergency department and intensive care unit. PATIENTS: Patients admitted from the emergency department to the intensive care unit (2000-2003). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Main outcomes were intensive care unit and hospital survival and intensive care unit and hospital length of stay. During the study period, 50,322 patients were admitted. Both groups (delayed, n = 1,036; nondelayed, n = 49,286) were similar in age, gender, and do-not-resuscitate status, along with Acute Physiology and Chronic Health Evaluation II score in the subgroup for which it was recorded. Among hospital survivors, the median hospital length of stay was 7.0 (delayed) vs. 6.0 days (nondelayed) (p < .001). Intensive care unit mortality was 10.7% (delayed) vs. 8.4% (nondelayed) (p < .01). In-hospital mortality was 17.4% (delayed) vs. 12.9% (nondelayed) (p < .001). In the stepwise logistic model, delayed admission, advancing age, higher Acute Physiology and Chronic Health Evaluation II score, male gender, and diagnostic categories of trauma, intracerebral hemorrhage, and neurologic disease were associated with lower hospital survival (odds ratio for delayed admission, 0.709; 95% confidence interval, 0.561-0.895). CONCLUSIONS: Critically ill emergency department patients with a >or=6-hr delay in intensive care unit transfer had increased hospital length of stay and higher intensive care unit and hospital mortality. This suggests the need to identify factors associated with delayed transfer as well as specific determinants of adverse outcomes.     

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.     

Intracranial pressure monitoring and case mix-adjusted mortality in intracranial hemorrhage

OBJECTIVE: Intracranial pressure (ICP) monitoring is frequently used in intensive care treatment of patients with intracranial hemorrhage. Data demonstrating an improved outcome from this intervention are lacking. We analyzed standardized mortality ratios in patients with and without ICP monitoring to determine its efficacy. DESIGN: A nonrandomized study of case records of consecutively admitted intensive care unit (ICU) patients with intracranial hemorrhage. SETTING: General and medical ICU of a 900-bed tertiary-care hospital. PATIENTS: A total of 225 patients with intracranial hemorrhage (mainly nontraumatic) admitted consecutively between April 1997 and March 2000. MEASUREMENTS: Simplified Acute Physiology Score (SAPS) II, diagnosis, age, sex, use of ICP monitoring, and in-hospital mortality rates were collected from the hospital's ICU database. Expected mortality was provided by means of SAPS II. Standardized mortality ratios were calculated and compared in 119 patients with ICP monitoring and 106 patients without ICP monitoring. MAIN RESULTS: The case mix-adjusted hospital mortality in the group with ICP monitoring was in the expected range (standardized mortality ratio, 1.09 [95% confidence interval (CI), 0.87-1.31]). Patients without ICP monitoring had a significantly higher standardized mortality ratio than expected (1.26 [95% CI, 1.06-1.46]). CONCLUSIONS: A beneficial effect of ICP monitoring in patients with intracranial hemorrhage may be reflected in an improved standardized mortality ratio.     

Comparison of Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) scoring systems in a single Greek intensive care unit

OBJECTIVE: To evaluate Acute Physiology and Chronic Health Evaluation (APACHE) II and Simplified Acute Physiology Score (SAPS) II scoring systems in a single intensive care unit (ICU), independent from the ICUs of the developmental sample; and to compare the performance of APACHE II and SAPS II by means of statistical analyses in such a clinical setting. DESIGN: Prospective, cohort study. SETTING: A single ICU in a Greek university hospital. PATIENTS: In a time interval of 5 yrs, data for 681 patients admitted to our ICU were collected. The original exclusion criteria of both systems were employed. Patients <17 yrs of age were dropped from the study to keep compatibility with both systems. Eventually, a total of 661 patients were included in the analysis. INTERVENTIONS: Demographics, clinical parameters essential for the calculation of APACHE II and SAPS II scores, and risk of hospital death were recorded. Patient vital status was followed up to hospital discharge. MEASUREMENTS AND MAIN RESULTS: Both systems showed poor calibration and underestimated mortality but had good discriminative power, with SAPS II performing better than APACHE II. The evaluation of uniformity of fit in various subgroups for both systems confirmed the pattern of underprediction of mortality from both models and the better performance of APACHE II over our data sample. CONCLUSIONS: APACHE II and SAPS II failed to predict mortality in a population sample other than the one used for their development. APACHE II performed better than SAPS II. Validation in such a population is essential. Because there is a great variation in clinical and other patient characteristics among ICUs, it is doubtful that one system can be validated in all types of populations to be used for comparisons among different ICUs.     

APACHE Ⅱ、SAPS Ⅱ及LODS 3种评分系统在单一重症监护室的应用比较

目的比较和评价急性生理学与慢性健康状况评分系统Ⅱ（APAcHEⅡ）、简明急性生理功能评分系统Ⅱ（SAPSⅡ）及Logistic器官功能障碍系统（LODS）3种评分系统对危重病患者院内病死率的预测能力。方法应用3种评分系统计算出病死概率并与实际病死率比较。通过受试者工作特征曲线（ROC）下的面积及分类表，判定3种评分系统的拟合优度；而各评分系统对分层精确度的预测则用校准曲线及Lemeshow—Hosmer妒统计来评估。结果APACHEⅡ评分系统的预测病死率与实际病死率基本相符，而其他两种评分系统的预测病死率偏低。APACHEⅡ、SAPSⅡ及LODS各评分系统的ROC曲线下面积分别为0．881、0．904和0．875；95％可信区间分别为0．858～0．904，0．884～0．924和0．851～0．898；而在诊断界点为50％时，APACHEⅡ、SAPSⅡ及LODS各评分系统的整体正确分类率分别为81．60％、82．Og％和79．26％。APACHEⅡ（X^2=9．69）及SAPSⅡ（X^2=13．50）评分系统对分层精确度的预测较好，LODS评分系统则较差（X^2=87．22）。结论3种评分系统预测危重病患者预后的鉴别能力均较好且接近一致，APACHEⅡ及SAPSⅡ评分系统的分层预测精确度明显好于LODS。