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Mieke Carlier,
Sofie Carrette,
Jason A Roberts,
Veronique Stove,
Alain G Verstraete,
Eric Hoste, Johan Decruyenaere,
Pieter Depuydt,
Jeffrey Lipman,
Steven C Wallis,
Jan J De Waele
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ABSTRACT: INTRODUCTION: Correct antibiotic dosing remains a challenge for the clinician. The aim of this study was to assess the influence of augmented renal clearance on pharmacokinetic/pharmacodynamic target attainment in critically ill patients receiving meropenem or piperacillin/tazobactam, administered as an extended infusion. METHODS: This was a prospective, observational, pharmacokinetic study executed at the medical and surgical intensive care unit at a large academic medical center. Elegible patients were adult patients without renal dysfunction receiving meropenem or piperacillin/tazobactam as an extended infusion. Serial blood samples were collected to describe the antibiotic pharmacokinetics. Urine samples were taken from a 24-hour collection to measure creatinine clearance. Relevant data were drawn from the electronic patient file and the intensive care information system. RESULTS: We obtained data from 61 patients and observed extensive pharmacokinetic variability. Forty-eight percent of the patients did not achieve the desired pharmacokinetic/pharmacodynamic target (100 % fT>MIC), of which almost 80 % had a measured creatinine clearance > 130 mL/min. Multivariate logistic regression demonstrated that high creatinine clearance was an independent predictor of not achieving the pharmacokinetic/pharmacodynamic target. Seven out of nineteen patients (37 %) displaying a creatinine clearance > 130 ml/min did not achieve the minimum pharmacokinetic/pharmacodynamic target of 50 % fT>MIC. CONCLUSIONS: In this large patient cohort, we observed significant variability in pharmacokinetic/pharmacodynamic target attainment in critically ill patients. A large proportion of the patients without renal dysfunction, most of whom displayed a creatinine clearance > 130 mL/min, did not achieve the desired pharmacokinetic/pharmacodynamic target, even with the use of alternative administration methods. Consequently, these patients may be at risk for treatment failure without dose up-titration.
Critical care (London, England) 05/2013; 17(3):R84. · 4.61 Impact Factor
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ABSTRACT: Objective: Time series often appear in medical databases, but only few machine learning methods exist that process this kind of data properly. Most modeling techniques have been designed with a static data model in mind and are not suitable for coping with the dynamic nature of time series. Recurrent neural networks (RNNs) are often used to process time series, but only a few training algorithms exist for RNNs which are complex and often yield poor results. Therefore, researchers often turn to traditional machine learning approaches, such as support vector machines (SVMs), which can easily be set up and trained and combine them with feature extraction (FE) and selection (FS) to process the high-dimensional temporal data. Recently, a new approach, called echo state networks (ESNs), has been developed to simplify the training process of RNNs. This approach allows modeling the dynamics of a system based on time series data in a straight forward way.
The objective of this study is to explore the advantages of using ESN instead of other traditional classifiers combined with FE and FS in classification problems in the intensive care unit (ICU) when the input data consists of time series. While ESNs have mostly been used to predict the future course of a time series, we use the ESN model for classification instead. Although time series often appear in medical data, little medical applications of ESNs have been studied yet.
Methods and material: ESN is used to predict the need for dialysis between the fifth and tenth day after admission in the ICU. The input time series consist of measured diuresis and creatinine values during the first 3days after admission. Data about 830 patients was used for the study, of which 82 needed dialysis between the fifth and tenth day after admission. ESN is compared to traditional classifiers, a sophisticated and a simple one, namely support vector machines and the naive Bayes (NB) classifier. Prior to the use of the SVM and NB classifier, FE and FS is required to reduce the number of input features and thus alleviate the curse dimensionality. Extensive feature extraction was applied to capture both the overall properties of the time series and the correlation between the different measurements in the time series. The feature selection method consists of a greedy hybrid filter-wrapper method using a NB classifier, which selects in each iteration the feature that improves prediction the best and shows little multicollinearity with the already selected set. Least squares regression with noise was used to train the linear readout function of the ESN to mitigate sensitivity to noise and overfitting. Fisher labeling was used to deal with the unbalanced data set. Parameter sweeps were performed to determine the optimal parameter values for the different classifiers. The area under the curve (AUC) and maximum balanced accuracy are used as performance measures. The required execution time was also measured.
Results: The classification performance of the ESN shows significant difference at the 5% level compared to the performance of the SVM or the NB classifier combined with FE and FS. The NB+FE+FS, with an average AUC of 0.874, has the best classification performance. This classifier is followed by the ESN, which has an average AUC of 0.849. The SVM+FE+FS has the worst performance with an average AUC of 0.838. The computation time needed to pre-process the data and to train and test the classifier is significantly less for the ESN compared to the SVM and NB.
Conclusion: It can be concluded that the use of ESN has an added value in predicting the need for dialysis through the analysis of time series data. The ESN requires significantly less processing time, needs no domain knowledge, is easy to implement, and can be configured using rules of thumb.
Engineering Applications of Artificial Intelligence 03/2013; 26(3):984–996. · 1.66 Impact Factor
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ABSTRACT: Critically ill patients generally receive moxifloxacin intravenously to achieve rapid bacterial killing. An early switch from intravenous to enteral moxifloxacin may be considered because of its good oral bioavailability in healthy volunteers. Since bioavailability may be altered in critically ill patients due to pathophysiological changes, this study aimed to investigate whether enteral moxifloxacin is bioequivalent to intravenous moxifloxacin in such patients. Blood samples were obtained from 4 critically ill patients before and at serial time-points after intravenous and enteral administration. In all patients, lower maximum plasma concentration (C(max)) and area under the plasma concentration-time curve during the 24-h observation period (AUC(24h)) values were observed after enteral administration compared to those after intravenous administration. This resulted in lower C(max)/minimum inhibitory concentration (MIC) and AUC(24h)/MIC values, which are 2 indices predicting the antibacterial efficacy of moxifloxacin. Despite the limited number of subjects, we conclude that a switch from intravenous to enteral moxifloxacin is not recommended in these patients, because the 2 administration forms are not bioequivalent.
Scandinavian Journal of Infectious Diseases 07/2012; 44(11):874-8. · 1.72 Impact Factor
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ABSTRACT: The Intensive Care Unit is a data intensive environment where large volumes of patient monitoring and observational data are daily generated. Today, there is a lack of an integrated clinical platform for automated decision support and analysis. Despite the potential of electronic records for infection surveillance and antibiotic management, different parts of the clinical data are stored across databases in their own formats with specific parameters, making access to all data a complex and time-consuming challenge. Moreover, the motivation behind physicians' therapy decisions is currently not captured in existing information systems. The COSARA research project offers automated data integration and services for infection control and antibiotic management for Ghent University Hospital. The platform not only gathers and integrates all relevant data, it also presents the information visually at the point of care. In this paper, we describe the design and value of COSARA for clinical treatment and infectious diseases monitoring. On the one hand, this platform can facilitate daily bedside follow-up of infections, antibiotic therapies and clinical decisions for the individual patient, while on the other hand, the platform serves as management view for infection surveillance and care quality improvement within the complete ICU ward. It is shown that COSARA is valuable for registration, real-time presentation and management of infection-related and antibiotics data.
Journal of Medical Systems 04/2012; 36(6):3765-75. · 1.13 Impact Factor
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European Journal of Intensive Care Medicine 03/2012; 38(3):528. · 5.17 Impact Factor
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Ruth D Piers,
Elie Azoulay,
Bara Ricou,
Freda Dekeyser Ganz, Johan Decruyenaere,
Adeline Max,
Andrej Michalsen,
Paulo Azevedo Maia,
Radoslaw Owczuk,
Francesca Rubulotta,
Pieter Depuydt,
Anne-Pascale Meert,
Anna K Reyners,
Andrew Aquilina,
Maarten Bekaert,
Nele J Van den Noortgate,
Wim J Schrauwen,
Dominique D Benoit
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ABSTRACT: Clinicians in intensive care units (ICUs) who perceive the care they provide as inappropriate experience moral distress and are at risk for burnout. This situation may jeopardize patient quality of care and increase staff turnover.
To determine the prevalence of perceived inappropriateness of care among ICU clinicians and to identify patient-related situations, personal characteristics, and work-related characteristics associated with perceived inappropriateness of care.
Cross-sectional evaluation on May 11, 2010, of 82 adult ICUs in 9 European countries and Israel. Participants were 1953 ICU nurses and physicians providing bedside care.
Perceived inappropriateness of care, defined as a specific patient-care situation in which the clinician acts in a manner contrary to his or her personal and professional beliefs, as assessed using a questionnaire designed for the study.
Of 1651 respondents (median response rate, 93% overall; interquartile range, 82%-100% [medians 93% among nurses and 100% among physicians]), perceived inappropriateness of care in at least 1 patient was reported by 439 clinicians overall (27%; 95% CI, 24%-29%), 300 of 1218 were nurses (25%), 132 of 407 were physicians (32%), and 26 had missing answers describing job title. Of these 439 individuals, 397 reported 445 situations associated with perceived inappropriateness of care. The most common reports were perceived disproportionate care (290 situations [65%; 95% CI, 58%-73%], of which "too much care" was reported in 89% of situations, followed by "other patients would benefit more" (168 situations [38%; 95% CI, 32%-43%]). Independently associated with perceived inappropriateness of care rates both among nurses and physicians were symptom control decisions directed by physicians only (odds ratio [OR], 1.73; 95% CI, 1.17-2.56; P = .006); involvement of nurses in end-of-life decision making (OR, 0.76; 95% CI, 0.60-0.96; P = .02); good collaboration between nurses and physicians (OR, 0.72; 95% CI, 0.56-0.92; P = .009); and freedom to decide how to perform work-related tasks (OR, 0.72; 95% CI, 0.59-0.89; P = .002); while a high perceived workload was significantly associated among nurses only (OR, 1.49; 95% CI, 1.07-2.06; P = .02). Perceived inappropriateness of care was independently associated with higher intent to leave a job (OR, 1.65; 95% CI, 1.04-2.63; P = .03). In the subset of 69 ICUs for which patient data could be linked, clinicians reported received inappropriateness of care in 207 patients, representing 23% (95% CI, 20%-27%) of 883 ICU beds.
Among a group of European and Israeli ICU clinicians, perceptions of inappropriate care were frequently reported and were inversely associated with factors indicating good teamwork.
JAMA The Journal of the American Medical Association 12/2011; 306(24):2694-703. · 30.03 Impact Factor
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ABSTRACT: Intensive care unit (ICU) patients frequently undergo contrast-enhanced radiographic examinations, which carries a risk for development of contrast-associated acute kidney injury (CA-AKI). Data on this in ICU patients are scarce. The aim of this study was therefore to evaluate the epidemiology and short- and long-term outcomes of CA-AKI in ICU patients.
A retrospective single-centre cohort study covering the period 1 March 2004 to 31 December 2008 on ICU patients who underwent a radiography examination with parenteral administration of iodinated radio contrast media was conducted. Data analysis included univariate and multivariate analyses of patients with and without CA-AKI.
A total of 787 ICU patients were included in the study. CA-AKI occurred in 128 (16.3%) and was associated with higher need for RRT [30 (4.6%) vs. 21 (16.4%), p < 0.001], worse kidney function at discharge, longer length of ICU and hospital stay, and higher 28-day and 1-year mortality [28-day: 86 (13.1%) vs. 46 (35.9%), p < 0.001, and 1-year: 158 (24.0%) vs. 71 (55.5%), p < 0.001]. Higher serum creatinine, lower mean arterial pressure, and administration of diuretics and vasoactive therapy were associated with development of CA-AKI in multivariate analysis. After correction for confounders we found that CA-AKI was associated with 28-day mortality in this cohort of ICU patients (odds ratio = 2.742, 95% confidence interval 1.374-5.471).
CA-AKI occurred in one out of six ICU patients who underwent a contrast-enhanced radiography examination and was associated with both short-and long-term worse outcomes such as need for RRT, worse kidney function at discharge, increased length of stay in the ICU and hospital, and mortality.
European Journal of Intensive Care Medicine 11/2011; 37(12):1921-31. · 5.17 Impact Factor
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ABSTRACT: To evaluate whether a real-time electronic alert system or "AKI sniffer," which is based on the RIFLE classification criteria (Risk, Injury and Failure), would have an impact on therapeutic interventions and acute kidney injury progression.
Prospective intervention study.
Surgical and medical intensive care unit in a tertiary care hospital.
A total of 951 patients having in total 1,079 admission episodes were admitted during the study period (prealert control group: 227, alert group: 616, and postalert control group: 236).
Three study phases were compared: A 1.5-month prealert control phase in which physicians were blinded for the acute kidney injury sniffer and a 3-month intervention phase with real-time alerting of worsening RIFLE class through the Digital Enhanced Cordless Technology telephone system followed by a second 1.5-month postalert control phase.
A total of 2593 acute kidney injury alerts were recorded with a balanced distribution over all study phases. Most acute kidney injury alerts were RIFLE class risk (59.8%) followed by RIFLE class injury (34.1%) and failure (6.1%). A higher percentage of patients in the alert group received therapeutic intervention within 60 mins after the acute kidney injury alert (28.7% in alert group vs. 7.9% and 10.4% in the pre- and postalert control groups, respectively, p μ .001). In the alert group, more patients received fluid therapy (23.0% vs. 4.9% and 9.2%, p μ .01), diuretics (4.2% vs. 2.6% and 0.8%, p μ .001), or vasopressors (3.9% vs. 1.1% and 0.8%, p μ .001). Furthermore, these patients had a shorter time to intervention (p μ .001). A higher proportion of patients in the alert group showed return to a baseline kidney function within 8 hrs after an acute kidney injury alert "from normal to risk" compared with patients in the control group (p = .048).
The real-time alerting of every worsening RIFLE class by the acute kidney injury sniffer increased the number and timeliness of early therapeutic interventions. The borderline significant improvement of short-term renal outcome in the RIFLE class risk patients needs to be confirmed in a large multicenter trial.
Critical care medicine 11/2011; 40(4):1164-70. · 6.37 Impact Factor
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ABSTRACT: Measuring the attributable mortality of ventilator-associated pneumonia (VAP) is challenging and prone to different forms of bias. Studies addressing this issue have produced variable and controversial results.
We estimate the attributable mortality of VAP in a large multicenter cohort using statistical methods from the field of causal inference.
Patients (n = 4,479) from the longitudinal prospective (1997-2008) French multicenter Outcomerea database were included if they stayed in the intensive care unit (ICU) for at least 2 days and received mechanical ventilation (MV) within 48 hours after ICU admission. A competing risk survival analysis, treating ICU discharge as a competing risk for ICU mortality, was conducted using a marginal structural modeling approach to adjust for time-varying confounding by disease severity.
Six hundred eighty-five (15.3%) patients acquired at least one episode of VAP. We estimated that 4.4% (95% confidence interval, 1.6-7.0%) of the deaths in the ICU on Day 30 and 5.9% (95% confidence interval, 2.5-9.1%) on Day 60 are attributable to VAP. With an observed ICU mortality of 23.3% on Day 30 and 25.6% on Day 60, this corresponds to an ICU mortality attributable to VAP of about 1% on Day 30 and 1.5% on Day 60.
Our study on the attributable mortality of VAP is the first that simultaneously accounts for the time of acquiring VAP, informative loss to follow-up after ICU discharge, and the existence of complex feedback relations between VAP and the evolution of disease severity. In contrast to the majority of previous reports, we detected a relatively limited attributable ICU mortality of VAP.
American Journal of Respiratory and Critical Care Medicine 08/2011; 184(10):1133-9. · 11.08 Impact Factor
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ABSTRACT: Acute kidney injury (AKI) is a common complication in patients admitted to the intensive care unit (ICU). Among other variables, serum urea concentrations are recommended for timing of initiation of renal replacement therapy (RRT). The aim of this study was to evaluate whether serum urea concentration or different serum urea concentration cutoffs as recommended in the literature were associated with in-hospital mortality at time of initiation of RRT for AKI.
This is a retrospective single- centre study during a 3-year period (2004-07), in a 44-bed tertiary care centre ICU of adult AKI patients who were treated with RRT.
Three hundred and two patients were included: 68.9% male, median age 65 years and an APACHE II score of 21. The overall in-hospital mortality was 57.9%. Non-survivors were older (67 versus 64 years, P = 0.016) and had a higher APACHE II score (22 versus 20, P < 0.001). At time of initiation of RRT, they were more severely ill and had a lower serum urea concentration compared to survivors (130 versus 141 mg/dL, P = 0.038). Serum urea concentration, as well as the different historical serum urea concentration cut-offs had low area under the curves for the receiver operating characteristic curve for prediction of mortality. In multivariate analysis, age, and at time of initiation of RRT, potassium, SOFA score with exclusion of points for AKI and RIFLE class were associated with mortality, but serum urea concentration and the different cut-offs were not.
This retrospective study suggests that serum urea concentration and serum urea concentration cut-offs at time of initiation of RRT have no predictive value for in-hospital mortality in ICU patients with AKI.
Nephrology Dialysis Transplantation 03/2011; 26(10):3211-8. · 3.40 Impact Factor
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ABSTRACT: The current, place-oriented nurse call systems are very static. A patient can only make calls with a button which is fixed to a wall of a room. Moreover, the system does not take into account various factors specific to a situation. In the future, there will be an evolution to a mobile button for each patient so that they can walk around freely and still make calls. The system would become person-oriented and the available context information should be taken into account to assign the correct nurse to a call.The aim of this research is (1) the design of a software platform that supports the transition to mobile and wireless nurse call buttons in hospitals and residential care and (2) the design of a sophisticated nurse call algorithm. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff members and patients into account. Additionally, the priority of a call probabilistically depends on the risk factors, assigned to a patient.
The ontology-based Nurse Call System (oNCS) was developed as an extension of a Context-Aware Service Platform. An ontology is used to manage the profile information. Rules implement the novel nurse call algorithm that takes all this information into account. Probabilistic reasoning algorithms are designed to determine the priority of a call based on the risk factors of the patient.
The oNCS system is evaluated through a prototype implementation and simulations, based on a detailed dataset obtained from Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls amongst nurses and the assignment of priorities to calls are compared for the oNCS system and the current, place-oriented nurse call system. Additionally, the performance of the system is discussed.
The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the oNCS system significantly improves the assignment of nurses to calls. Calls generally have a nurse present faster and the workload-distribution amongst the nurses improves.
BMC Health Services Research 02/2011; 11:26. · 1.66 Impact Factor
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ABSTRACT: De-escalation of antimicrobial therapy is often advocated to reduce the use of broad-spectrum antibiotics in critically ill patients. However, little data are available on the application of this strategy in daily clinical practice.
This is a retrospective analysis of all meropenem prescriptions in a surgical intensive care unit (ICU) during 1 year. Age, Acute Physiology and Chronic Health Evaluation II score on admission to the ICU, site of infection, causative organism, duration of meropenem administration, other antibiotic prescription for the same infectious episode for which meropenem was administered, and ICU mortality were recorded. De-escalation was defined as the administration of an antibiotic with a narrower spectrum within 3 days of the start of meropenem.
Data from 113 meropenem prescriptions were available for analysis. Pulmonary (46%) and complicated intraabdominal (31%) infections were the most frequent infections. In 37 patients, meropenem was used after identification of a multiresistant gram-negative organism (MRGN), whereas in 76 patients, empirical treatment with meropenem was started. Empirical prescription of meropenem was de-escalated in 42% of the patients. In the majority of the patients in whom de-escalation was not done, no conclusive cultures were available to guide treatment; also, colonization with MRGN at other sites was frequently associated with non-de-escalation. Patients in whom antibiotics were de-escalated had a trend toward a lower mortality rate (7% vs 21%, P = .12).
De-escalation after empirical treatment with meropenem was performed in less than half of the patients. Reasons for not de-escalating included the absence of conclusive microbiology and colonization with MRGN.
Journal of critical care 12/2010; 25(4):641-6. · 2.13 Impact Factor
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ABSTRACT: The computerization of Intensive Care Units provides an overwhelming amount of electronic data for both medical and financial analysis. However, the current tarification, which is the process to tick and count patients' procedures, is still a repetitive, time-consuming process on paper. Nurses and secretaries keep track manually of the patients' medical procedures. This paper describes the design methodology and implementation of automated tarification services. In this study we investigate if the tarification can be modeled in service oriented architecture as a composition of interacting services. Services are responsible for data collection, automatic assignment of records to physicians and application of rules. Performance is evaluated in terms of execution time, cost evaluation and return on investment based on tracking of real procedures. The services provide high flexibility in terms of maintenance, integration and rules support. It is shown that services offer a more accurate, less time-consuming and cost-effective tarification.
Journal of Medical Systems 10/2010; 36(3):1403-16. · 1.13 Impact Factor
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ABSTRACT: Information technology (IT) may improve the quality, safety and efficiency of medicine, and is especially useful in intensive Care Units (ICUs) as these are extremely data-rich environments with round-the-clock changing parameters. However, data regarding the implementation rates of IT in ICUs are scarce, and restricted to non-European countries. The current paper aims to provide relevant information regarding implementation of IT in Flemish ICU's (Flanders, Belgium).
The current study is based on two separate but complementary surveys conducted in the region of Flanders (Belgium): a written questionnaire in 2005 followed by a telephone survey in October 2008. We have evaluated the actual health IT adoption rate, as well as its evolution over a 3-year time frame. In addition, we documented the main benefits and obstacles for taking the decision to implement an Intensive Care Information System (ICIS).
Currently, the computerized display of laboratory and radiology results is almost omnipresent in Flemish ICUs, (100% and 93.5%, respectively), but the computerized physician order entry (CPOE) of these examinations is rarely used. Sixty-five % of Flemish ICUs use an electronic patient record, 41.3% use CPOE for medication prescriptions, and 27% use computerized medication administration recording. The implementation rate of a dedicated ICIS has doubled over the last 3 years from 9.3% to 19%, and another 31.7% have plans to implement an ICIS within the next 3 years. Half of the tertiary non-academic hospitals and all university hospitals have implemented an ICIS, general hospitals are lagging behind with 8% implementation, however. The main reasons for postponing ICIS implementation are: (i) the substantial initial investment costs, (ii) integration problems with the hospital information system, (iii) concerns about user-friendly interfaces, (iv) the need for dedicated personnel and (v) the questionable cost-benefit ratio.
Most ICUs in Flanders use hospital IT systems such as computerized laboratory and radiology displays. The adoption rate of ICISs has doubled over the last 3 years but is still surprisingly low, especially in general hospitals. The major reason for not implementing an ICIS is the substantial financial cost, together with the lack of arguments to ensure the cost/benefit.
BMC Medical Informatics and Decision Making 10/2010; 10:62. · 1.48 Impact Factor
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ABSTRACT: The Intensive Care Unit (ICU) is an extremely data-intensive environment where each patient needs to be monitored 24/7. Bedside monitors continuously register vital patient values (such as serum creatinine, systolic blood pressure) which are recorded frequently in the hospital database (e.g. every 2 min in the ICU of the Ghent University Hospital), laboratories generate hundreds of results of blood and urine samples, and nurses measure blood pressure and temperature up to 4 times an hour. The processing of such large amount of data requires an automated system to support the physicians' daily work. The Intensive Care Service Platform (ICSP) offers the needed support through the development of medical support services for processing and monitoring patients' data. With an increased deployment of these medical support services, reusing existing services as building blocks to create new services offers flexibility to the developer and accelerates the design process. This paper presents a new addition to the ICSP, the Dynamic Composer for Web services. Based on a semantic description of the medical support services, this Composer enables a service to be executed by creating a composition of medical services that provide the needed calculations. The composition is achieved using various algorithms satisfying certain quality of service (QoS) constraints and requirements. In addition to the automatic composition the paper also proposes a recovery mechanism in case of unavailable services. When executing the composition of medical services, unavailable services are dynamically replaced by equivalent services or a new composition achieving the same result. The presented platform and QoS algorithms are put through extensive performance and scalability tests for typical ICU scenarios, in which basic medical services are composed to a complex patient monitoring service.
Computer methods and programs in biomedicine 05/2010; 100(3):248-64. · 1.14 Impact Factor
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ABSTRACT: The main objective of this review was to analyse the prevalence and outcome of acute kidney injury (AKI) in patients with severe burn injury. AKI is a common complication in patients with severe burn injury and one of the major causes of death (often combined with other organ dysfunctions). Several definitions of AKI have been used, but the RIFLE 'consensus' classification is nowadays considered the gold standard, enabling a more objective comparison of populations.
We performed a systematic literature search (1960-2009), involving PubMed, the Web of Science, the search engine Google and textbooks. Reference lists and the Science Citation Index search were also consulted. Attributable mortality was assessed by performing a meta-analysis.
This search yielded 57 articles and abstracts with relevant epidemiologic data of AKI in the burn population. Of these, 30 contained complete mortality data of the burn and control population, which revealed a 3- to 6-fold higher mortality for AKI patients in univariate analysis, depending on the applied definition. When defined by the RIFLE consensus classification, AKI occurred in one quarter of patients with severe burn injury (median mortality of 34.9%), and when defined by the need for renal replacement therapy (RRT), AKI occurred in 3% (median mortality of 80%). The prevalence of AKI slightly increased, but AKI-RRT decreased. However, the outcome in both groups improved.
Despite the wide variation of the analysed burn populations and definitions of AKI, this review clearly showed that AKI remains prevalent and is associated with increased mortality in patients with severe burn injury.
European Journal of Intensive Care Medicine 03/2010; 36(6):915-25. · 5.17 Impact Factor
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ABSTRACT: The appendix contains a description of the standardization efforts and formalisms for representing clinical guidelines that have been proposed in literature, namely the Arden Syntax, PROforma, EON, GLIF, PRODIGY, Asbru and Guide.
BMC Medical Informatics and Decision Making 01/2010; 10(3). · 1.48 Impact Factor
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IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS 2010), Perth, Australia, October 12-15, 2010; 01/2010
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IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS 2010), Perth, Australia, October 12-15, 2010; 01/2010
