Comparison of the Sequential Organ Failure Assessment, Acute Physiology and Chronic Health Evaluation II scoring system, and Trauma and Injury Severity Score method for predicting the outcomes of intensive care unit trauma patients

Purpose

The aim of this study was to assess the ability of the Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation (APACHE) II scoring system, and Trauma and Injury Severity Score (TRISS) method to predict group mortality for intensive care unit (ICU) trauma patients.

Methods

The medical records of 706 consecutive major trauma patients admitted to the ICU of Samsung Changwon Hospital from May 2006 to April 2010 were retrospectively examined. The SOFA and the APACHE II scores were calculated based on data from the first 24 hours of ICU admission, and the TRISS was calculated using initial laboratory data from the emergency department and operative data. The probability of death was calculated for each patient based on the SOFA score, APACHE II score, and TRISS equations. The ability to predict group mortality for the SOFA score, APACHE II score, and TRISS method was assessed by using 2-by-2 decision matrices and receiver operating characteristic curve analysis and calibration analysis.

Results

In 2-by-2 decision matrices with a decision criterion of 0.5, the sensitivities, specificities, and accuracies were 74.1%, 97.1%, and 92.4%, respectively, for the SOFA score; 58.5%, 99.6%, and 91.1%, respectively, for the APACHE II scoring system; and 52.4%, 94.8%, and 86.0%, respectively, for the TRISS method. In the receiver operating characteristic curve analysis, the areas under the curve for the SOFA score, APACHE II scoring system, and TRISS method were 0.953, 0.950, and 0.922, respectively.

Conclusion

The results from the present study showed that the SOFA score was not different from APACHE II scoring system and TRISS in predicting the outcomes for ICU trauma patients. However, the method for calculating SOFA scores is easier and simpler than APACHE II and TRISS.     

Arterial lactate improves the prognostic performance of severity score systems in septic patients in the ED

Objective

To evaluate the prognostic performance of lactate in septic patients in the emergency department (ED) and investigate how to add lactate to the traditional score systems.

Methods

This was a single-centered, prospective, observational cohort study conducted in ED of Beijing Chao-Yang Hospital. The study enrolled adult septic patients admitted to the ED. Arterial lactate was measured in every patient. Acute Physiology and Chronic Health Evaluation (APACHE) II, Sequential Organ Failure Assessment (SOFA), and Mortality in Emergency Department Sepsis (MEDS) scores were calculated on ED arrival. The primary outcome was 28-day mortality.

Results

The average levels of lactate, MEDS, APACHE II, and SOFA were much higher in nonsurvivors than in survivors (P < .001), and they were the independent predictors of 28-day mortality. Area under receiver operating characteristic (AUC) curves of MEDS, APACHE II, SOFA, and lactate were 0.74, 0.74, 0.75, and 0.79, respectively. The AUCs of combination lactate and MEDS, APACHE II, and SOFA were 0.81, 0.81, and 0.82, respectively and were much higher than that of score systems alone (P < .05). The AUCs of modified MEDS, APACHE II, and SOFA were 0.80, 0.80, and 0.81, respectively. The prognostic value of the modified score systems was superior to the original score systems and similar to the combination of the lactate and original score systems.

Conclusions

Lactate is a prognostic predictor in septic patients in the ED, and it may improve the performance of APACHE II, SOFA, and MEDS scores in predicting mortality.     

External validation of Acute Physiology and Chronic Health Evaluation IV in Dutch intensive care units and comparison with Acute Physiology and Chronic Health Evaluation II and Simplified Acute Physiology Score II

Purpose

The aim of this study was to validate and compare the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) IV in the Dutch intensive care unit (ICU) population to the APACHE II and Simplified Acute Physiology Score (SAPS) II.

Materials and Methods

This is a prospective study based on data from a national quality registry between 2006 and 2009 from 59 Dutch ICUs. The validation set consisted of 62?737 patients; the 3 models were compared using 44?112 patients. Measures of discrimination, accuracy, and calibration (area under the receiver operating characteristic curve (AUC), Brier score, R², and ?-statistic) were calculated using bootstrapping. In addition, the standardized mortality ratios were calculated.

Results

The original APACHE IV showed good discrimination and accuracy (AUC = 0.87, Brier score = 0.10, R² = 0.29) but poor calibration (?-statistic = 822.67). Customization significantly improved the performance of the APACHE IV.The overall discrimination and accuracy of the customized APACHE IV were statistically better, and the overall ?-statistic was inferior to those of the customized APACHE II and SAPS II, but these differences were small in perspective of clinical use.

Conclusions

The 3 models have comparable capabilities for benchmarking purposes after customization. Main advantage of APACHE IV is the large number of diagnoses that enable subgroup analysis. The APACHE IV coronary artery bypass grafting (CABG) model has a good performance in the Dutch ICU population and can be used to complement the 3 models.     

Severity scores in respiratory intensive care: APACHE II predicted mortality better than SAPS II

BACKGROUND: In recent years several scoring systems have been developed to describe the severity of illness, to establish the individual prognosis, and to group adult ICU patients by predicted risk of mortality. In addition, these scores can be used to measure and/or compare the quality of care in different ICUs. We compared the mortality predictions of the Acute Physiology and Chronic Health Evaluation (APACHE II) score and a new Simplified Acute Physiology Score (SAPS II) in patients with respiratory disease who require intensive care. PATIENTS & METHODS: We prospectively studied all 306 admissions from January 1, 1992 through December 31, 1994. McNemar and Hosmer-Lemeshow tests, and receiver operating characteristic (ROC) curves were used to describe and analyze our data. RESULTS: The average APACHE II score was 17.5 (SD 6.0), corresponding to a mean predicted death rate of 24.9% (SD 17.2%) as compared to an observed overall RICU mortality rate of 21.6%. The average SAPS II score was 39.1 (SD 11.1) corresponding to a mean predicted death rate of 26.0% (SD 18.4%). The ratio between the actual and predicted hospital mortality was 86% for APACHE II and 83% for SAPS II. Survivors had a significantly lower predicted risk of death than nonsurvivors (p < 0.0001) with both indices, and a higher Glasgow coma scale score (p < 0.0001). The ROC-curve analysis suggested the superior predictive ability of APACHE II in our patients. Area under the APACHE II ROC curve was 80.88% (standard error [SE] 2.89%), significantly larger (p < 0.01) than that found for SAPS II (73.52%, SE 3.61%). CONCLUSIONS: The APACHE II score was a good predictor of hospital outcome and better than SAPS II in our population.     

Comparison of acute physiology and chronic health evaluations II and III and simplified acute physiology score II: a prospective cohort study evaluating these methods to predict outcome in a German interdisciplinary intensive care unit

OBJECTIVE: To evaluate the ability of three scoring systems to predict hospital mortality in adult patients of an interdisciplinary intensive care unit in Germany. DESIGN: A prospective cohort study. SETTING: A mixed medical and surgical intensive care unit at a teaching hospital in Germany. PATIENTS: From a total of 3,108 patients, 2,795 patients (89.9%) for Acute Physiology and Chronic Health Evaluation (APACHE) II and 2,661 patients (85.6%) for APACHE III and Simplified Acute Physiology Score (SAPS) II could be enrolled to the study because of defined exclusion criteria. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Probabilities of hospital death for patients were estimated by applying APACHE II and III and SAPS II and compared with observed outcomes. The overall goodness-of-fit of the three models was assessed. Hospital death rates were equivalent to those predicted by APACHE II but higher than those predicted by APACHE III and SAPS II. Calibration was good for APACHE II. For the other systems, it was insufficient, but better for SAPS II than for APACHE III. The overall correct classification rate, applying a decision criterion of 50%, was 84% for APACHE II and 85% for APACHE III and SAPS II. The areas under the receiver operating characteristic curve were 0.832 for APACHE II and 0.846 for APACHE III and SAPS II. Risk estimates for surgical and medical admissions differed between the three systems. For all systems, risk predictions for diagnostic categories did not fit uniformly across the spectrum of disease categories. CONCLUSIONS: Our data more closely resemble those of the APACHE II database, demonstrating a higher degree of overall goodness-of-fit of APACHE II than APACHE III and SAPS II. Although discrimination was slightly better for the two new systems, calibration was good with a close fit for APACHE II only. Hospital mortality was higher than predicted for both new models but was underestimated to a greater degree by APACHE III. Both score systems demonstrated a considerable variation across the spectrum of diagnostic categories, which also differed between the two models.     

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   

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.     

Mortality discrimination in acute myocardial infarction: comparison between APACHE III and SAPS II prognosis systems

Objective: To compare the Acute Physiology, Age and Chronic Health Evaluation (APACHE) III with the Simplified Acute Physiology Score (SAPS II) in discriminating in-hospital mortality for intensive care unit (ICU) patients with acute myocardial infarction (AMI). Design: Prospective, observational, multicenter study. Setting: 70 Spanish ICUs. Patients and participants: 1711 patients with AMI and representative of Spanish ICUs. Measurements and results: APACHE III score, APACHE III system probability of death (APACHE III probability), SAPS II score and in-hospital mortality were noted for each patient. Two hundred and twenty three (13.0 %) patients died in the hospital. The sensitivity (± SE), specificity (± SE), and accuracy (± SE) for the APACHE III score were, respectively, 75.8 ± 2.9, 75.9 ± 1.1, and 75.9 ± 1.0. The corresponding figures for APACHE III probability were 75.3 ± 2.9, 79.2 ± 1.1, and 78.7 ± 1.0, and for SAPS II 72.2 ± 3.0, 75.9 ± 1.1, and 75.4 ± 1.0. Conclusions: The results indicate good discrimination by the three tests. APACHE III probability shows a statistically significant improvement in accuracy and specificity when compared with the two scores. Received: 4 July 1996 Accepted: 27 November 1996     

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.     

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.     

Comparison of Predisposition, Insult/Infection, Response, and Organ dysfunction, Acute Physiology And Chronic Health Evaluation II, and Mortality in Emergency Department Sepsis in patients meeting criteria for early goal-directed therapy and the severe sepsis resuscitation bundle

Purpose

The aim of the study was to examine the performance of the Predisposition, Insult/Infection, Response, and Organ dysfunction (PIRO) model compared with the Acute Physiology and Chronic Health Evaluation (APACHE) II and Mortality in Emergency Department Sepsis (MEDS) scoring systems in predicting in-hospital mortality for patients presenting to the emergency department (ED) with severe sepsis or septic shock.

Materials and Methods

This study was an analysis of a prospectively maintained registry including adult patients with severe sepsis or septic shock meeting criteria for early goal-directed therapy and the severe sepsis resuscitation bundle over a 6-year period. The registry contains data on patient demographics, sepsis category, vital signs, laboratory values, ED length of stay, hospital length of stay, physiologic scores, and outcome status. The discrimination and calibration characteristics of PIRO, APACHE II, and MEDS were analyzed.

Results

Five-hundred forty-one patients with age 63.5 ± 18.5 years were enrolled, 61.9% in septic shock, 46.9% blood-culture positive, and 31.8% in-hospital mortality. Median (25th and 75th percentile) PIRO, APACHE II, and MEDS scores were 6 (5 and 8), 28 (22 and 34), and 12 (9 and 15), with predicted mortalities of 48.5% (40.1 and 63.9), 66.0% (42.0 and 83.0), and 16.0% (9.0 and 39.0), respectively. The area under the receiver operating characteristic curves for PIRO was 0.71 (95% confidence interval, 0.66-0.75); APACHE II, 0.71 (0.66-0.76); and MEDS, 0.63 (0.60-0.70). The standardized mortality ratio was 0.70 (0.08-1.41), 0.70 (−0.46 to 1.80), and 4.00 (−8.53 to 16.62), respectively. Actual mortality significantly increased with increasing PIRO score in patients with APACHE II 25 or more (P < .01).

Conclusions

The PIRO, APACHE II, and MEDS have variable abilities to early discriminate and estimate in-hospital mortality of patients presenting to the ED meeting criteria for early goal-directed therapy and the severe sepsis resuscitation bundle. The PIRO may provide additional risk stratification in patients with APACHE II 25 or more. More studies are required to evaluate the clinical applicability of PIRO in high-risk patients with severe sepsis and septic shock.     

A laboratory-based risk score for medical intensive care patients.

BACKGROUND: Established general risk score models for intensive care patients incorporate several clinical and laboratory data. However, the collection, documentation and classification of clinical data are time-consuming, incur labor-related costs, and are dependent on the experience of the examiner. Therefore, in the present study a general score for medical intensive care patients based solely on routine laboratory parameters is presented. METHODS: Parameter selection was performed using stepwise logistic regression analysis. The maximum likelihood estimate of variable influence on mortality provided a relative weighting for each variable. The new score was compared to two established risk models (Acute Physiology And Chronic Health Evaluation II, APACHE II; and Simplified Acute Physiology Score II, SAPS II). RESULTS: The study included 528 medical intensive care patients with a mean age of 65.4+/-0.7 years. The in-hospital mortality was 16.5% (87/528). Multiple logistic regression analysis revealed eight parameters with significant prognostic power: alanine aminotransferase, cholesterol, creatinine, leukocytes, sodium, thrombocytes, urea, and age. These parameters were used to build a new laboratory score called Critical Risk Evaluation by Early Keys (CREEK). The area under the receiver operating characteristics curve was 0.857 (0.814-0.900). Pearson correlation analysis showed significant correlation between CREEK and APACHE II (r=0.550) and SAPS II (r=0.516; p<0.001; n=387). The areas under curve of the APACHE II and the SAPS II were 0.869 and 0.874, respectively. CONCLUSIONS: We show that a general risk score for medical intensive care patients on admission based solely on routine laboratory parameters is feasible. The quality of risk estimation using CREEK is comparable to established risk models. Furthermore, this new score is based on quality controlled low-cost laboratory parameters that are routinely measured on admission to the intensive care unit. Therefore, no additional costs are involved.     

Prognostic accuracy of Acute Physiology and Chronic Health Evaluation II scores in critically ill cancer patients.

BACKGROUND: The predictive accuracy of scores on the Acute Physiology and Chronic Health Evaluation II (APACHE II) for in-hospital mortality among critically ill cancer patients varies. OBJECTIVE: To evaluate the predictive accuracy of APACHE II scores for severity of illness in critically ill cancer patients and to find clinical indicators to improve the accuracy. METHODS: Actual hospital mortality rates were compared with predicted rates. Data were collected prospectively from 1263 cancer patients admitted to the intensive care unit during a 5-year period in a cancer center in Taiwan. The APACHE II score for each patient was calculated at admission. Stepwise logistic regression was used to identify clinical predictors associated with increased mortality. RESULTS: The scores ranged from 2 to 54. The mortality rates were 19% overall, 45% for medical patients, and 1% for surgical patients. The fit of the scores was good for the medical patients (Hosmer-Lemeshow statistic 8.2, P = .41). The estimated odds ratios for mortality of presence of metastasis and respiratory failure were 4.18 (95% CI 2.65-6.59) and 2.03 (95% CI 1.22-3.38), respectively. When metastasis and respiratory failure were incorporated into the APACHE II model, the area under the receiver operating characteristic curve for medical patients increased from 0.82 to 0.86. The fit of the modified model was excellent (Hosmer and Lemeshow statistic 6.57, P=.58). CONCLUSIONS: APACHE II scores are predictive of hospital mortality in critically ill cancer patients. The presence of metastasis and respiratory failure at admission are also associated with outcome.     

不同风险评估系统和炎性指标对重症老年机械通气患者撤机结果的预测价值

目的探讨不同风险评估系统及炎性指标对重症老年机械通气患者撤机结果的预测价值分析。方法选取四川省达州市中西医结合医院2016年10月-2018年12月ICU收治的136例需要机械通气的老年患者作为研究对象,于撤机前对所有患者进行APACHE II、SAPS II、MODS、SOFA、CPIS风险评估,并检测患者血清炎性指标(PCT、CRP、PTX-3、HRG)。按拔管结果分为撤机成功组和撤机困难组,使用ROC曲线分析各风险评估系统结果及炎性指标对拔管结果预测的敏感性及特异性。结果撤机成功76例,失败60例。撤机成功组APACHE II、SAPS II、MODS、SOFA、CPIS等评分均显著低于撤机困难组,组间比较差异有统计学意义(P<0.05);风险评估系统APACHE II、SAPS II、MODS、SOFA、CPIS预测机械通气的ICU患者预后情况均具有较高效能,其中SAPS II的AUC值较高,其cut-off值为26.63,敏感性为89.53%,特异性为85.05%。炎性指标PCT、CRP、PTX-3、HRG预测机械通气的ICU患者预后情况均具有较高效能,其中PTX-3的AUC值最大,显著高于其它各指标(P<0.05),其cut-off值为33.82,敏感性为68.42%,特异性为93.33%。SAPS II评分和PTX-3作为联合指标预测机械通气的ICU患者预后的敏感度为94.74%,特异度为86.67%。结论风险评估系统APACHE II、SAPS II、MODS、SOFA、CPIS均可用于预测机械通气的ICU患者预后,其中SAPS II较优。炎性指标PTX-3预测机械通气的ICU患者预后效果好,优于PCT、CRP、HRG等指标。SAPS II评分联合PTX-3预测老年机械通气的ICU患者预后效果更佳。     

The Multiple Organ Dysfunction Score (MODS) versus the Sequential Organ Failure Assessment (SOFA) score in outcome prediction

OBJECTIVE: To compare outcome prediction using the Multiple Organ Dysfunction Score (MODS) and the Sequential Organ Failure Assessment (SOFA), two of the systems most commonly used to evaluate organ dysfunction in the intensive care unit (ICU). DESIGN: Prospective, observational study. SETTING: Thirty-one-bed, university hospital ICU. PATIENTS AND PARTICIPANTS: Nine hundred forty-nine ICU patients. MEASUREMENTS AND RESULTS: The MODS and the SOFA score were calculated on admission and every 48 h until ICU discharge. The Acute Physiology and Chronic Health Evaluation (APACHE) II score was calculated on admission. Areas under receiver operating characteristic (AUROC) curves were used to compare initial, 48 h, 96 h, maximum and final scores. Of the 949 patients, 277 died (mortality rate 29.1%). Shock was observed in 329 patients (mortality rate 55.3%). There were no significant differences between the two scores in terms of mortality prediction. Outcome prediction of the APACHE II score was similar to the initial MODS and SOFA score in all patients, and slightly worse in patients with shock. Using the scores' cardiovascular components (CV), outcome prediction was better for the SOFA score at all time intervals (initial AUROC SOFA CV 0.750 vs MODS CV 0.694, p<0.01; 48 h AUROC SOFA CV 0.732 vs MODS CV 0.675, p<0.01; and final AUROC SOFA CV 0.781 vs MODS CV 0.674, p<0.01). The same tendency was observed in patients with shock. There were no significant differences in outcome prediction for the other five organ systems. CONCLUSIONS: MODS and SOFA are reliable outcome predictors. Cardiovascular dysfunction is better related to outcome with the SOFA score than with the MODS.     

Predicting six-month mortality of patients with traumatic brain injury: usefulness of common intensive care severity scores

Introduction

The aim of this study was to evaluate the usefulness of the APACHE II (Acute Physiology and Chronic Health Evaluation II), SAPS II (Simplified Acute Physiology Score II) and SOFA (Sequential Organ Failure Assessment) scores compared to simpler models based on age and Glasgow Coma Scale (GCS) in predicting long-term outcome of patients with moderate-to-severe traumatic brain injury (TBI) treated in the intensive care unit (ICU).

Methods

A national ICU database was screened for eligible TBI patients (age over 15 years, GCS 3–13) admitted in 2003–2012. Logistic regression was used for customization of APACHE II, SAPS II and SOFA score-based models for six-month mortality prediction. These models were compared to an adjusted SOFA-based model (including age) and a reference model (age and GCS). Internal validation was performed by a randomized split-sample technique. Prognostic performance was determined by assessing discrimination, calibration and precision.

Results

In total, 1,625 patients were included. The overall six-month mortality was 33%. The APACHE II and SAPS II-based models showed good discrimination (area under the curve (AUC) 0.79, 95% confidence interval (CI) 0.75 to 0.82; and 0.80, 95% CI 0.77 to 0.83, respectively), calibration (P > 0.05) and precision (Brier score 0.166 to 0.167). The SOFA-based model showed poor discrimination (AUC 0.68, 95% CI 0.64 to 0.72) and precision (Brier score 0.201) but good calibration (P > 0.05). The AUC of the SOFA-based model was significantly improved after the insertion of age and GCS (∆AUC +0.11, P < 0.001). The performance of the reference model was comparable to the APACHE II and SAPS II in terms of discrimination (AUC 0.77; compared to APACHE II, ΔAUC −0.02, P = 0.425; compared to SAPS II, ΔAUC −0.03, P = 0.218), calibration (P > 0.05) and precision (Brier score 0.181).

Conclusions

A simple prognostic model, based only on age and GCS, displayed a fairly good prognostic performance in predicting six-month mortality of ICU-treated patients with TBI. The use of the more complex scoring systems APACHE II, SAPS II and SOFA added little to the prognostic performance.     

The predictive performance of the SAPS II and SAPS 3 scoring systems: A retrospective analysis

PurposeThe purpose was to analyze and compare the performance of Simplified Acute Physiology Score (SAPS) II and SAPS 3 (North Europe Logit) in an intensive care unit (ICU) for internal disorders at a German university hospital.Materials and methodsThis retrospective study was conducted at a single-center 12-bed ICU sector for Internal Medicine in Essen, Germany, within an 18-month period. Data for adult ICU patients (N = 548) were evaluated. SAPS II and SAPS 3 scores were assessed along with the predicted mortality rates. Discrimination was evaluated by calculating the area under the receiver operating characteristic curve, and calibration was evaluated using the Hosmer-Lemeshow goodness-of-fit C-test. The ratios of observed-to-expected deaths (standardized mortality ratio, SMR) were calculated along with the 95% confidence intervals (95% CIs).ResultsThe in-hospital mortality rate was 22.6%, which provided an SMR of 0.91 (95% CI, 0.77-0.99) for SAPS II and 0.62 (95% CI, 0.52-0.71) for SAPS 3. Both SAPS II and SAPS 3 exhibited acceptable discrimination, with an area under the receiver operating characteristic curve of 0.84 (95% CI, 0.79-0.89) and 0.73 (95% CI, 0.67-0.79), respectively. However, SAPS II demonstrated superior SMR-based discrimination, which was closer to the observed mortality rate, compared with SAPS 3. Calibration curves exhibited similar performance based on the Hosmer-Lemeshow goodness-of-fit C-test results: χ² = 7.10 with P = .525 for SAPS II and χ² = 3.10 with P = .876 for SAPS 3. Interestingly, both scores overpredicted mortality.ConclusionsIn this study, SAPS 3 overestimated mortality and therefore appears less suitable for risk evaluation in comparison to SAPS II.     

Evaluation of the Acute Physiology and Chronic Health Evaluation III in predicting the prognosis of patients admitted to Emergency Department, in need of intensive care unit

Introduction

Many of critically ill patients receive medical care for prolonged periods in emergency department (ED). This study is the evaluation of efficiency of Acute Physiology and Chronic Health Evaluation (APACHE) III scoring system in predicting mortality rate in these patients.

Methods

This study was conducted between 2008 and 2009 in Tehran, Iran. One hundred subjects were enrolled in the study. Cases were chosen from patients in need of intensive care unit (ICU) bed who were kept in the ED. The APACHE III scores and predicted and observed mortality rates were calculated using the information from patients' files, interviews with the patients' families, and performing required physical examinations and laboratory tests.

Results

The age of the patients and the ED length of stay were 66.07 (±19.92) years and 5.11 (±3.79) days, respectively. The mean (±SD) of APACHE III score of the patients was 58.89 (±18.24). The predicted mortality rate was calculated to be 32.73%, whereas the observed mortality rate was 55%. The mean (±SD) of APACHE III score of survivors and nonsurvivors was 48.63 (±16.35) and 67.63 (±14.84), respectively (P < .001). Furthermore, the ED length of stay was 3.20 (±1.34) and 6.57 (±4.4) days in survivors vs nonsurvivors, respectively (P < .001).

Conclusion

The APACHE III score and ED lengths of stay were higher in this study compared with other studies. This could be ascribed to more critical patients presenting to the study center and also limited ICU bed availability. This study was indicative of applicability of APACHE III scoring system in evaluating the quality of care and prognosis of ED patients in need of ICU.     

Scoring systems for prediction of mortality in patients with intensive care unit-acquired sepsis: a comparison of the Pitt bacteremia score and the Acute Physiology and Chronic Health Evaluation II scoring systems

This study compares the effectiveness of the Pitt bacteremia score, the Charlson weighted index of comorbidity, and the Acute Physiology and Chronic Health Evaluation II (APACHE II) scoring systems for the prediction of mortality in intensive care unit (ICU) patients with sepsis using the retrospective observational method on 134 patients with ICU-acquired sepsis. The statistical analyses show several important findings. First, Pitt bacteremia score is significantly correlated with the APACHE II scoring system (correlation coefficient = 0.738, P < 0.001). Second, the APACHE II scoring system, the Pitt bacteremia score, and the Charlson weighted index of comorbidity are independently correlated with mortality. Third, the Pitt bacteremia score and the APACHE II scores are positively related to mortality in patients with ICU-acquired sepsis. As the result of the analyses, the mortality rate in patients with sepsis in the ICU is better predicted with the Pitt bacteremia score because it provides better estimation of sensitivity and specificity than the APACHE II scoring system and the Charlson weighted index of comorbidity.     

Validation of severity scoring systems SAPS II and APACHE II in a single-center population

OBJECTIVE: To validate two severity scoring systems, the Simplified Acute Physiology Score (SAPS II) and Acute Physiology and Chronic Health Evaluation (APACHE II), in a single-center ICU population. DESIGN AND SETTING: Prospective data collection in a two four-bed multidisciplinary ICUs of a teaching hospital. PATIENTS AND METHODS: Data were collected in ICU over 4 years on 1,721 consecutively admitted patients (aged 18 years or older, no transferrals, ICU stay at least 24 h) regarding SAPS II, APACHE II, predicted hospital mortality, and survival upon hospital discharge. RESULTS: At the predicted risk of 0.5, sensitivity was 39.4 % for SAPS II and 31.6 % for APACHE II, specificity 95.6 % and 97.2 %, and correct classification rate 85.6 % and 85.5 %, respectively. The area under the ROC curve was higher than 0.8 for both models. The goodness-of-fit statistic showed no significant difference between observed and predicted hospital mortality (H = 7.62 for SAPS II, H = 3.87 for APACHE II; and C = 9.32 and C = 5.05, respectively). Observed hospital mortality of patients with risk of death higher than 60 % was overpredicted by SAPS II and underpredicted by APACHE II. The observed hospital mortality was significantly higher than that predicted by the models in medical patients and in those admitted from the ward. CONCLUSIONS: This study validates both SAPS II and APACHE II scores in an ICU population comprised mainly of surgical patients. The type of ICU admission and the location in the hospital before ICU admission influence the predictive ability of the models.