Dataset Information

Persistently Elevated Glucagon-Like Peptide-1 Levels among Critically Ill Surgical Patients after Sepsis and Development of Chronic Critical Illness and Dismal Long-Term Outcomes.

ABSTRACT: BACKGROUND:Glucagon-like peptide-1 (GLP-1) is a gut-derived incretin hormone that stimulates insulin secretion, cellular glucose uptake, and has immune-regulatory functions. Glucagon-like peptide-1 is markedly altered after trauma and sepsis, but the implications remain unclear. STUDY DESIGN:We performed an analysis of a prospective, longitudinal cohort study of critically ill surgical patients with sepsis. Patient characteristics and clinical data were collected, as well as peripheral blood sampling for biomarker analysis, out to 28 days after sepsis onset. We prospectively adjudicated sepsis diagnosis, severity, clinical outcomes, and 6-month follow-up. RESULTS:The cohort included 157 septic surgical patients with significant physiologic derangement (Maximum Sequential Organ Failure Assessment [SOFA] score 8, interquartile range [IQR] 4 to 11), a high rate of multiple organ failure (50.3%), and septic shock (24.2%). Despite high disease severity, both early death (<14 days; n = 4, 2.9%) and overall inpatient mortality were low (n = 12, 7.6%). However, post-discharge 6-month mortality was nearly 3-fold higher (19.7%). Both GLP-1 and interleukin [IL]-6 levels were significantly elevated for 21 days (p ? 0.01) in patients who developed chronic critical illness (CCI) compared with patients with a rapid recovery. Elevated GLP-1 at 24 hours was a significant independent predictor for the development of CCI after controlling for IL-6 and glucose levels (p = 0.027), and at day 14 for death or severe functional disability at 6 months (WHO/Zubrod score 4-5, p = 0.014). CONCLUSIONS:Elevated GLP-1 within 24 hours of sepsis is a predictor of early death or persistent organ dysfunction. Among early survivors, persistently elevated GLP-1 levels at day 14 are strongly predictive of death or severe functional disability at 6 months. Persistently elevated GLP-1 levels may be a marker of a nonresolving catabolic state that is associated with muscle wasting and dismal outcomes after sepsis and chronic critical illness.

SUBMITTER: Brakenridge SC

PROVIDER: S-EPMC6599553 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Persistently Elevated Glucagon-Like Peptide-1 Levels among Critically Ill Surgical Patients after Sepsis and Development of Chronic Critical Illness and Dismal Long-Term Outcomes.

Brakenridge Scott C SC Moore Frederick A FA Mercier Nicole R NR Cox Michael M Wu Quron Q Moldawer Lyle L LL Mohr Alicia M AM Efron Philip A PA Smith R Stephen RS

Journal of the American College of Surgeons 20190413 1

<h4>Background</h4>Glucagon-like peptide-1 (GLP-1) is a gut-derived incretin hormone that stimulates insulin secretion, cellular glucose uptake, and has immune-regulatory functions. Glucagon-like peptide-1 is markedly altered after trauma and sepsis, but the implications remain unclear.<h4>Study design</h4>We performed an analysis of a prospective, longitudinal cohort study of critically ill surgical patients with sepsis. Patient characteristics and clinical data were collected, as well as perip ...[more]

PMID: 30991107

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Project description:BackgroundSuboptimal triage of critically ill patients with surgical sepsis may contribute to adverse outcomes. Patients transferred to a tertiary care center after spending 24 hours or longer at an outside facility were compared with patients who had early triage to a tertiary care center with the null hypothesis that management parameters and outcomes would be similar between groups.MethodsThis prospective observational cohort study included 308 patients treated for surgical sepsis in a surgical intensive care unit at a tertiary care center. Patients transferred after spending more than 24 hours at an outside facility (n = 69) were compared with patients who were directly admitted or transferred within 24 hours (n = 239). Patient characteristics, management parameters, and outcomes were compared between groups. This study was registered at ClinicalTrials.gov (NCT02276066).ResultsAverage outside facility length of stay in the delayed transfer group was 43 hours. Delayed transfer patients had higher sequential organ failure assessment (7 vs. 5, p = 0.003) and APACHE II scores (19 vs. 16, p = 0.007) on admission. The interval between admission and source control was significantly longer in the delayed transfer group (12.1 hours vs. 1.0 hours, p = 0.009). The incidence of nosocomial infection was significantly higher in the delayed transfer group (41% vs. 23%, p = 0.005). Delayed transfer was independently associated with a 10-day increase in hospital length of stay. Delayed transfer patients were less likely to be discharged home (22% vs. 59%, p < 0.001) and suffered twofold higher in-hospital mortality (14.5% vs. 7.1%, p = 0.056).ConclusionPatients with surgical sepsis who spent more than 24 hours at an outside facility prior to transfer had greater initial illness severity, longer intervals between admission and source control, and more nosocomial infections compared with patients who had early triage to a tertiary care center.Level of evidenceCare management/therapeutic, Level IV; Epidemiologic/prognostic, Level III.

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 SeptiCyteÂ® 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; SeptiCyteÂ® 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 SeptiCyteÂ® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyteÂ® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyteÂ® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyteÂ® 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

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.

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

Project description:ImportanceRapid and accurate discrimination of sepsis and its potential severity currently require multiple assays with slow processing times that are often inconclusive in discerning sepsis from sterile inflammation.ObjectiveTo analyze a whole-blood, multivalent, host-messenger RNA expression metric for estimating the likelihood of bacterial infection and 30-day mortality and compare performance of the metric with that of other diagnostic and prognostic biomarkers and clinical parameters.Design, setting, and participantsThis prospective diagnostic and prognostic study was performed in the surgical intensive care unit (ICU) of a single, academic health science center. The analysis included 200 critically ill adult patients admitted with suspected sepsis (cohort A) or those at high risk for developing sepsis (cohort B) between July 1, 2020, and July 30, 2021.ExposuresWhole-blood sample measurements of a custom 29-messenger RNA transcriptomic metric classifier for likelihood of bacterial infection (IMX-BVN-3) or 30-day mortality (severity) (IMX-SEV-3) in a clinical-diagnostic laboratory setting using an analysis platform (510[k]-cleared nCounter FLEX; NanoString, Inc), compared with measurement of procalcitonin and interleukin 6 (IL-6) plasma levels, and maximum 24-hour sequential organ failure assessment (SOFA) scores.Main outcomes and measuresEstimated sepsis and 30-day mortality performance.ResultsAmong the 200 patients included (124 men [62.0%] and 76 women [38.0%]; median age, 62.5 [IQR, 47.0-72.0] years), the IMX-BVN-3 bacterial infection classifier had an area under the receiver operating characteristics curve (AUROC) of 0.84 (95% CI, 0.77-0.90) for discriminating bacterial infection at ICU admission, similar to procalcitonin (0.85 [95% CI, 0.79-0.90]; P = .79) and significantly better than IL-6 (0.67 [95% CI, 0.58-0.75]; P < .001). For estimating 30-day mortality, the IMX-SEV-3 metric had an AUROC of 0.81 (95% CI, 0.66-0.95), which was significantly better than IL-6 levels (0.57 [95% CI, 0.37-0.77]; P = .006), marginally better than procalcitonin levels (0.65 [95% CI, 0.50-0.79]; P = .06), and similar to the SOFA score (0.76 [95% CI, 0.62-0.91]; P = .48). Combining IMX-BVN-3 and IMX-SEV-3 with procalcitonin or IL-6 levels or SOFA scores did not significantly improve performance. Among patients with sepsis, IMX-BVN-3 scores decreased over time, reflecting the resolution of sepsis. In 11 individuals at high risk (cohort B) who subsequently developed sepsis during their hospital course, IMX-BVN-3 bacterial infection scores did not decline over time and peaked on the day of documented infection.Conclusions and relevanceIn this diagnostic and prognostic study, a novel, multivalent, transcriptomic metric accurately estimated the presence of bacterial infection and risk for 30-day mortality in patients admitted to a surgical ICU. The performance of this single transcriptomic metric was equivalent to or better than multiple alternative diagnostic and prognostic metrics when measured at admission and provided additional information when measured over time.

Dataset Information

Persistently Elevated Glucagon-Like Peptide-1 Levels among Critically Ill Surgical Patients after Sepsis and Development of Chronic Critical Illness and Dismal Long-Term Outcomes.

Publications

Persistently Elevated Glucagon-Like Peptide-1 Levels among Critically Ill Surgical Patients after Sepsis and Development of Chronic Critical Illness and Dismal Long-Term Outcomes.

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