Unselected Intensive Care Unit Research Articles

Oxygen extraction–guided transfusion strategy in critically ill patients: study protocol for a randomised, open-labelled, controlled trial

IntroductionIn critically ill patients, individualised strategies for red blood cell transfusion (RBCT) are lacking. The objective of this study is to demonstrate the potential advantages of employing an individualised transfusion...

Acute kidney injury in intensive care patients: Incidence, time course, and risk factors.

BackgroundAcute kidney injury (AKI) is frequent and influences the prognosis of intensive care unit (ICU) patients. The aim of this study was to estimate the incidence, time‐course, risk factors, and mortality of AKI among unselected ICU patients.MethodsAll adult ICU patients admitted to the ICU at the University Hospital in Central Norway from 2010 to 2015 with a stay of 24 h or more were included in the study. AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. All patients were followed with respect to reversal of AKI. Risk factors for AKI were analyzed using Cox regression.ResultsAmong 2325 ICU patients, 1245 developed AKI during the ICU stay, corresponding to an incidence of 53.5 % (CI, 51.5–55.5). The incidence according to KDIGO AKI stages 1, 2, and 3 was 26.2, 11.7, and 15.7%, respectively. The median duration of AKI was 24 (CI 19–24), 32 (CI 26–39), and 101 (CI 75–164) hours for AKI KDIGO stage 1, 2, and 3, respectively. AKI was transient, persistent, or AKD in 73.4, 16.5, and 10.0% of the patients with a known outcome. AKI reversal was observed in 72.9% of all AKI patients. Independent risk factors for AKI in a multivariate analysis were hypertension, diabetes, heart disease, and higher body weight. Episodes of mean arterial pressure below 73 mmHg were associated with a higher risk of AKI.ConclusionsIn our material, the incidence of AKI was comparable to what has been reported previously. Risk factors for the development of AKI were a MAP below 73, hypertension, diabetes, heart disease, chronic kidney disease, and higher body weight. Most AKI patients regain their kidney function during the ICU stay, particularly in the KDIGO AKI stages 1 and 2.

A Comparison between Endostatin and Conventional Biomarkers on 30-Day Mortality and Renal Replacement Therapy in Unselected Intensive Care Patients.

Endostatin may predict mortality and kidney impairment in general populations as well as in critically ill patients. We decided to explore the possible role of endostatin as a predictor of 30-day mortality, acute kidney injury (AKI), and renal replacement therapy (RRT) in a cohort of unselected intensive care unit (ICU) patients. Endostatin and creatinine in plasma were analyzed and SAPS3 was determined in 278 patients on ICU arrival at admission to a Swedish medium-sized hospital. SAPS3 had the highest predictive value, 0.85 (95% C.I.: 0.8–0.90), for 30-day mortality. Endostatin, in combination with age, predicted 30-day mortality by 0.76 (95% C.I.: 0.70–0.82). Endostatin, together with age and creatinine, predicted AKI with 0.87 (95% C.I.: 0.83–0.91). Endostatin predicted AKI with [0.68 (0.62–0.74)]. Endostatin predicted RRT, either alone [0.82 (95% C.I.: 0.72–0.91)] or together with age [0.81 (95% C.I.: 0.71–0.91)]. The predicted risk for 30-day mortality, AKI, or RRT during the ICU stay, predicted by plasma endostatin, was not influenced by age. Compared to the complex severity score SAPS3, circulating endostatin, combined with age, offers an easily managed option to predict 30-day mortality. Additionally, circulating endostatin combined with creatinine was closely associated with AKI development.

Systematic review of diagnostic methods for acute respiratory distress syndrome.

RationaleAcute respiratory distress syndrome (ARDS) is currently diagnosed by the Berlin definition, which does not include a direct measure of pulmonary oedema, endothelial permeability or pulmonary inflammation. We hypothesised that biomarkers of these processes have good diagnostic accuracy for ARDS.MethodsMedline and Scopus were searched for original diagnostic studies using minimally invasive testing. Primary outcome was the diagnostic accuracy per test and was categorised by control group. The methodological quality was assessed with QUADAS-2 tool. Biomarkers that had an area under the receiver operating characteristic curve (AUROCC) of >0.75 and were studied with minimal bias against an unselected control group were considered to be promising.ResultsForty-four articles were included. The median AUROCC for all evaluated tests was 0.80 (25th to 75th percentile: 0.72–0.88). The type of control group influenced the diagnostic accuracy (p=0.0095). Higher risk of bias was associated with higher diagnostic accuracy (AUROCC 0.75 for low-bias, 0.77 for intermediate-bias and 0.84 for high-bias studies; p=0.0023). Club cell protein 16 and soluble receptor for advanced glycation end-products in plasma and two panels with biomarkers of oxidative stress in breath showed good diagnostic accuracy in low-bias studies that compared ARDS patients to an unselected intensive care unit (ICU) population.ConclusionThis systematic review revealed only four diagnostic tests fulfilling stringent criteria for a promising biomarker in a low-bias setting. For implementation into the clinical setting, prospective studies in a general unselected ICU population with good methodological quality are needed.

Neurally Adjusted Ventilatory Assist in Difficult Weaning: Promising Findings on a Prickly Issue.

Neurally Adjusted Ventilatory Assist in Difficult Weaning: Promising Findings on a Prickly Issue.

Lactate indices as predictors of in-hospital mortality or 90-day survival after admission to an intensive care unit in unselected critically ill patients.

BackgroundWe performed an exclusive study to investigate the associations between a total of 23 lactate-related indices during the first 24h in an intensive care unit (ICU) and in-hospital mortality.MethodsNine static and 14 dynamic lactate indices, including changes in lactate concentrations (Δ Lac) and slope (linear regression coefficient), were calculated from individual critically ill patient data extracted from the Multiparameter Intelligent Monitoring for Intensive Care (MIMIC) III database.ResultsData from a total of 781 ICU patients were extracted, consisted of 523 survivors and 258 non-survivors. The in-hospital mortality rate for this cohort was 33.0%. A multivariate logistic regression model identified maximal lactate concentration at 24h after ICU admission (max lactate at T24) as a significant predictor of in-hospital mortality (odds ratio = 1.431, 95% confidence interval [CI] = 1.278–1.604, p<0.001) after adjusting for predefined confounders (age, gender, sepsis, Elixhauser comorbidity score, mechanical ventilation, renal replacement therapy, vasopressors, ICU severity scores). Area under curve (AUC) for max lactate at T24 was larger (AUC = 0.776, 95% CI = 0.740–0.812) than other indices (p<0.001), comparable to an APACHE III score of 0.771. When combining max lactate at T24 with APACHE III, the AUC was increased to 0.815 (95% CI:0.783–0.847). The sensitivity, specificity, and positive and negative predictive values for the cut-off value of 3.05 mmol/L were 64.3%, 77.4%, 58.5%, and 81.5%, respectively.Kaplan-Myer survival curves of the max lactate at T24 for 90-day survival after admission to ICU demonstrated a significant difference according to the cut-off value (p<0.001).ConclusionsThese data indicate that the maximal arterial lactate concentration at T24 is a robust predictor of in-hospital mortality as well as 90-day survival in unselected ICU patients with predictive ability as comparable with APACHE III score.

Tracheostomy in the ICU: hope or delusion?

Introduction: Current literature suggests that tracheostomy has no impact on survival in unselected intensive care unit (ICU) patients, and that it actually transfers mortality from ICU to the ward. Methods: Data from 71 adult subjects who underwent tracheostomy as part of their ICU management and were subsequently transferred to the ward were obtained retrospectively. Results: During 2015, 104 subjects received tracheostomy. Thirty-two died during their initial ICU admission (30.4%) and were excluded from analysis. Of the remaining 73 individuals, 28 died (38.3%) in hospital. Most common diagnoses were sepsis (33.8%) and neurological emergencies (23.9%). Life-sustaining treatments were withheld or withdrawn in 25 decedents. Seven subjects died in later hospitalizations at our institution over the period recorded. Conclusions: Tracheostomy may represent a burden after ICU discharge, involving high resource use and low survival rate. Efforts should be made to recognize patients who might clearly benefit from this technique to avoid unwanted prolonged mechanical ventilation. Keywords: Tracheostomy; critical illness; decision-making

Factors determining outcomes in adult patient undergoing mechanical ventilation: A "real-world" retrospective study in an Indian Intensive Care Unit.

Background:Characteristics of patients admitted to intensive care units with respiratory failure (RF) and undergoing mechanical ventilation (MV) have been described for particular indications and diseases, but there are few studies in the general Intensive Care Unit (ICU) population and even lesser from developing countries.Objective:This study aims to study clinical characteristics, outcomes, and factors affecting outcomes in adult patients with RF on MV admitted to ICU.Methods:A retrospective study of medical records of all patients admitted to ICU between January 1, 2015, and March 31, 2016. Patients receiving MV for more than 6 h were included in the study. Patients younger than 12 years were excluded. Data were recorded of all patients receiving MV during this period regarding demographics, indications for MV, type and characteristics of ventilation, concomitant complications and treatment, and outcomes. Data were recorded at the initiation of MV and daily all throughout the course of MV. The main outcome measure was all-cause mortality at the end of ICU stay.Results:Of the 500 patients admitted to the ICU during the period of the study, a total of 122 patients received MV (and were included in study) for mean (standard deviation [SD]) duration of 4 (3.4) days. The mean (SD) stay in ICU and hospital was 4.49 (3.52) and 6.4 (3.6), respectively. Overall mortality for the unselected general ICU patients on MV was 67.21% while that for ARDS patients was 76.1%. The main factors independently associated with increased mortality were (i) pre-MV factors: age, Apache II scores, heart failure (odds ratio [OR], 1.42; 95% confidence interval [CI], 0.54–3.73; P < 0.001); (ii) patient management factors: positive end-expiratory pressure (OR, 2.69; 95% CI, 0.84–8.61; P < 0.001); (iii) Factors occurring over the course of MV: PaO2/FiO2 ratio < 100 (OR, 1.66; 95% CI, 0.67–4.11; P < 0.001) and development of renal failure (OR, 2.33; 95% CI, 2.05–2.42; P < 0.001) and hepatic failure (OR, 2.07; 95% CI, 1.91–2.24; P < 0.001) after initiation of MV.Conclusions:Outcomes of patients undergoing MV are dependent on various factors (including patient demographics, nature of associated morbidity, characteristics of the MV received, and conditions developing over course of MV) and these factors may be present before or develop after initiation of MV.

Extended-spectrum beta-lactamase--producing enterobacteriaceae in the intensive care unit: acquisition does not mean cross-transmission.

BackgroundIn intensive care unit (ICU), infection and colonization by resistant Gram-negative bacteria increase costs, length of stay and mortality. Extended-spectrum beta-lactamase − producing Enterobacteriaceae (ESBL-E) is a group of pathogens increasingly encountered in ICU setting. Conditions that promote ESBL-E acquisition are not completely understood. The increasing incidence of infections related to ESBL-E and the unsolved issues related to ESBL-E cross-transmission, prompted us to assess the rates of referred and acquired cases of ESBL-E in ICU and to assess patient-to-patient cross-transmission of ESBL-E using a multimodal microbiological analysis.MethodsDuring a 5-month period, all patients admitted to a medical ICU were tested for ESBL-E carriage. A rectal swab was performed at admission and then twice a week until discharge or death. ESBL-E strains were analyzed according to antibiotic susceptibility pattern, rep-PCR (repetitive-element Polymerase chain reaction) chromosomal analysis, and plasmid PCR (Polymerase chain reaction) analysis of ESBL genes. Patient-to-patient transmission was deemed likely when 2 identical strains were found in 2 patients hospitalized simultaneously in the ICU.ResultsAmong the 309 patients assessed for ESBL-E carriage on admission, 25 were found to carry ESBL-E (importation rate: 8 %). During follow-up, acquisition was observed among 19 of them (acquisition rate: 6.5 %). Using the multimodal microbiological approach, we found only one case of likely patient-to-patient ESBL-E transmission.ConclusionsIn unselected ICU patients, we found rather low rates of ESBL-E referred and acquired cases. Only 5 % of acquisitions appeared to be related to patient-to-patient transmission. These data highlight the importance of jointly analyzing phenotypic profile and molecular data to discriminate strains of ESBL-E.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-016-1489-z) contains supplementary material, which is available to authorized users.

The association between the neutrophil-to-lymphocyte ratio and mortality in critical illness: an observational cohort study.

IntroductionThe neutrophil-to-lymphocyte ratio (NLR) is a biological marker that has been shown to be associated with outcomes in patients with a number of different malignancies. The objective of this study was to assess the relationship between NLR and mortality in a population of adult critically ill patients.MethodsWe performed an observational cohort study of unselected intensive care unit (ICU) patients based on records in a large clinical database. We computed individual patient NLR and categorized patients by quartile of this ratio. The association of NLR quartiles and 28-day mortality was assessed using multivariable logistic regression. Secondary outcomes included mortality in the ICU, in-hospital mortality and 1-year mortality. An a priori subgroup analysis of patients with versus without sepsis was performed to assess any differences in the relationship between the NLR and outcomes in these cohorts.ResultsA total of 5,056 patients were included. Their 28-day mortality rate was 19%. The median age of the cohort was 65 years, and 47% were female. The median NLR for the entire cohort was 8.9 (interquartile range, 4.99 to 16.21). Following multivariable adjustments, there was a stepwise increase in mortality with increasing quartiles of NLR (first quartile: reference category; second quartile odds ratio (OR) = 1.32; 95% confidence interval (CI), 1.03 to 1.71; third quartile OR = 1.43; 95% CI, 1.12 to 1.83; 4th quartile OR = 1.71; 95% CI, 1.35 to 2.16). A similar stepwise relationship was identified in the subgroup of patients who presented without sepsis. The NLR was not associated with 28-day mortality in patients with sepsis. Increasing quartile of NLR was statistically significantly associated with secondary outcome.ConclusionThe NLR is associated with outcomes in unselected critically ill patients. In patients with sepsis, there was no statistically significant relationship between NLR and mortality. Further investigation is required to increase understanding of the pathophysiology of this relationship and to validate these findings with data collected prospectively.Electronic supplementary materialThe online version of this article (doi:10.1186/s13054-014-0731-6) contains supplementary material, which is available to authorized users.

P147: Relationship between serum cystatin C level and prognosis in unselected ICU elderly patients

Objective: To study the relationship between the serum Cystatin C (Cys C) level and the prognosis of unselected ICU elderly patients admitted to intensive care unit (ICU). Methods: A total of 531 consecutive patients were screened for eligibility and followed up during their ICU stay. We collected each patient's baseline characteristics, including the Acute Physiology and Chronic Health Evaluation II (APACHEII) score and N-terminal pro-brain natriuretic peptide (NTproBNP), C-reactive protein (CRP) and Cys C levels. The primary outcome was ICU mortality in elderly patients. Multivariate logistic regression analysis was used to determine independent predictors of ICU mortality in elderly patients. We also evaluated the ability of Cys C and NT-proBNP together with APACHE-Ⅱ score to predict ICU mortality in elderly patients by calculation of net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices. Results: Multiple regression analysis revealed that Cys C level, APACHE-II score, NT-proBNP level and CRP level could independently predict primary outcome in unselected ICU Elderly Patients. APACHE-II had the greatest power to predict ICU mortality, as suggested by the largest area under the curve (AUC) of (0.784±0.020). The AUC for CRP level was less than that for NT-proBNP level (0.684±0.027) but greater than that for Cys C level (0.614±0.026) . The addition of Cys C level and NT-proBNP level to APACHE II score gave an NRI of 21.99% (p＜0.01) and an IDI of 8.12% (p＜0.01). The addition of Cys C to the APACHE-II score can obviously increase Cox & Snell R2 and Nagelkerke R2. IDI and NRI were statistically significant in higheGFR patients. Conclusion: In unselected ICU elderly patients, Cys C was an independent predictor of ICU mortality. The addition of Cys C level and NT-proBNP level to the APACHE-Ⅱ score could significantly improve the ability to predict ICU mortality in unselected ICU elderly patients. Cys C appeared to be more useful for predicting ICU outcomes in elderly patients with high eGFR.

Urine output on ICU entry is associated with hospital mortality in unselected critically ill patients

Urine output (UO) is routinely measured in the intensive care unit (ICU) but its prognostic value remains debated. The study aimed to investigate the association between day 1 UO and hospital mortality. Clinical data were abstracted from the Multiparameter Intelligent Monitoring in Intensive Care II (version 2.6) database. UO was recorded for the first 24h after ICU entry, and was classified into three categories: UO >0.5, 0.3-0.5 and ≤0.3ml/kg per hour. The primary endpoint was the hospital mortality. Four models were built to adjust for the hazards ratio of mortality. A total of 21,207 unselected ICU patients including 2,401 non-survivors and 18,806 survivors were included (mortality rate 11.3%). Mortality rate increased progressively across UO categories: >0.5 (7.67%), 0.3-0.5 (11.27%) and ≤0.3ml/kg/h (18.29%), and this relationship remained statistically significant after rigorous control of confounding factors with the Cox proportional hazards regression model. With UO >0.5 as the referent group, the hazards ratios for UO 0.3-0.5 and UO ≤0.3 were 1.41 (95% CI 1.29-1.54) and 1.52 (95% CI 1.38-1.67), respectively. UO obtained on ICU entry is an independent predictor of mortality irrespective of diuretic use. It would be interesting to examine whether strategies to increase UO would improve clinical outcome.

Effect of Timing of Tracheotomy on Clinical Outcomes: an Update Meta-analysis Including 11 Trials

To estimate the relative effect of early vs. late tracheotomy on clinical end-points in unselected intensive care unit (ICU) patients undergoing mechanical ventilation. We searched electronic databases (up to February 27, 2013) for both randomized control trials and observational studies satisfying the predefined inclusion criteria. We retrieved 11 reports of studies including a total of 13 705 patients. Early tracheotomy was associated with significant reductions in mortality [33.3% vs. 36.3%; relative risk (RR); 0.92; 95% confidence interval (CI): 0.88, 0.97; I(2): 29%], length of ICU stay (mean difference: -6.55 days; 95% CI: -8.19, -4.90; I(2): 98%) and duration of mechanical ventilation (mean difference: -6.53 days; 95% CI: -11.43, -1.63; I(2): 100%). However, as compared with late tracheotomy, early tracheotomy did not reduce the incidence of hospital pneumonia (21.9% vs. 21.0%, RR: 0.85; 95% CI: 0.68, 1.06; I(2): 67%). Early tracheotomy can reduce length of ICU stay, duration of mechanical ventilation and mortality but has no influence on hospital pneumonia when compared with late tracheotomy. Once the decision has been made about tracheotomy, clinical physicians should not hesitate to perform the procedure.

Combination Biomarkers to Diagnose Sepsis in the Critically Ill Patient

Although the outcome of sepsis benefits from the prompt administration of appropriate antibiotics on correct diagnosis, the assessment of infection in critically ill patients is often a challenge for clinicians. In this setting, simple biomarkers, especially when used in combination, could prove useful. To determine the usefulness of combination biomarkers to diagnose sepsis. Three hundred consecutive patients were enrolled to construct a biologic score that was next validated in an independent prospective cohort of 79 critically ill patients from another center. Plasma concentrations of soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) and procalcitonin (PCT) were assayed, and the expression of the high-affinity immunoglobulin-Fc fragment receptor I (FcγRI) CD64 on neutrophils (polymorphonuclear [PMN] CD64 index) in flow cytometry was measured. A "bioscore" combining these biomarkers was constructed. Serum concentrations of PCT and sTREM-1 and the PMN CD64 index were higher in patients with sepsis compared with all others (P < 0.001 for the three markers). These biomarkers were all independent predictors of infection, the best receiver-operating characteristic curve being obtained for the PMN CD64 index. The performance of the bioscore, better than that of each individual biomarker, was externally confirmed in the validation cohort. This prospective study, including inceptive and validation cohorts of unselected intensive care unit patients, demonstrates the high performance of a bioscore combining the PMN CD64 index together with PCT and sTREM-1 serum levels in diagnosing sepsis in the critically ill patient.

Utile or futile: biomarkers in the ICU

Biomarkers complement other clinical information by proving quantitative data regarding a pathophysiological mechanism that can be used for the early diagnosis of a specific disease, to monitor and guide treatment, and to predict the risk of death or other adverse events. The stronger the link between the information provided by the biomarker and the immediate clinical course of action that we physicians take in response, the higher the clinical utility of the biomarker. This link is weakest for prognostic biomarkers applied in patients with a wide variety of diseases, such as in unselected intensive care unit (ICU) patients. Although the added value on top of current ICU mortality scores seems to be too low to justify clinical use, the observation that hemodynamic cardiac stress and inflammation are present in multiple conditions provides important insights into the pathophysiology of common disorders in the ICU.

Do simple ventilation and gas exchange measurements predict early successful weaning from respiratory support in unselected general intensive care patients?

BackgroundThe value of respiratory variables as weaning predictors in the intensive care unit (ICU) is controversial. We evaluated the ability of tidal volume (Vtexp), respiratory rate (f), minute volume (MVexp), rapid shallow breathing index (f/Vt), inspired–expired oxygen concentration difference [(I–E)O2], and end-tidal carbon dioxide concentration (Pe′co2) at the end of a weaning trial to predict early weaning outcomes. MethodsSeventy-three patients who required >24 h of mechanical ventilation were studied. A controlled pressure support weaning trial was undertaken until 5 cm H2O continuous positive airway pressure or predefined criteria were reached. The ability of data from the last 5 min of the trial to predict whether a predefined endpoint indicating discontinuation of ventilator support within the next 24 h was evaluated. ResultsPre-test probability for achieving the outcome was 44% in the cohort (n=32). Non-achievers were older, had higher APACHE II and organ failure scores before the trial, and higher baseline arterial H+ concentrations. The Vt, MV, f, and f/Vt had no predictive power using a range of cut-off values or from receiver operating characteristic (ROC) analysis. The [I–E]O2 and Pe′co2 had weak discriminatory power [area under the ROC curve: [I–E]O2 0.64 (P=0.03); Pe′co2 0.63 (P=0.05)]. Using best cut-off values for [I–E]O2 of 5.6% and Pe′co2 of 5.1 kPa, positive and negative likelihood ratios were 2 and 0.5, respectively, which only changed the pre- to post-test probability by about 20%. ConclusionsIn unselected ICU patients, respiratory variables predict early weaning from mechanical ventilation poorly.

Development and validation of a questionnaire for quantitative assessment of perceived discomforts in critically ill patients

To develop and validate the IPREA (Inconforts des Patients de REAnimation) questionnaire for the assessment of discomfort perceived by patients related to their intensive care unit (ICU) stay. This was a two step-study comprising a phase of item generation conducted in one ICU and a phase of psychometric evaluation during a multicenter prospective cohort study in 14 ICUs. Patients were unselected consecutive adult surviving ICU patients. On the day of ICU discharge, a nurse asked patients to rate the severity of 16 discomfort sources, from 0 to 100. Ten percent of patients were randomly chosen to be questioned again to assess the reproducibility. Of 1,380 eligible patients, 1,113 survived and 868 patients could be questioned. The highest scores were for sleep deprivation (35 ± 33), being restrained by tubing, wires, and cables (33 ± 30), pain (32 ± 30), and thirst (32 ± 34). No multidimensional structure was identified. The mean overall score of discomfort was 22 ± 14. Internal consistency was satisfactory using Cronbach's alpha coefficient (0.78). The test-retest reliability study found average measure intraclass correlations ranging from 0.70 to 0.92. The mean duration of the questionnaire administration was 10 ± 7 min. The psychometric properties and acceptability of the IPREA questionnaire make it a potential instrument for measuring discomfort perceived by unselected ICU patients.

A comparison of three methods to estimate baseline creatinine for RIFLE classification

A pre-morbid 'baseline' creatinine is required in order to diagnose and stage acute kidney injury (AKI) using the RIFLE classification. Estimation of baseline creatinine by solving the Modification of Diet in Renal Disease (MDRD) equation assuming a glomerular filtration rate of 75 ml/min/1.73 m(2) has been widely used but never validated. We analysed four cohorts of intensive care unit (ICU) patients from three centres (two from Pittsburgh and one from Mayo and Austin). Three cohorts consisted of preselected patients without AKI (Pittsburgh 1 n = 1048, Mayo n = 737, Austin n = 333), and measured creatinine values in these cohorts were taken to represent baseline creatinine values. The last cohort (Pittsburgh 2 n = 468) consisted of unselected ICU patients with baseline creatinine values recorded within 1 year before ICU admission. Using the Pittsburgh 1 cohort, we derived an equation using the same anthropometric variables as the MDRD equation: baseline creatinine = 0.74 - 0.2 (if female) + 0.08 (if black) + 0.003 × age (in years). We then compared measured creatinine in the Mayo and Austin cohorts and recorded creatinine in the Pittsburgh 2 cohort to the estimated creatinine from: (i) the MDRD equation; (ii) our new equation; (iii) a gender-fixed creatinine of 0.8 mg/dl for females and 1.0 mg/dl for males. Using any of the three methods, the median absolute error of the estimates was of the order of 0.1-0.2 mg/dl, and overall accuracy was similar. When the definition of AKI was limited to the severity grades of Injury and Failure, all three methods were able to generate 78-90% reliable results for preselected normal range cohorts, and 63-70% for the unselected cohort of ICU patients. Estimates of incidence of AKI in the critically ill using RIFLE classification can be affected by the bias and limited accuracy of methods to estimate baseline creatinine. Whenever possible, recorded creatinine values should be used as a reference of baseline. The use of the MDRD equation to estimate baseline creatinine when it is unknown may over- or underestimate some mild (Risk) AKI cases but is unlikely to misclassify patients in Injury and Failure.

Effect of oral beta-blocker on short and long-term mortality in patients with acute respiratory failure: results from the BASEL-II-ICU study

IntroductionAcute respiratory failure (ARF) is responsible for about one-third of intensive care unit (ICU) admissions and is associated with adverse outcomes. Predictors of short- and long-term outcomes in unselected ICU-patients with ARF are ill-defined. The purpose of this analysis was to determine predictors of in-hospital and one-year mortality and assess the effects of oral beta-blockers in unselected ICU patients with ARF included in the BASEL-II-ICU study.MethodsThe BASEL II-ICU study was a prospective, multicenter, randomized, single-blinded, controlled trial of 314 (mean age 70 (62 to 79) years) ICU patients with ARF evaluating impact of a B-type natriuretic peptide- (BNP) guided management strategy on short-term outcomes.ResultsIn-hospital mortality was 16% (51 patients) and one-year mortality 41% (128 patients). Multivariate analysis assessed that oral beta-blockers at admission were associated with a lower risk of both in-hospital (HR 0.33 (0.14 to 0.74) P = 0.007) and one-year mortality (HR 0.29 (0.16 to 0.51) P = 0.0003). Kaplan-Meier analysis confirmed the lower mortality in ARF patients when admitted with oral beta-blocker and further shows that the beneficial effect of oral beta-blockers at admission holds true in the two subgroups of patients with ARF related to cardiac or non-cardiac causes. Kaplan-Meier analysis also shows that administration of oral beta-blockers before hospital discharge gives striking additional beneficial effects on one-year mortality.ConclusionsEstablished beta-blocker therapy appears to be associated with a reduced mortality in ICU patients with acute respiratory failure. Cessation of established therapy appears to be hazardous. Initiation of therapy prior to discharge appears to confer benefit. This finding was seen regardless of the cardiac or non-cardiac etiology of respiratory failure.Trial registrationclinicalTrials.gov Identifier: NCT00130559

Long-term outcome and quality-adjusted life years after severe sepsis*

To study long-term mortality, quality of life (QOL), quality-adjusted life years (QALYs), and costs per QALY in an unselected intensive care unit (ICU) patient population with severe sepsis. Prospective observational cohort study. Twenty-four ICUs in Finland. A total of 470 adult patients with severe sepsis who were treated in ICUs between November 1, 2004 and February 28, 2005. The QOL before critical illness was assessed in 252 patients and QOL after severe sepsis in 156 patients (58% of the patients surviving in April 30, 2006). Ninety-eight patients responded to both questionnaires. QOL was assessed by a generic EuroQol-5D (EQ-5D) measurement with summary index (EQsum) and visual analogue scale (VAS). The 2-year mortality after severe sepsis was 44.9% (211 of 470). The median response time for QOL assessment after severe sepsis was 17 months (interquartile range [IQR] 16-18). The median EQsum (75, IQR 56-92) and EQ VAS (66, IQR 50-80) were lower after severe sepsis than age- and sex-adjusted reference values (p < 0.001 and p < 0.001). The decrease between the mean EQsum reference value and that of severe sepsis patients was 12 (95% confidence interval [CI], 9-16). The difference between the mean EQ VAS reference values and the mean EQ VAS was 8 (95% CI, 5-11). The mean calculated QALYs after severe sepsis were 10.9 (95% CI, 9.7-12.1) and the calculated cost for one QALY was only 2139 [Euro sign] for all survivors and nonsurvivors. Two-year mortality after severe sepsis was high (44.9%) and the QOL was lower after severe sepsis than before critical illness as assessed by EQ-5D. However, the mean QALYs for the surviving patients were reasonable and the cost for one QALY was reasonably low, which makes intensive care in patients with severe sepsis cost effective.