Mortality after Discharge from Intensive Care: the Impact of Organ System Failure and Nursing Workload Use at Discharge

OBJECTIVES: Mortality after ICU discharge accounts for approx. 20-30% of deaths. We examined whether post-ICU discharge mortality is associated with the presence and severity of organ dysfunction/failure just before ICU discharge. PATIENTS AND METHODS: The study used the database of the EURICUS-II study, with a total of 4,621 patients, including 2,958 discharged alive to the general wards (post-ICU mortality 8.6%). Over a 4-month period we collected clinical and demographic characteristics, including the Simplified Acute Physiology Score (SAPS II), Nine Equivalents of Nursing Manpower Use Score, and Sequential Organ Failure Assessment (SOFA) score. RESULTS: Those who died in the hospital after ICU discharge had a higher SAPS II score, were more frequently nonoperative, admitted from the ward, and had stayed longer in the ICU. Their degree of organ dysfunction/failure was higher (admission, maximum, and delta SOFA scores). They required more nursing workload resources while in the ICU. Both the amount of organ dysfunction/failure (especially cardiovascular, neurological, renal, and respiratory) and the amount of nursing workload that they required on the day before discharge were higher. The presence of residual CNS and renal dysfunction/failure were especially prognostic factors at ICU discharge. Multivariate analysis showed only predischarge organ dysfunction/failure to be important; thus the increased use of nursing workload resources before discharge probably reflects only the underlying organ dysfunction/failure. CONCLUSIONS: It is better to delay the discharge of a patient with organ dysfunction/failure from the ICU, unless adequate monitoring and therapeutic resources are available in the ward.

Continuous Infusion of Piperacillin/Tazobactam in Septic Critically Ill Patients - a Multicenter Propensity Matched Analysis

The clinical efficacy of continuous infusion of piperacillin/tazobactam in critically ill patients with microbiologically documented infections is currently unknown. We conducted a retrospective multicenter cohort study in 7 Portuguese intensive care units (ICU). We included 569 critically ill adult patients with a documented infection and treated with piperacillin/tazobactam admitted to one of the participating ICU between 2006 and 2010. We successfully matched 173 pairs of patients according to whether they received continuous or conventional intermittent dosing of piperacillin/tazobactam, using a propensity score to adjust for confounding variables. The majority of patients received 16g/day of piperacillin plus 2g/day of tazobactam. The 28-day mortality rate was 28.3% in both groups (p = 1.0). The ICU and in-hospital mortality were also similar either in those receiving continuous infusion or intermittent dosing (23.7% vs. 20.2%, p = 0.512 and 41.6% vs. 40.5%, p = 0.913, respectively). In the subgroup of patients with a Simplified Acute Physiology Score (SAPS) II>42, the 28-day mortality rate was lower in the continuous infusion group (31.4% vs. 35.2%) although not reaching significance (p = 0.66). We concluded that the clinical efficacy of piperacillin/tazobactam in this heterogeneous group of critically ill patients infected with susceptible bacteria was independent of its mode of administration, either continuous infusion or intermittent dosing.

Modeling in-Hospital Patient Survival During the First 28 Days After Intensive Care Unit Admission: a Prognostic Model for Clinical Trials in General Critically Ill Patients

OBJECTIVE: The objective of the study was to develop a model for estimating patient 28-day in-hospital mortality using 2 different statistical approaches. DESIGN: The study was designed to develop an outcome prediction model for 28-day in-hospital mortality using (a) logistic regression with random effects and (b) a multilevel Cox proportional hazards model. SETTING: The study involved 305 intensive care units (ICUs) from the basic Simplified Acute Physiology Score (SAPS) 3 cohort. PATIENTS AND PARTICIPANTS: Patients (n = 17138) were from the SAPS 3 database with follow-up data pertaining to the first 28 days in hospital after ICU admission. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The database was divided randomly into 5 roughly equal-sized parts (at the ICU level). It was thus possible to run the model-building procedure 5 times, each time taking four fifths of the sample as a development set and the remaining fifth as the validation set. At 28 days after ICU admission, 19.98% of the patients were still in the hospital. Because of the different sampling space and outcome variables, both models presented a better fit in this sample than did the SAPS 3 admission score calibrated to vital status at hospital discharge, both on the general population and in major subgroups. CONCLUSIONS: Both statistical methods can be used to model the 28-day in-hospital mortality better than the SAPS 3 admission model. However, because the logistic regression approach is specifically designed to forecast 28-day mortality, and given the high uncertainty associated with the assumption of the proportionality of risks in the Cox model, the logistic regression approach proved to be superior.

Is It Possible to Simplify Risk Stratification Scores for Patients with ST-Segment Elevation Myocardial Infarction Undergoing Primary Angioplasty?

INTRODUCTION: There are several risk scores for stratification of patients with ST-segment elevation myocardial infarction (STEMI), the most widely used of which are the TIMI and GRACE scores. However, these are complex and require several variables. The aim of this study was to obtain a reduced model with fewer variables and similar predictive and discriminative ability. METHODS: We studied 607 patients (age 62 years, SD=13; 76% male) who were admitted with STEMI and underwent successful primary angioplasty. Our endpoints were all-cause in-hospital and 30-day mortality. Considering all variables from the TIMI and GRACE risk scores, multivariate logistic regression models were fitted to the data to identify the variables that best predicted death. RESULTS: Compared to the TIMI score, the GRACE score had better predictive and discriminative performance for in-hospital mortality, with similar results for 30-day mortality. After data modeling, the variables with highest predictive ability were age, serum creatinine, heart failure and the occurrence of cardiac arrest. The new predictive model was compared with the GRACE risk score, after internal validation using 10-fold cross validation. A similar discriminative performance was obtained and some improvement was achieved in estimates of probabilities of death (increased for patients who died and decreased for those who did not). CONCLUSION: It is possible to simplify risk stratification scores for STEMI and primary angioplasty using only four variables (age, serum creatinine, heart failure and cardiac arrest). This simplified model maintained a good predictive and discriminative performance for short-term mortality.