Diagnostic accuracy and clinical relevance of an inflammatory biomarker panel for sepsis in adult critically ill patients.
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ABSTRACT:
SUBMITTER: Bauer PR
PROVIDER: S-EPMC4716883 | biostudies-literature | 2016 Feb
REPOSITORIES: biostudies-literature
Publications
Diagnostic accuracy and clinical relevance of an inflammatory biomarker panel for sepsis in adult critically ill patients.
Bauer Philippe R PR Kashyap Rahul R League Stacy C SC Park John G JG Block Darci R DR Baumann Nikola A NA Algeciras-Schimnich Alicia A Jenkins Sarah M SM Smith Carin Y CY Gajic Ognjen O Abraham Roshini S RS
Diagnostic microbiology and infectious disease 20151009 2
The objective of this study was to assess the diagnostic accuracy of C-reactive protein (CRP), procalcitonin (PCT), and cellular immune markers levels in sepsis. This was a prospective observational study in adult intensive care unit (ICU) patients, between 2012 and 2014. The 8-color flow cytometric biomarker panel included CD64, CD163, and HLA-DR. Index test results were compared with sepsis, using receiver operating characteristic curve analyses. Multivariate logistic regression assessed the r ...[more]
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Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood 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 overall 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 (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood 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 the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples Retrospective, mutli-site sutdy using retrospective physician adjudication as a comparator
2015-10-24 | E-GEOD-74224 | biostudies-arrayexpress
Project description:Objective: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients. Design: A prospective cross-sectional study. Setting: A 20-bed general intensive care unit of a tertiary referral hospital. Patients: Seventy-two patients admitted to the intensive care unit. Interventions: Intravenous blood was collected for leukocyte separation and RNA extraction. Microarray experiements were then performed examing the expression level of 19,232 genes in each sample. Measurements and Main Results: There was no difference in the expression profile between gram-positive and gram-negative sepsis. The finding remained unchanged even when genes with lower expression level were included or after statistical stringency was lowered. There were, however, ninety-four genes differentially expressed between sepsis and control patients. These genes included those involved in immune regulation, inflammation and mitochondrial function. Hierarchical cluster analysis confirmed that the difference in gene expression profile existed between sepsis and control patients, but not between gram-positive and gram-negative patients. Conclusion: Gram-positive and gram-negative sepsis share a common host response at a transcriptome level. These findings support the hypothesis that the septic response is non-specific and is designed to provide a more general response that can be elicited by a wide range of different micro-organisms. The study included seventy-two critically ill patients admitted to the intensive care unit (ICU) of Nepean Hospital, Sydney, Australia. Of these, fifty-five patients were diagnosed to have sepsis, as confirmed by microbiological culture. The remaining seventeen patients did not have sepsis and were therefore used as controls. The study was approved by the hospital ethics committee and informed consent was obtained from all patients or their relatives. Patient Samples. Whole blood was taken from each patient on admission to ICU. Neutrophils were separated from whole blood using density-gradient separation with Ficoll-PaqueP P(Amersham). Subsequent neutrophil RNA extraction was performed using guanidinium thiocyanate (Ambion). Microarray Experiment. The neutrophil RNA was converted to cDNA, fluorescently labeled and hybridized to its complimentary sequences on the microarray (Invitrogen). The fluorescent signals on each micrroarray were captured using the GenePix 4000B laser scanner (Axon Instruments). Expression level of each gene was represented by the intensity of its fluorescent signal. Data Extraction. All signal intensity values were processed using background-subtraction method. Prior to analysis, all values were log-transformed and normalized by fitting a print-tip group Lowess curve. Normalization minimizes bias due to dye chemistry, signal intensity or location of a gene on the array. It ensures the detection of genes that are truly differentially expressed, instead of those caused by experimental artifacts or variation in the hybridization process. After normalization, genes that had more than 50% of data missing were removed. We then selected genes that had at least 80% of the data showing two-fold changes from the geneâs median values. After filtering, 1617 genes were available for further analysis.
2010-05-25 | E-GEOD-6535 | biostudies-arrayexpress
Project description:BackgroundEarly and accurate diagnosis of sepsis is challenging. Although procalcitonin and presepsin have been identified as potential biomarkers to differentiate between sepsis and other non-infectious causes of systemic inflammation, the diagnostic accuracy of these biomarkers remains controversial. Herein, we performed a comprehensive meta-analysis to assess the overall diagnostic value of procalcitonin and presepsin for the diagnosis of sepsis.MethodsWe searched three electronic databases (MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials) for relevant studies. Two authors independently screened articles on the basis of inclusion and exclusion criteria. The pooled sensitivity, specificity, and summary receiver operating characteristic curves were estimated. The quality of evidence for diagnostic accuracy in absolute effects, i.e., the number of true or false positives and true or false negatives, gave a particular pre-test probability.ResultsWe included 19 studies (19 observational studies and no randomized controlled trials) that had enrolled 3012 patients. Analyses of summary receiver operating characteristic curves revealed areas under the receiver operating characteristic curves of 0.84 for procalcitonin and 0.87 for presepsin. The pooled sensitivities and specificities were 0.80 (95% confidence interval 0.75 to 0.84) and 0.75 (95% confidence interval 0.67 to 0.81) for procalcitonin. For presepsin, these values were 0.84 (95% confidence interval 0.80 to 0.88) and 0.73 (95% confidence interval 0.61 to 0.82), respectively. There were no statistically significant differences in both pooled sensitivities (p = 0.48) and specificities (p = 0.57) between procalcitonin and presepsin.ConclusionOur meta-analysis provided evidence that the diagnostic accuracy of procalcitonin and presepsin in detecting infection was similar and that both are useful for early diagnosis of sepsis and subsequent reduction of mortality in critically ill adult patients.Systematic review registrationThe study was registered in PROSPERO under the registration number CRD42016035784.
| S-EPMC6466719 | biostudies-literature
Project description:Objective:Electrographic seizures in critically ill patients are often equivocal. In this study, we sought to determine the diagnostic accuracy of electrographic seizure annotation in adult intensive care units (ICUs) and to identify affecting factors. Methods:To investigate diagnostic accuracy, interreader agreement (IRA) measures were derived from 5,769 unequivocal and 6,263 equivocal seizure annotations by five experienced electroencephalogram (EEG) readers after reviewing 74 days of EEGs from 50 adult ICU patients. Factors including seizure equivocality (unequivocal vs. equivocal) and laterality (generalized, partial, or bilaterally independent), cyclicity (cyclic vs. noncyclic), persistency (occurrence of status epilepticus), and patient consciousness level (coma vs. noncoma) were further investigated for their influence on IRA measures. Results:On average, 70% of seizures marked by a reference reader overlapped, at least in part, with those marked by a test reader (any-overlap sensitivity, AO-Sn). Agreed seizure duration between reader pairs (overlap-integral sensitivity, OI-Sn) was 62%, while agreed nonseizure duration (overlap-integral specificity, OI-Sp) was 99%. A test reader would annotate one additional seizure not overlapping with a reference reader's annotation in every 11.7 h of EEG, that is, the false-positive rate (FPR) was 0.0854/h. Classifying seizure patterns into unequivocal and equivocal improved specificity and FPR (unequivocal patterns) but compromised sensitivity only for equivocal patterns. Sensitivity of all and unequivocal annotations was higher for patients with status epilepticus. Specificity was higher for partial than for bilaterally independent unequivocal seizure patterns, and lower for cyclic all seizure patterns. Significance:Diagnosing electrographic seizures in critically ill adults is highly specific and moderately sensitive. Improved criteria for diagnosing electrographic seizures in the ICU are needed.
| S-EPMC5939393 | biostudies-literature
Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood 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 overall 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 (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood 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 the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples
2015-10-24 | GSE74224 | GEO
Project description:Objective: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients. Design: A prospective cross-sectional study. Setting: A 20-bed general intensive care unit of a tertiary referral hospital. Patients: Seventy-two patients admitted to the intensive care unit. Interventions: Intravenous blood was collected for leukocyte separation and RNA extraction. Microarray experiements were then performed examing the expression level of 19,232 genes in each sample. Measurements and Main Results: There was no difference in the expression profile between gram-positive and gram-negative sepsis. The finding remained unchanged even when genes with lower expression level were included or after statistical stringency was lowered. There were, however, ninety-four genes differentially expressed between sepsis and control patients. These genes included those involved in immune regulation, inflammation and mitochondrial function. Hierarchical cluster analysis confirmed that the difference in gene expression profile existed between sepsis and control patients, but not between gram-positive and gram-negative patients. Conclusion: Gram-positive and gram-negative sepsis share a common host response at a transcriptome level. These findings support the hypothesis that the septic response is non-specific and is designed to provide a more general response that can be elicited by a wide range of different micro-organisms. Keywords: disease state analysis, gram-positive sepsis, gram-negative sepsis
2007-12-01 | GSE6535 | GEO
Project description:Chimeric antigen receptor (CAR) T-cells directed against CD19 have drastically altered outcomes for children with relapsed and refractory acute lymphoblastic leukemia (r/r ALL). Pediatric patients with r/r ALL treated with CAR-T are at increased risk of both cytokine release syndrome (CRS) and sepsis. We sought to investigate the biologic differences between CRS and sepsis and to develop predictive models which could accurately differentiate CRS from sepsis at the time of critical illness. We identified 23 different cytokines that were significantly different between patients with sepsis and CRS. Using elastic net prediction modeling and tree classification, we identified cytokines that were able to classify subjects as having CRS or sepsis accurately. A markedly elevated interferon ? (IFN?) or a mildly elevated IFN? in combination with a low IL1? were associated with CRS. A normal to mildly elevated IFN? in combination with an elevated IL1? was associated with sepsis. This combination of IFN? and IL1? was able to categorize subjects as having CRS or sepsis with 97% accuracy. As CAR-T therapies become more common, these data provide important novel information to better manage potential associated toxicities.
| S-EPMC7594400 | biostudies-literature
Project description:Sepsis is a frequent complication in critically ill patients and highly heterogeneous that is associated with high morbidity and mortality rates, especially in the elderly population. Utilizing RNA-Sequencing (RNA-Seq) to analysis biological pathways is widely used in clinical and molecular genetics studies, but in elderly patients with sepsis are still lacking. Hence, we aim to investigate the mortality-relevant biological features and transcriptomic features in elderly patients who were admitted to intensive care unit (ICU) for sepsis.
2022-11-03 | GSE216902 | GEO
Project description:BackgroundSepsis is associated with a deflection of inflammatory and coagulative parameters, since some clotting factors are known to be involved in the host's defense against infection and inflammation. These parameters could play a crucial role in the course of sepsis and be used as prognostic markers in critically ill children.MethodsA total of 250 critically ill pediatric patients diagnosed with sepsis were retrospectively analyzed to identify routinely measured predictors for in-hospital mortality at the peak level of C-reactive protein. Those parameters entered multivariate logistic regression analysis as well as a decision tree for survival.ResultsMultivariate logistic regression analysis revealed fibrinogen, platelets and activated partial thromboplastin time (aPTT) at the peak level of C-reactive protein to be predictors for survival (p?=?0.03, p?=?0.01 and p?=?0.02, respectively). An increase in fibrinogen and platelets is linked to survival, whereas an aPTT prolongation is associated with higher mortality; adjusted odds ratios (95% CI) for an increase of 100 mg/dl in fibrinogen are 1.35 (1.04-1.82) per 50 G/l platelets 1.94 (1.3-3.29) and 0.83 (0.69-0.96) for an aPTT prolongation of 10 s. Decision tree analysis shows that a fibrinogen level below 192 mg/dl (90.9% vs. 13% mortality) is most distinctive in non-survivors.ConclusionsHigh levels of fibrinogen and platelets as well as a non-overshooting aPTT are associated with a higher survival rate in pediatric patients with diagnosed sepsis. In particular, hypofibrinogenemia is distinctive for a high mortality rate in septic critically ill children.
| S-EPMC6240023 | biostudies-literature
Project description:IntroductionLipopolysaccharide-binding protein (LBP) is widely reported as a biomarker to differentiate infected from non-infected patients. The diagnostic use of LBP for sepsis remains a matter of debate. We aimed to perform a systematic review and meta-analysis to assess the diagnostic accuracy of serum LBP for sepsis in adult patients.MethodsWe performed a systematic review and meta-analysis to assess the accuracy of LBP for sepsis diagnosis. A systematic search in PubMed and EMBASE for studies that evaluated the diagnostic role of LBP for sepsis through December 2015 was conducted. We searched these databases for original, English language, research articles that studied the diagnostic accuracy between septic and non-septic adult patients. Sensitivity, specificity, and other measures of accuracy, such as diagnostic odds ratio (DOR) and area under the receiver operating characteristic curve (AUC) of LBP were pooled using the Hierarchical Summary Receiver Operating Characteristic (HSROC) method.ResultsOur search returned 53 reports, of which 8 fulfilled the inclusion criteria, accounting for 1684 patients. The pooled sensitivity and specificity of LBP for diagnosis of sepsis by the HSROC method were 0.64 (95% CI: 0.56-0.72) and 0.63 (95% CI: 0.53-0.73), respectively. The value of the DOR was 3.0 (95% CI: 2.0-4.0) and the AUC was 0.68 (95% CI: 0.64-0.72). Meta-regression analysis revealed that cut-off values accounted for the heterogeneity of sensitivity and sample size (> = 150) accounted for the heterogeneity of specificity.ConclusionsBased on the results of our meta-analysis, LBP had weak sensitivity and specificity in the detection of sepsis. LBP may not be practically recommended for clinical utilization as a single biomarker.
| S-EPMC4824361 | biostudies-literature