May 152013
 
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A Systematic Review of Evidence-Informed Practices for Patient Care Rounds in the ICU.

Crit Care Med. 2013 May 9;

Authors: Lane D, Ferri M, Lemaire J, McLaughlin K, Stelfox HT

Abstract
OBJECTIVES:: Patient care rounds are a key mechanism by which healthcare providers communicate and make patient care decisions in the ICU but no synthesis of best practices for rounds currently exists. Therefore, we systematically reviewed the evidence for facilitators and barriers to patient care rounds in the ICU. DATA SOURCES:: Search of Medline, Embase, CINAHL, PubMed, and the Cochrane library through September 21, 2012. STUDY SELECTION:: Original, peer-reviewed research studies (no methodological restrictions) were selected, which described current practices, facilitators, or barriers to healthcare provider rounding in the ICU. DATA EXTRACTION:: Two authors with methodological and content expertise independently abstracted data using a prespecified abstraction tool. DATA SYNTHESIS:: The literature search identified 7,373 citations. Reviews of abstracts led to the retrieval of 136 full text articles for assessment; 43 articles in three languages (English, German, Spanish) were selected for review. Of these, 13 were ethnographic studies and 15 uncontrolled before-after studies. Six studies used control groups, including one cross-over randomized, one time-series, three cohort, and one controlled before-after study. A total of 13 facilitators and 9 barriers to patient care rounds were identified through a narrative and meta-synthesis of included studies. Identified facilitators suggest that the quality of rounds is improved when conducted by a multidisciplinary group of providers, with explicitly defined roles, using a standardized structure and goal-oriented approach that includes a best practices checklist. Barriers to quality patient care rounds include poor information retrieval and documentation, interruptions, long rounding times, and allied healthcare provider perceptions of not being valued by rounding physicians. CONCLUSIONS:: Although the evidence base for best practices of patient care rounds in the ICU is limited, several practical and low-risk practices can be considered for implementation.

PMID: 23666096 [PubMed - as supplied by publisher]

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May 112013
 

A New Severity of Illness Scale Using a Subset of Acute Physiology, Age, and Chronic Health Evaluation Data Elements Shows Comparable Predictive Accuracy.

Crit Care Med. 2013 May 8;

Authors: Johnson AE, Kramer AA, Clifford GD

Abstract
OBJECTIVES:: Severity of illness scores have gained considerable interest for their use in predicting outcomes such as mortality and length of stay. The most sophisticated scoring systems require the collection of numerous physiologic measurements, making their use in real-time difficult. A severity of illness score based on a few parameters that can be captured electronically would be of great benefit. Using a machine-learning technique known as particle swarm optimization, we attempted to reduce the number of physiologic parameters collected in the Acute Physiology, Age, and Chronic Health Evaluation IV system without losing predictive accuracy. DESIGN:: Retrospective cohort study of ICU admissions from 2007 to 2011. SETTING:: Eighty-six ICUs at 49 U.S. hospitals where an Acute Physiology, Age, and Chronic Health Evaluation IV system had been installed. PATIENTS:: 81,087 admissions, of which 72,474 did not have any missing values. INTERVENTIONS:: None. MEASUREMENTS AND MAIN RESULTS:: Machine-learning algorithms were used to come up with the minimal set of variables that were capable of yielding an accurate severity of illness score: the Oxford Acute Severity of Illness Score. Predictive models of ICU mortality using Oxford Acute Severity of Illness Score were developed on admissions during 2007-2009 and validated on admissions during 2010-2011. The most parsimonious Oxford Acute Severity of Illness Score consisted of seven physiologic measurements, elective surgery, age, and prior length of stay. Predictive models of ICU mortality using Oxford Acute Severity of Illness Score achieved an area under the receiver operating characteristic curve of 0.88 and calibrated well. CONCLUSIONS:: A reduced severity of illness score had discrimination and calibration equivalent to more complex existing models. This was accomplished in large part using machine-learning algorithms, which can effectively account for the nonlinear associations between physiologic parameters and outcome.

PMID: 23660729 [PubMed - as supplied by publisher]

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May 112013
 

Predictive Ability of the Stability and Workload Index for Transfer Score to Predict Unplanned Readmissions After ICU Discharge.

Crit Care Med. 2013 May 8;

Authors: Kastrup M, Powollik R, Balzer F, Röber S, Ahlborn R, von Dossow-Hanfstingl V, Wernecke KD, Spies CD

Abstract
OBJECTIVE:: Unplanned readmission of hospitalized patients to an ICU is associated with an increased mortality and hospital length of stay. The ability to identify patients at risk, who would benefit from prolonged ICU treatment, is limited. The aim of this study is to validate a previously published numerical index named the Stability and Workload Index for Transfer in a heterogeneous group of ICU patients. DESIGN:: In this retrospective data analysis, the Stability and Workload Index for Transfer score was calculated for all patients, and the ability of the score to predict readmission was compared with the original publication. SETTING:: Four ICUs, one intermediate care unit, and one postanesthesia care unit of the department of anesthesia and intensive care of a university hospital. PATIENTS:: All consecutive patients treated in one of the units. INTERVENTIONS:: None. MEASUREMENTS AND MAIN RESULTS:: Unplanned ICU readmissions or unexpected death within 7 days of ICU discharge. The data of 7,175 patients were included in the analysis. Five hundred ninety-six patients were readmitted or died within 7 days of discharge. The patients who are readmitted to the ICU are significantly older and have significantly higher scores that define the severity of disease at the time of admission and discharge of their first ICU stay. The source of admission for the initial ICU stay did not differ (p = 0.055), and the last Glasgow Coma Scale and the last PaO2/FIO2 ratio before discharge from the ICU were higher in patients who did not need a readmission to the ICU. The performance of the Stability and Workload Index for Transfer score is poor with an area under the receiver operator curve of 0.581 (95% CI, 0.556-0.605; p < 0.001). CONCLUSIONS:: Based on the data from our patients, the proposed Stability and Workload Index for Transfer score by Gajic et al is not ideal in aiding the clinician in the decision, if a patient can be discharged safely from the ICU and further research is necessary to define the patients at risk for readmission.

PMID: 23660731 [PubMed - as supplied by publisher]

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May 112013
 

The Influence of Prehospital Systemic Corticosteroid Use on Development of Acute Respiratory Distress Syndrome and Hospital Outcomes.

Crit Care Med. 2013 May 8;

Authors: Karnatovskaia LV, Lee AS, Gajic O, Festic E

Abstract
OBJECTIVE:: The role of systemic corticosteroids in pathophysiology and treatment of acute respiratory distress syndrome is controversial. Use of prehospital systemic corticosteroid therapy may prevent the development of acute respiratory distress syndrome and improve hospital outcomes. DESIGN:: This is a preplanned retrospective subgroup analysis of the prospectively identified cohort from a trial by the U.S. Critical Illness and Injury Trials Group designed to validate the Lung Injury Prediction Score. SETTING:: Twenty-two acute care hospitals. PATIENTS:: Five thousand eighty-nine patients with at least one risk factor for acute respiratory distress syndrome at the time of hospitalization. INTERVENTION:: Propensity-based analysis of previously recorded data. MEASUREMENTS AND MAIN RESULTS:: Three hundred sixty-four patients were on systemic corticosteroids. Prevalence of acute respiratory distress syndrome was 7.7% and 6.9% (odds ratio, 1.1 [95% CI, 0.8-1.7]; p = 0.54) for patients on systemic corticosteroid and not on systemic corticosteroids, respectively. A propensity for being on systemic corticosteroid was derived through logistic regression by using all available covariates. Subsequently, 354 patients (97%) on systemic corticosteroid were matched to 1,093 not on systemic corticosteroid by their propensity score for a total of 1,447 patients in the matched set. Adjusted risk for acute respiratory distress syndrome (odds ratio, 0.96 [95% CI, 0.54-1.38]), invasive ventilation (odds ratio, 0.84 [95% CI, 0.62-1.12]), and in-hospital mortality (odds ratio, 0.97 [95% CI, 0.63-1.49]) was then calculated from the propensity-matched sample using conditional logistic regression model. No significant associations were present. CONCLUSIONS:: Prehospital use of systemic corticosteroid neither decreased the development of acute respiratory distress syndrome among patients hospitalized with at one least risk factor, nor affected the need for mechanical ventilation or hospital mortality.

PMID: 23660730 [PubMed - as supplied by publisher]

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May 112013
 

Clinical Features of Critically Ill Patients With Shiga Toxin-Induced Hemolytic Uremic Syndrome.

Crit Care Med. 2013 May 8;

Authors: Braune SA, Wichmann D, von Heinz MC, Nierhaus A, Becker H, Meyer TN, Meyer GP, Müller-Schulz M, Fricke J, de Weerth A, Hoepker WW, Fiehler J, Magnus T, Gerloff C, Panzer U, Stahl RA, Wegscheider K, Kluge S

Abstract
OBJECTIVE:: In Spring 2011, an unprecedented outbreak of Shiga toxin-producing Escherichia coli serotype O104:H4-associated hemolytic uremic syndrome occurred in Northern Germany. The aim of this study was to describe the clinical characteristics, treatments, and outcomes of critically ill patients with Shiga toxin-producing E. coli-associated hemolytic uremic syndrome during this outbreak. DESIGN, SETTING, AND PATIENTS:: Multicenter, retrospective, observational study of critically ill adult patients with Shiga toxin-producing E. coli-associated hemolytic uremic syndrome in six hospitals in Hamburg, Germany, between May and August 2011. MEASUREMENTS AND MAIN RESULTS:: During the study period, 106 patients with Shiga toxin-producing E. coli-associated hemolytic uremic syndrome were admitted to the ICUs. The median age was 40 years (range, 18-83) with a female:male ratio of 3:1. The median time from onset of clinical symptoms to hospital admission was 3 days and from hospital to ICU admission an additional 3 days. A total of 101 patients (95.3%) had acute renal failure and 78 (73.6%) required renal replacement therapy. Intubation and mechanical ventilation were required in 38 patients (35.8%) and noninvasive ventilation was required in 17 patients (16.0%). The median duration of invasive ventilation was 7 days (range, 1-32 days) and the median ICU stay was 10 days (range, 1-45 days). Fifty-one patients (48.1%) developed sepsis; of these 51 patients, 27 (25.4%) developed septic shock. Seventy patients (66.0%) developed severe neurological symptoms. Ninety-seven patients (91.5%) were treated with plasma exchange and 50 patients (47.2%) received eculizumab (monoclonal anti-C5 antibody). The mortality rate was 4.7%. Mild residual neurological symptoms were present in 21.7% of patients at ICU discharge, and no patient required renal replacement therapy 6 months after ICU admission. CONCLUSIONS:: During the 2011 Shiga toxin-producing E. coli-associated hemolytic uremic syndrome outbreak in Germany, critical illness developed rapidly after hospital admission, often in young women. The infection was associated with severe neurological and renal symptoms, requiring mechanical ventilation and renal replacement therapy in a substantial proportion of patients. Overall, recovery was much better than expected.

PMID: 23660733 [PubMed - as supplied by publisher]

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Apr 182013
 

Mortality After Hospital Discharge in ICU Patients*

Crit Care Med. 2013 May;41(5):1229-1236

Authors: Brinkman S, de Jonge E, Abu-Hanna A, Arbous MS, de Lange DW, de Keizer NF

Abstract
OBJECTIVES:: To assess the mortality risk of ICU patients after hospital discharge and compare it to mortality of the general Dutch population. DESIGN:: Cohort study of ICU admissions from a national ICU registry linked to administrative records from an insurance claims database. SETTING:: Eighty-one Dutch ICUs. PATIENTS:: ICU patients (n = 91,203) who were discharged alive from the hospital between January 1, 2007, and October 1, 2010. INTERVENTIONS:: None. MEASUREMENTS AND MAIN RESULTS:: The unadjusted observed survival was inspected by Kaplan-Meier curves. Mortality risk at 1, 2, and 3 years after hospital discharge was 12.5%, 19.3%, and 27.5%, respectively. The 3-year mortality after hospital discharge in ICU patients was higher than the weighted average of the gender and age-specific death risks of the general Dutch population (27.5% versus 8.2%). The 1-year mortality after hospital discharge was adjusted for case-mix differences by a set of determinants which showed a statistically significant influence on the outcome in a 10-fold cross validation. The elective and cardiac surgical patients have statistically significantly better mortality outcomes (adjusted hazard ratio, 0.73 and 0.28, respectively), whereas medical patients and patients admitted for cancer have statistically significantly worse mortality outcomes (adjusted hazard ratio, 1.41, 1.94, respectively) compared with other ICU patients. Urgent surgery patients and patients with a subarachnoid hemorrhage, trauma, acute renal failure, or severe community-acquired pneumonia did not differ statistically from the other ICU patients after adjustment for case-mix differences. CONCLUSIONS:: In-hospital mortality underestimates the true mortality of ICU patients as the mortality in the first months after hospital discharge is substantial. Most ICU patients still have an increased mortality risk in the subsequent years after hospital discharge compared with the general Dutch population. The mortality after hospital discharge differs widely between ICU subgroups. Future studies should focus on the analysis of mortality after hospital discharge that is attributable to the former ICU admission.

PMID: 23591209 [PubMed - as supplied by publisher]

Link to Article at PubMed

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