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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. [ABSTRACT FROM AUTHOR]

Objective: To evaluate risk factors in critically ill patients who were readmitted to an intensive care unit (ICU) during their hospital stay.Design: Prospective multicenter cohort study.Patients and Setting: A total of 15180 patients discharged from 30 medical, surgical and mixed ICUs in Austria over a 2-year period.Measurements and Results: The data analyzed included data on patients' clinical characteristics, Simplified Acute Physiology Score II (SAPS II), Logistic Organ Dysfunction system (LOD), Simplified Therapeutic Intervention Scoring System (TISS-28), length of ICU stay, ICU mortality and hospital mortality. Of the 15180 patients who survived the first ICU stay, 780 patients (5.1%) were readmitted. These patients had more than a fourfold risk of dying during their hospital stay (21.7 vs 5.2%, p<0.001). For mechanically ventilated patients, the time between extubation and discharge during the first ICU stay was significantly shorter for readmitted than for non-readmitted patients (median 1 vs 2 days, p<0.001). On the day of their first ICU discharge, readmitted patients were in greater need of organ support, with more patients still requiring ventilatory, cardiovascular and renal support than non-readmitted patients.Conclusions: The results of this study provide evidence that there exists a group of patients at higher risk of readmission to the ICU. At the time of their first ICU discharge, these patients presented with residual organ dysfunctions, which were associated with an increased risk of being readmitted. Optimizing organ functions in these patients before discharge from the ICU could result in reduced readmission rates. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the performance of the logistic organ dysfunction (LOD) system for the assessment of morbidity and mortality in multiple organ dysfunction/failure (MOD/F) in an independent database and to evaluate the use of sequential LOD measurements for the prediction of outcome.Design and Setting: Prospective, multicentric cohort study in 13 adult medical, surgical, and mixed intensive care units (ICUs) in Austria.Patients: A total of 2,893 consecutive admissions to the ICUs.Measurements and Main Results: Patient vital status at ICU and hospital discharge was recorded. Univariate analysis showed that the LOD was able to distinguish between survivors and nonsurvivors (2 vs. 6 median score). Within organ systems, higher levels of the severity of organ dysfunction were consistently associated with higher mortality. For the prediction of hospital mortality, the original prognostic LOD model did not perform well in our patients, as indicated by the goodness-of-fit C statistic. Using multiple logistic regression we developed a prognostic model with a satisfactory fit in our patients. The integration of further measurements during the ICU stay increased discrimination but not calibration.Conclusions: The LOD system is well correlated well with the numbers and levels of organ dysfunctions and discriminates well between survivors and nonsurvivors. It can thus be used to quantify the baseline severity of organ dysfunction. Moreover, after customization of the predictive equation the LOD predicted hospital mortality in our patients with high precision. It thus provides a combined measure of morbidity and mortality for critically ill patients with MOD/F. [ABSTRACT FROM AUTHOR]

Objectives: To validate SAPS II-AM, a recently customized version of the Simplified Acute Physiology Score II (SAPS II) in a larger cohort of Austrian intensive care patients and to evaluate the effect of the customization process on the ratio of observed to expected mortality.Design: Prospective, multicentric cohort study.Patients and Setting: A total of 2,901 patients consecutively admitted to 13 adult medical, surgical, and mixed intensive care units (ICUs) in Austria.Measurements and Results: After the database was divided randomly into a development sample (n = 1,450) and a validation sample (n = 1,451), logistic regression was used to develop a new model (SAPS II-AM2). The original SAPS II, the SAPS IIAM, and the newly developed SAPS II-AM2 were then compared by means of calibration, discrimination and O/E ratios. Differences in O/E ratios before and after customization (deltaO/E) were calculated. The Hosmer-Lemeshow goodness-of-fit H and C statistics revealed poor calibration of the original SAPS II on the database. The new model, SAPS II-AM2, performed better than the SAPS II-AM and excellent in the validation data set. However, mean O/E ratios varied widely among diagnostic categories (range 0.55-1.05 for the SAPS II). Moreover, the deltaO/E of the 13 ICUs ranged from -3.6 % to +25 %.Conclusions: Today's severity scoring systems, such as the SAPS II, are limited by not measuring (and adjusting for) a profound part of what constitutes case mix. Changes in the distribution of patient characteristics (known and unknown) therefore affect prognostic accuracy. First-level customization was not able to solve all these problems. Using O/E ratios for quality of care comparisons one must therefore be critical when using these data and should search for possible confounding factors. In the case of unsatisfactory calibration, customized severity of illness models may be useful as an adjunct for quality control. [ABSTRACT FROM AUTHOR]

Objectives: To examine predictors of delayed diagnosis of inflammatory bowel disease in children and adolescents., Study Design: A total of 2,436 patients (age 0-18 years) with Crohn's disease, ulcerative colitis, or unclassified colitis were included from 53 pediatric gastroenterologists. Predictors were examined with the proportional hazards model, presented as hazard ratios (HR) with 95% confidence intervals. HR < 1.0 represent factors associated with late diagnosis., Results: Median time to diagnosis was 4 (2-8) months. Crohn's disease (HR 0.62; 0.56-0.68), and within Crohn's disease, ileal disease (HR 0.77, 95% confidence interval 0.67 to 0.89) were associated with delayed diagnosis. Chances for early diagnosis increased with increasing age (HR 1.07 per year of age; 1.06 to 1.08). There was also an effect by center (HR 0.63, 0.52 to 0.67), but not by sex or country (Austria vs Germany). Growth failure was more common in those cases with delayed diagnosis., Conclusions: There is still concern about delays in the diagnosis of inflammatory bowel disease in the very young and in children with small bowel disease. Inequalities of care by region require further investigation., (Copyright © 2011. Published by Mosby, Inc.)

Objectives: To test (a) the prognostic performance of TRISS and SAPS II scoring systems in a large sample of trauma patients admitted to Austrian ICUs, and (b) the hypothesis that the prognostic performance of TRISS could be improved by adding SAPS II., Methods: Prospective multicenter cohort study comprising 5,538 trauma patients out of 35,637 patients admitted to 31 ICUs in Austria over a 4-year period., Results: Separately, TRISS and SAPS II showed lack of calibration in the cohort of trauma patients. The database was then split into two equal samples, development and validation. Using the development sample, a new scoring system was developed, with vital status at hospital discharge as the dependent variable and TRISS and SAPS II as independent variables. The prognostic performance of the new TRISS-SAPS system was then assessed in the validation cohort: Both, discrimination (as shown by area under the ROC curve), and calibration (using Hosmer-Lemeshow goodness-of-fit statistics) was excellent., Conclusions: We improved risk adjustment in critically ill trauma patients by combining TRISS and SAPS II. This new scoring system might aid in evaluating and comparing specialized trauma ICUs.

Objective: The organizational structure of health care facilities has been shown to affect outcome in critically ill patients. We evaluated the association between structures, treatments and outcomes in a large cohort of critically ill patients., Design: Prospective multicentre cohort study., Patients and Setting: A total of 26,186 patients consecutively admitted to 31 intensive care units (ICUs) in Austria from January 1998 through December 2000., Measurements and Results: The ICUs were divided into three groups according to the size and function of the hospital: community hospitals and specialized trauma centers (group A); central referral hospitals (group B); and teaching hospitals (group C). Group C patients exhibited a significantly higher risk-adjusted mortality (O/E ratio). Although severity of illness at admission in groups B and C was similar, group C patients received significantly more invasive diagnostic and therapeutic interventions throughout their ICU stay: For 7 of 10 invasive interventions identified, odds ratios for group C vs group B patients were significantly increased, even after adjustment for age, gender, severity of illness and reason for admission (odds ratios 1.2-13.1; all 95% CIs >1). Risk-adjusted multivariate analysis confirmed that six of these invasive interventions were independently associated with mortality. Furthermore, nurse-to-patient ratios did not differ between groups, leading to a significantly increased nursing workload in group C ICUs., Conclusions: Several invasive interventions were independently associated with increased mortality. Our results provide strong evidence that this association was responsible in part for the increased risk-adjusted mortality in group C patients.

Objective: To determine whether gender-related differences exist in the provided level of care and outcome in a large cohort of critically ill patients., Design: Prospective, observational cohort study with data collection from January 1, 1998, to December 31, 2000., Setting: Thirty-one intensive care units in Austria., Patients: A total of 25,998 adult patients, consecutively admitted to 31 intensive care units in Austria., Interventions: We assessed severity of illness, level of provided care, and vital status at hospital discharge., Measurements and Main Results: Of 25,998 patients, 58.3% were male and 41.7% were female. Hospital mortality rate was slightly higher in women (18.1%) than in men (17.2%), but severity of illness-adjusted mortality rate was not different. Men received an overall increased level of care and had a significantly higher probability of receiving invasive procedures, such as mechanical ventilation (odds ratio [OR], 1.22; 95% confidence interval [CI], 1.16-1.28), single vasoactive medication (OR, 1.18; 95% CI, 1.12-1.24), multiple vasoactive medication (OR, 1.21; 95% CI, 1.15-1.28), intravenous replacement of large fluid losses (OR, 1.14; 95% CI, 1.08-1.20), central venous catheter (OR, 1.06; 95% CI, 1.01-1.12), peripheral arterial catheter (OR, 1.15; 95% CI, 1.10-1.22), pulmonary artery catheter (OR, 1.48; 95% CI, 1.34-1.62), renal replacement therapy (OR, 1.28; 95% CI, 1.16-1.42), and intracranial pressure measurement (OR, 1.34; 95% CI, 1.18-1.53)., Conclusions: In a large cohort of critically ill patients, no differences in severity of illness-adjusted mortality rate between men and women were found. Despite a higher severity of illness in women, men received an increased level of care and underwent more invasive procedures. This different therapeutic approach in men did not translate into a better outcome.

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.

Objectives: Acute renal failure is a complication in critically ill patients that has been associated with an excess risk of hospital mortality. Whether this reflects the severity of the disease or whether acute renal failure is an independent risk factor is unknown. The aim of this study was to analyze severity of illness and mortality in a group of critically ill patients with acute renal failure requiring renal replacement therapy in a number of Austrian intensive care units., Design: Prospective, multicenter cohort study., Patients and Setting: A total of 17,126 patients admitted consecutively to 30 medical, surgical, and mixed intensive care units in Austria over a period of 2 yrs., Measurements and Main Results: Analyzed data included admission data, Simplified Acute Physiology Score, Logistic Organ Dysfunction system, Simplified Therapeutic Intervention Scoring System, length of intensive care unit stay, intensive care unit mortality, and hospital mortality. Of the admitted patients, 4.9% (n = 839) underwent renal replacement therapy because of acute renal failure (renal replacement therapy patients). These patients had a significantly higher hospital mortality (62.8% vs. 15.6%, p<.001), which remained significantly higher even when renal replacement therapy patients were matched with control subjects for age, severity of illness, and treatment center. Since univariate analysis demonstrated further intensity of treatment to be an additional predictor for outcome, a multivariate model including therapeutic interventions was developed. Five interventions were associated with nonsurvival (mechanical ventilation, single vasoactive medication, multiple vasoactive medication, cardiopulmonary resuscitation, and treatment of complicated metabolic acidosis/alkalosis). In contrast, the use of enteral nutrition predicted a favorable outcome., Conclusions: The results of our study suggest that acute renal failure in patients undergoing renal replacement therapy presents an excess risk of in-hospital death. This increased risk cannot be explained solely by a more pronounced severity of illness. Our results provide strong evidence that acute renal failure presents a specific and independent risk factor for poor prognosis.