Peter M. C. Klein Klouwenberg

Electronic implementation of a novel surveillance paradigm for ventilator-associated events. Feasibility and validation.

RATIONALE Accurate surveillance of ventilator-associated pneumonia (VAP) is hampered by subjective diagnostic criteria. A novel surveillance paradigm for ventilator-associated events (VAEs) was introduced. OBJECTIVES To determine the validity of surveillance using the new VAE algorithm. METHODS Prospective cohort study in two Dutch academic medical centers (2011-2012). VAE surveillance was electronically implemented and included assessment of (infection-related) ventilator-associated conditions (VAC, IVAC) and VAP. Concordance with ongoing prospective VAP surveillance was assessed, along with clinical diagnoses underlying VAEs and associated mortality of all conditions. Consequences of minor differences in electronic VAE implementation were evaluated. MEASUREMENTS AND MAIN RESULTS The study included 2,080 patients with 2,296 admissions. Incidences of VAC, IVAC, VAE-VAP, and VAP according to prospective surveillance were 10.0, 4.2, 3.2, and 8.0 per 1000 ventilation days, respectively. The VAE algorithm detected at most 32% of the patients with VAP identified by prospective surveillance. VAC signals were most often caused by volume overload and infections, but not necessarily VAP. Subdistribution hazards for mortality were 3.9 (95% confidence interval, 2.9-5.3) for VAC, 2.5 (1.5-4.1) for IVAC, 2.0 (1.1-3.6) for VAE-VAP, and 7.2 (5.1-10.3) for VAP identified by prospective surveillance. In sensitivity analyses, mortality estimates varied considerably after minor differences in electronic algorithm implementation. CONCLUSIONS Concordance between the novel VAE algorithm and VAP was poor. Incidence and associated mortality of VAE were susceptible to small differences in electronic implementation. More studies are needed to characterize the clinical entities underlying VAE and to ensure comparability of rates from different institutions.

Incidence, Risk Factors, and Attributable Mortality of Secondary Infections in the Intensive Care Unit After Admission for Sepsis

IMPORTANCE Sepsis is considered to induce immune suppression, leading to increased susceptibility to secondary infections with associated late mortality. OBJECTIVE To determine the clinical and host genomic characteristics, incidence, and attributable mortality of intensive care unit (ICU)-acquired infections in patients admitted to the ICU with or without sepsis. DESIGN, SETTING, AND PARTICIPANTS Prospective observational study comprising consecutive admissions of more than 48 hours in 2 ICUs in the Netherlands from January 2011 to July 2013 stratified according to admission diagnosis (sepsis or noninfectious). MAIN OUTCOMES AND MEASURES The primary outcome was ICU-acquired infection (onset >48 hours). Attributable mortality risk (fraction of mortality that can be prevented by elimination of the risk factor, acquired infection) was determined using time-to-event models accounting for competing risk. In a subset of sepsis admissions (n = 461), blood gene expression (whole-genome transcriptome in leukocytes) was analyzed at baseline and at onset of ICU-acquired infectious (n = 19) and noninfectious (n = 9) events. RESULTS The primary cohort included 1719 sepsis admissions (1504 patients; median age, 62 years; interquartile range [IQR], 51-71 years]; 924 men [61.4%]). A comparative cohort included 1921 admissions (1825 patients, median age, 62 years; IQR, 49-71 years; 1128 men [61.8%] in whom infection was not present in the first 48 hours. Intensive care unit-acquired infections occurred in 13.5% of sepsis ICU admissions (n = 232) and 15.1% of nonsepsis ICU admissions (n = 291). Patients with sepsis who developed an ICU-acquired infection had higher disease severity scores on admission than patients with sepsis who did not develop an ICU-acquired infection (Acute Physiology and Chronic Health Evaluation IV [APACHE IV] median score, 90 [IQR, 72-107] vs 79 [IQR, 62-98]; P < .001) and throughout their ICU stay but did not have differences in baseline gene expression. The population attributable mortality fraction of ICU-acquired infections in patients with sepsis was 10.9% (95% CI, 0.9%-20.6%) by day 60; the estimated difference between mortality in all patients with a sepsis admission diagnosis and mortality in those without ICU-acquired infection was 2.0% (95% CI, 0.2%-3.8%; P = .03) by day 60. Among nonsepsis ICU admissions, ICU-acquired infections had a population attributable mortality fraction of 21.1% (95% CI, 0.6%-41.7%) by day 60. Compared with baseline, blood gene expression at the onset of ICU-acquired infections showed reduced expression of genes involved in gluconeogenesis and glycolysis. CONCLUSIONS AND RELEVANCE Intensive care unit-acquired infections occurred more commonly in patients with sepsis with higher disease severity, but such infections contributed only modestly to overall mortality. The genomic response of patients with sepsis was consistent with immune suppression at the onset of secondary infection.

Interobserver agreement of Centers for Disease Control and Prevention criteria for classifying infections in critically ill patients

Objectives:Correct classification of the source of infection is important in observational and interventional studies of sepsis. Centers for Disease Control and Prevention criteria are most commonly used for this purpose, but the robustness of these definitions in critically ill patients is not known. We hypothesized that in a mixed ICU population, the performance of these criteria would be generally reduced and would vary among diagnostic subgroups. Design:Prospective cohort. Setting:Data were collected as part of a cohort of 1,214 critically ill patients admitted to two hospitals in The Netherlands between January 2011 and June 2011. Patients:Eight observers assessed a random sample of 168 of 554 patients who had experienced at least one infectious episode in the ICU. Each patient was assessed by two randomly selected observers who independently scored the source of infection (by affected organ system or site), the plausibility of infection (rated as none, possible, probable, or definite), and the most likely causative pathogen. Assessments were based on a post hoc review of all available clinical, radiological, and microbiological evidence. The observed diagnostic agreement for source of infection was classified as partial (i.e., matching on organ system or site) or complete (i.e., matching on specific diagnostic terms), for plausibility as partial (2-point scale) or complete (4-point scale), and for causative pathogens as an approximate or exact pathogen match. Interobserver agreement was expressed as a concordant percentage and as a kappa statistic. Interventions:None. Measurements and Main Results:A total of 206 infectious episodes were observed. Agreement regarding the source of infection was 89% (183/206) and 69% (142/206) for a partial and complete diagnostic match, respectively. This resulted in a kappa of 0.85 (95% CI, 0.79–0.90). Agreement varied from 63% to 91% within major diagnostic categories and from 35% to 97% within specific diagnostic subgroups, with the lowest concordance observed in cases of ventilator-associated pneumonia. In the 142 episodes for which a complete match on source of infection was obtained, the interobserver agreement for plausibility of infection was 83% and 65% on a 2- and 4-point scale, respectively. For causative pathogen, agreement was 78% and 70% for an approximate and exact pathogen match, respectively. Conclusions:Interobserver agreement for classifying sources of infection using Centers for Disease Control and Prevention criteria was excellent overall. However, full concordance on all aspects of the diagnosis between independent observers was rare for some types of infection, in particular for ventilator-associated pneumonia.

The attributable mortality of delirium in critically ill patients: prospective cohort study

Objective To determine the attributable mortality caused by delirium in critically ill patients. Design Prospective cohort study. Setting 32 mixed bed intensive care unit in the Netherlands, January 2011 to July 2013. Participants 1112 consecutive adults admitted to an intensive care unit for a minimum of 24 hours. Exposures Trained observers evaluated delirium daily using a validated protocol. Logistic regression and competing risks survival analyses were used to adjust for baseline variables and a marginal structural model analysis to adjust for confounding by evolution of disease severity before the onset of delirium. Main outcome measure Mortality during admission to an intensive care unit. Results Among 1112 evaluated patients, 558 (50.2%) developed at least one episode of delirium, with a median duration of 3 days (interquartile range 2-7 days). Crude mortality was 94/558 (17%) in patients with delirium compared with 40/554 (7%) in patients without delirium (P<0.001). Delirium was significantly associated with mortality in the multivariable logistic regression analysis (odds ratio 1.77, 95% confidence interval 1.15 to 2.72) and survival analysis (subdistribution hazard ratio 2.08, 95% confidence interval 1.40 to 3.09). However, the association disappeared after adjustment for time varying confounders in the marginal structural model (subdistribution hazard ratio 1.19, 95% confidence interval 0.75 to 1.89). Using this approach, only 7.2% (95% confidence interval −7.5% to 19.5%) of deaths in the intensive care unit were attributable to delirium, with an absolute mortality excess in patients with delirium of 0.9% (95% confidence interval −0.9% to 2.3%) by day 30. In post hoc analyses, however, delirium that persisted for two days or more remained associated with a 2.0% (95% confidence interval 1.2% to 2.8%) absolute mortality increase. Furthermore, competing risk analysis showed that delirium of any duration was associated with a significantly reduced rate of discharge from the intensive care unit (cause specific hazard ratio 0.65, 95% confidence interval 0.55 to 0.76). Conclusions Overall, delirium prolongs admission in the intensive care unit but does not cause death in critically ill patients. Future studies should focus on episodes of persistent delirium and its long term sequelae rather than on acute mortality. Trial registration Clinicaltrials.gov NCT01905033.

A molecular biomarker to diagnose community-acquired pneumonia on intensive care unit admission.

RATIONALE Community-acquired pneumonia (CAP) accounts for a major proportion of intensive care unit (ICU) admissions for respiratory failure and sepsis. Diagnostic uncertainty complicates case management, which may delay appropriate cause-specific treatment. OBJECTIVES To characterize the blood genomic response in patients with suspected CAP and identify a candidate biomarker for the rapid diagnosis of CAP on ICU admission. METHODS The study comprised two cohorts of consecutively enrolled patients treated for suspected CAP on ICU admission. Patients were designated CAP (cases) and no-CAP patients (control subjects) by post hoc assessment. The first (discovery) cohort (101 CAP and 33 no-CAP patients) was enrolled between January 2011 and July 2012; the second (validation) cohort (70 CAP and 30 no-CAP patients) between July 2012 and June 2013. Blood was collected within 24 hours of ICU admission. MEASUREMENTS AND MAIN RESULTS Blood microarray analysis of CAP and no-CAP patients revealed shared and distinct gene expression patterns. A 78-gene signature was defined for CAP, from which a FAIM3:PLAC8 gene expression ratio was derived with area under curve of 0.845 (95% confidence interval, 0.764-0.917) and positive and negative predictive values of 83% and 81%, respectively. Robustness of the FAIM3:PLAC8 ratio was ascertained by quantitative polymerase chain reaction in the validation cohort. The FAIM3:PLAC8 ratio outperformed plasma procalcitonin and IL-8 and IL-6 in discriminating between CAP and no-CAP patients. CONCLUSIONS CAP and no-CAP patients presented shared and distinct blood genomic responses. We propose the FAIM3:PLAC8 ratio as a candidate biomarker to assist in the rapid diagnosis of CAP on ICU admission. Clinical trial registered with www.clinicaltrials.gov (NCT 01905033).

Thrombocytopenia is associated with a dysregulated host response in critically ill sepsis patients

Preclinical studies have suggested that platelets influence the host response during sepsis. We sought to assess the association of admission thrombocytopenia with the presentation, outcome, and host response in patients with sepsis. Nine hundred thirty-one consecutive sepsis patients were stratified according to platelet counts (very low <50 × 10(9)/L, intermediate-low 50 × 10(9) to 99 × 10(9)/L, low 100 × 10(9) to 149 × 10(9)/L, or normal 150 × 10(9) to 399 × 10(9)/L) on admission to the intensive care unit. Sepsis patients with platelet counts <50 × 10(9)/L and 50 × 10(9) to 99 × 10(9)/L presented with higher Acute Physiology and Chronic Health Evaluation scores and more shock. Both levels of thrombocytopenia were independently associated with increased 30-day mortality (hazard ratios with 95% confidence intervals 2.00 [1.32-3.05] and 1.72 [1.22-2.44], respectively). To account for baseline differences besides platelet counts, propensity matching was performed, after which the association between thrombocytopenia and the host response was tested, as evaluated by measuring 17 plasma biomarkers indicative of activation and/or dysregulation of pathways implicated in sepsis pathogenesis and by whole genome blood leukocyte expression profiling. In the propensity matched cohort, platelet counts < 50 × 10(9)/L were associated with increased cytokine levels and enhanced endothelial cell activation. All thrombocytopenic groups showed evidence of impaired vascular integrity, whereas coagulation activation was similar between groups. Blood microarray analysis revealed a distinct gene expression pattern in sepsis patients with <50 × 10(9)/L platelets, showing reduced signaling in leukocyte adhesion and diapedesis and increased complement signaling. These data show that admission thrombocytopenia is associated with enhanced mortality and a more disturbed host response during sepsis independent of disease severity, thereby providing clinical validity to animal studies on the role of platelets in severe infection.

A Molecular Host Response Assay to Discriminate Between Sepsis and Infection-Negative Systemic Inflammation in Critically Ill Patients: Discovery and Validation in Independent Cohorts

Background Systemic inflammation is a whole body reaction having an infection-positive (i.e., sepsis) or infection-negative origin. It is important to distinguish between these two etiologies early and accurately because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on peripheral blood RNAs could be discovered that would (1) determine which patients with systemic inflammation had sepsis, (2) be robust across independent patient cohorts, (3) be insensitive to disease severity, and (4) provide diagnostic utility. The goal of this study was to identify and validate such a molecular classifier. Methods and Findings We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICUs). Biomarker discovery utilized an Australian cohort (n = 105) consisting of 74 cases (sepsis patients) and 31 controls (post-surgical patients with infection-negative systemic inflammation) recruited at five tertiary care settings in Brisbane, Australia, from June 3, 2008, to December 22, 2011. A four-gene classifier combining CEACAM4, LAMP1, PLA2G7, and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte Lab, was validated using reverse transcription quantitative PCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Patients for validation were selected from the Molecular Diagnosis and Risk Stratification of Sepsis study (ClinicalTrials.gov, NCT01905033), which recruited ICU patients from the Academic Medical Center in Amsterdam and the University Medical Center Utrecht. Patients recruited from November 30, 2012, to August 5, 2013, were eligible for inclusion in the present study. Validation cohort 1 (n = 59) consisted entirely of unambiguous cases and controls; SeptiCyte Lab gave an area under curve (AUC) of 0.95 (95% CI 0.91–1.00) in this cohort. ROC curve analysis of an independent, more heterogeneous group of patients (validation cohorts 2–5; 249 patients after excluding 37 patients with an infection likelihood of “possible”) gave an AUC of 0.89 (95% CI 0.85–0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility of SeptiCyte Lab was evaluated by comparison to various clinical and laboratory parameters available to a clinician within 24 h of ICU admission. SeptiCyte Lab was significantly better at differentiating cases from controls than all tested parameters, both singly and in various logistic combinations, and more than halved the diagnostic error rate compared to procalcitonin in all tested cohorts and cohort combinations. Limitations of this study relate to (1) cohort compositions that do not perfectly reflect the composition of the intended use population, (2) potential biases that could be introduced as a result of the current lack of a gold standard for diagnosing sepsis, and (3) lack of a complete, unbiased comparison to C-reactive protein. Conclusions SeptiCyte Lab is a rapid molecular assay that may be clinically useful in managing ICU patients with systemic inflammation. Further study in population-based cohorts is needed to validate this assay for clinical use.

Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study

BACKGROUND Host responses during sepsis are highly heterogeneous, which hampers the identification of patients at high risk of mortality and their selection for targeted therapies. In this study, we aimed to identify biologically relevant molecular endotypes in patients with sepsis. METHODS This was a prospective observational cohort study that included consecutive patients admitted for sepsis to two intensive care units (ICUs) in the Netherlands between Jan 1, 2011, and July 20, 2012 (discovery and first validation cohorts) and patients admitted with sepsis due to community-acquired pneumonia to 29 ICUs in the UK (second validation cohort). We generated genome-wide blood gene expression profiles from admission samples and analysed them by unsupervised consensus clustering and machine learning. The primary objective of this study was to establish endotypes for patients with sepsis, and assess the association of these endotypes with clinical traits and survival outcomes. We also established candidate biomarkers for the endotypes to allow identification of patient endotypes in clinical practice. FINDINGS The discovery cohort had 306 patients, the first validation cohort had 216, and the second validation cohort had 265 patients. Four molecular endotypes for sepsis, designated Mars1-4, were identified in the discovery cohort, and were associated with 28-day mortality (log-rank p=0·022). In the discovery cohort, the worst outcome was found for patients classified as having a Mars1 endotype, and at 28 days, 35 (39%) of 90 people with a Mars1 endotype had died (hazard ratio [HR] vs all other endotypes 1·86 [95% CI 1·21-2·86]; p=0·0045), compared with 23 (22%) of 105 people with a Mars2 endotype (HR 0·64 [0·40-1·04]; p=0·061), 16 (23%) of 71 people with a Mars3 endotype (HR 0·71 [0·41-1·22]; p=0·19), and 13 (33%) of 40 patients with a Mars4 endotype (HR 1·13 [0·63-2·04]; p=0·69). Analysis of the net reclassification improvement using a combined clinical and endotype model significantly improved risk prediction to 0·33 (0·09-0·58; p=0·008). A 140-gene expression signature reliably stratified patients with sepsis to the four endotypes in both the first and second validation cohorts. Only Mars1 was consistently significantly associated with 28-day mortality across the cohorts. To facilitate possible clinical use, a biomarker was derived for each endotype; BPGM and TAP2 reliably identified patients with a Mars1 endotype. INTERPRETATION This study provides a method for the molecular classification of patients with sepsis to four different endotypes upon ICU admission. Detection of sepsis endotypes might assist in providing personalised patient management and in selection for trials. FUNDING Center for Translational Molecular Medicine, Netherlands.

Likelihood of infection in patients with presumed sepsis at the time of intensive care unit admission: a cohort study

IntroductionA clinical suspicion of infection is mandatory for diagnosing sepsis in patients with a systemic inflammatory response syndrome. Yet, the accuracy of categorizing critically ill patients presenting to the intensive care unit (ICU) as being infected or not is unknown. We therefore assessed the likelihood of infection in patients who were treated for sepsis upon admission to the ICU, and quantified the association between plausibility of infection and mortality.MethodsWe studied a cohort of critically ill patients admitted with clinically suspected sepsis to two tertiary ICUs in the Netherlands between January 2011 and December 2013. The likelihood of infection was categorized as none, possible, probable or definite by post-hoc assessment. We used multivariable competing risks survival analyses to determine the association of the plausibility of infection with mortality.ResultsAmong 2579 patients treated for sepsis, 13% had a post-hoc infection likelihood of “none”, and an additional 30% of only “possible”. These percentages were largely similar for different suspected sites of infection. In crude analyses, the likelihood of infection was associated with increased length of stay and complications. In multivariable analysis, patients with an unlikely infection had a higher mortality rate compared to patients with a definite infection (subdistribution hazard ratio 1.23; 95% confidence interval 1.03-1.49).ConclusionsThis study is the first prospective analysis to show that the clinical diagnosis of sepsis upon ICU admission corresponds poorly with the presence of infection on post-hoc assessment. A higher likelihood of infection does not adversely influence outcome in this population.Trial registrationClinicalTrials.gov NCT01905033. Registered 11 July 2013.

Incidence, Predictors, and Outcomes of New-Onset Atrial Fibrillation in Critically Ill Patients with Sepsis. A Cohort Study

Rationale: Patients admitted to intensive care units with sepsis are prone to developing cardiac dysrhythmias, most commonly atrial fibrillation. Objectives: To determine the incidence, risk factors, and outcomes of atrial fibrillation in a cohort of critically ill patients with sepsis. Methods: We assessed the association between atrial fibrillation and mortality using time‐dependent competing risks survival analysis. Subsequently, for development of a risk score estimating the probability of a first occurrence of atrial fibrillation within the following 24 hours, we performed logistic regression analysis. Measurements and Main Results: Among 1,782 patients with sepsis admitted to two tertiary intensive care units in the Netherlands between January 2011 and June 2013, a total of 1,087 episodes of atrial fibrillation occurred in 418 (23%) individuals. The cumulative risk of new‐onset atrial fibrillation was 10% (95% confidence interval [CI], 8‐12), 22% (95% CI, 18‐25), and 40% (95% CI, 36‐44) in patients with sepsis, severe sepsis, and septic shock, respectively. New‐onset atrial fibrillation was associated with a longer stay (hazard ratio [HR], 0.55; 95% CI, 0.48‐0.64), an increased death rate (HR, 1.52; 95% CI, 1.16‐2.00), and an overall increased mortality risk (subdistribution HR, 2.10; 95% CI, 1.61‐2.73) when considering discharge as a competing event. A simple risk score for daily prediction of atrial fibrillation occurrence yielded good discrimination (C statistic, 0.81; 95% CI, 0.79‐0.84) and calibration (chi‐square, 9.38; P = 0.31), with similar performance in an independent validation cohort (C statistic, 0.80; 95% CI, 0.76‐0.85). Conclusions: Atrial fibrillation is a common complication of sepsis and independently associated with excess mortality. A simple risk score may identify patients at high risk of this complication. Clinical trial registered with www.clinicaltrials.gov (NCT 01905033).