Serum syndecan-1 reflects organ dysfunction in critically ill patients.
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SUBMITTER: Suzuki K
PROVIDER: S-EPMC8065146 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Perilipin 2 (PLIN2) is a lipid droplet protein with various metabolic functions. However, studies investigating PLIN2 in the context of inflammation, especially in systemic and acute inflammation, are lacking. Hence, we assessed the relevance of serum PLIN2 in critically ill patients. We measured serum PLIN2 serum in 259 critically ill patients (166 with sepsis) upon admission to a medical intensive care unit (ICU) compared to 12 healthy controls. A subset of 36 patients underwent computed tomography to quantify body composition. Compared to controls, serum PLIN2 concentrations were elevated in critically ill patients at ICU admission. Interestingly, PLIN2 independently indicated multiple organ dysfunction (MOD), defined as a SOFA score > 9 points, at ICU admission, and was also able to independently predict MOD after 48 h. Moreover, serum PLIN2 levels were associated with severe respiratory failure potentially reflecting a moribund state. However, PLIN2 was neither a predictor of ICU mortality nor did it reflect metabolic dysregulation. Conclusively, the first study assessing serum PLIN2 in critical illness proved that it may assist in risk stratification because it is capable of independently indicating MOD at admission and predicting MOD 48 h after PLIN2 measurement. Further evaluation regarding the underlying mechanisms is warranted.
| S-EPMC8468514 | biostudies-literature
Project description:Background: Multiple organ dysfunction is a complex and lethal clinical feature with heterogeneous causes and is usually characterized by tissue injury of multiple organs. Tenascin-C (TNC) is a matricellular protein that is rarely expressed in most of the adult tissues, but re-induced following injury. This study aimed to evaluate serum TNC in predicting mortality in critically ill patients with multiple organ dysfunction. Methods: Adult critically ill patients with at least two organs dysfunction and an increase of Sequential Organ Failure Assess (SOFA) score ≥ 2 points within 7 days were prospectively enrolled into two independent cohorts. The emergency (derivation) cohort was a consecutive series and the patients were from Emergency Department. The inpatient (validation) cohort was a convenience series and the patients were from medical wards. Their serum samples at the first 24 h after enrollment were collected and subjected to TNC measurement using ELISA. The association between serum TNC level and 28-day all-cause mortality was investigated, and then the predictive value of serum TNC was analyzed. Results: A total of 110 patients with a median age of 64 years (53, 73) were enrolled in the emergency cohort. Compared to the survivors, serum TNC in the non-survivors was significantly higher (467.7 vs. 197.5 ng/ml, p < 0.001). Multivariate logistic regression analysis revealed that the association between serum TNC and 28-day mortality was independent of sepsis or critical illness scores such as SOFA, Acute Physiology and Chronic Health Evaluation (APACHE II), and Simplified Acute Physiology Score (SAPS II), respectively (p < 0.001 for each). The area under receiver operating characteristic curve of serum TNC for predicting mortality was 0.803 (0.717-0.888) (p < 0.001), similar with SOFA 0.808 (0.725-0.891), APACHE II 0.762 (0.667-0.857), and SAPS II 0.779 (0.685-0.872). The optimal cut-off value of serum TNC was 298.2 ng/ml. Kaplan-Meier analysis showed that the survival of patients with serum TNC ≥ 300 ng/ml was significantly worse than that of patients with serum TNC < 300 ng/ml. This result was validated in the inpatient cohort. The sensitivity and specificity of serum TNC ≥ 300 ng/ml for predicting mortality were 74.3 and 74.7% in the emergency cohort, and 63.0 and 70.1% in the inpatient cohort, respectively. Conclusion: Serum TNC was associated with mortality in critically ill patients with multiple organ dysfunction, and would be used as a prognostic tool for predicting mortality in this population.
| S-EPMC8661593 | biostudies-literature
Project description:IntroductionMultiple organ dysfunction (MOD) is a common pathway to morbidity and death in critically ill children. Defining organ dysfunction is challenging, as we lack a complete understanding of the complex pathobiology. Current pediatric organ dysfunction criteria assign the same diagnostic value-the same "weight"- to each organ system. While each organ dysfunction in isolation contributes to the outcome, there are likely complex interactions between multiple failing organs that are not simply additive.ObjectiveDetermine whether certain combinations of organ system dysfunctions have a significant interaction associated with higher risk of morbidity or mortality in critically ill children.MethodsWe conducted a retrospective observational cohort study of critically ill children at two large academic medical centers from 2010 and 2018. Patients were included in the study if they had at least two organ dysfunctions by day 3 of PICU admission based on the Pediatric Organ Dysfunction Information Update Mandate (PODIUM) criteria. Mortality was described as absolute number of deaths and mortality rate. Combinations of two pediatric organ dysfunctions were analyzed with interaction terms as independent variables and mortality or persistent MOD as the dependent variable in logistic regression models.ResultsOverall, 7,897 patients met inclusion criteria and 446 patients (5.6%) died. The organ dysfunction interactions that were significantly associated with the highest absolute number of deaths were cardiovascular + endocrinologic, cardiovascular + neurologic, and cardiovascular + respiratory. Additionally, the interactions associated with the highest mortality rates were liver + cardiovascular, respiratory + hematologic, and respiratory + renal. Among patients with persistent MOD, the most common organ dysfunctions with significant interaction terms were neurologic + respiratory, hematologic + immunologic, and endocrinologic + respiratory. Further analysis using classification and regression trees (CART) demonstrated that the absence of respiratory and liver dysfunction was associated with the lowest likelihood of mortality.Implications and future directionsCertain combinations of organ dysfunctions are associated with a higher risk of persistent MOD or death. Notably, the three most common organ dysfunction interactions were associated with 75% of the mortality in our cohort. Critically ill children with MOD presenting with these combinations of organ dysfunctions warrant further study.
| S-EPMC9081807 | biostudies-literature
Project description:BackgroundShock and organ damage occur in critically ill patients in the emergency department because of biological responses to invasion, and cytokines play an important role in their development. It is important to predict early multiple organ dysfunction (MOD) because it is useful in predicting patient outcomes and selecting treatment strategies. This study examined the accuracy of biomarkers, including interleukin (IL)-6, in predicting early MOD in critically ill patients compared with that of quick sequential organ failure assessment (qSOFA).MethodsThis was a multicenter observational sub-study. Five universities from 2016 to 2018. Data of adult patients with systemic inflammatory response syndrome who presented to the emergency department or were admitted to the intensive care unit were prospectively evaluated. qSOFA score and each biomarker (IL-6, IL-8, IL-10, tumor necrosis factor-α, C-reactive protein, and procalcitonin [PCT]) level were assessed on Days 0, 1, and 2. The primary outcome was set as MOD on Day 2, and the area under the curve (AUC) was analyzed to evaluate qSOFA scores and biomarker levels.ResultsOf 199 patients, 38 were excluded and 161 were included. Patients with MOD on Day 2 had significantly higher qSOFA, SOFA, and Acute Physiology and Chronic Health Evaluation II scores and a trend toward worse prognosis, including mortality. The AUC for qSOFA score (Day 0) that predicted MOD (Day 2) was 0.728 (95% confidence interval [CI]: 0.651-0.794). IL-6 (Day 1) showed the highest AUC among all biomarkers (0.790 [95% CI: 0.711-852]). The combination of qSOFA (Day 0) and IL-6 (Day 1) showed improved prediction accuracy (0.842 [95% CI: 0.771-0.893]). The combination model using qSOFA (Day 1) and IL-6 (Day 1) also showed a higher AUC (0.868 [95% CI: 0.799-0.915]). The combination model of IL-8 and PCT also showed a significant improvement in AUC.ConclusionsThe addition of IL-6, IL-8 and PCT to qSOFA scores improved the accuracy of early MOD prediction.
| S-EPMC8573766 | biostudies-literature
Project description:COVID-19-associated respiratory failure offers the unprecedented opportunity to evaluate the differential host response to a uniform pathogenic insult. Understanding whether there are distinct subphenotypes of severe COVID-19 may offer insight into its pathophysiology. Sequential Organ Failure Assessment (SOFA) score is an objective and comprehensive measurement that measures dysfunction severity of six organ systems, i.e., cardiovascular, central nervous system, coagulation, liver, renal, and respiration. Our aim was to identify and characterize distinct subphenotypes of COVID-19 critical illness defined by the post-intubation trajectory of SOFA score. Intubated COVID-19 patients at two hospitals in New York city were leveraged as development and validation cohorts. Patients were grouped into mild, intermediate, and severe strata by their baseline post-intubation SOFA. Hierarchical agglomerative clustering was performed within each stratum to detect subphenotypes based on similarities amongst SOFA score trajectories evaluated by Dynamic Time Warping. Distinct worsening and recovering subphenotypes were identified within each stratum, which had distinct 7-day post-intubation SOFA progression trends. Patients in the worsening suphenotypes had a higher mortality than those in the recovering subphenotypes within each stratum (mild stratum, 29.7% vs. 10.3%, p = 0.033; intermediate stratum, 29.3% vs. 8.0%, p = 0.002; severe stratum, 53.7% vs. 22.2%, p < 0.001). Pathophysiologic biomarkers associated with progression were distinct at each stratum, including findings suggestive of inflammation in low baseline severity of illness versus hemophagocytic lymphohistiocytosis in higher baseline severity of illness. The findings suggest that there are clear worsening and recovering subphenotypes of COVID-19 respiratory failure after intubation, which are more predictive of outcomes than baseline severity of illness. Distinct progression biomarkers at differential baseline severity of illness suggests a heterogeneous pathobiology in the progression of COVID-19 respiratory failure.
| S-EPMC8342520 | biostudies-literature
Project description: Not available
| S-EPMC7812556 | biostudies-literature
Project description:The brainstem conveys sensory and motor inputs between the spinal cord and the brain, and contains nuclei of the cranial nerves. It controls the sleep-wake cycle and vital functions via the ascending reticular activating system and the autonomic nuclei, respectively. Brainstem dysfunction may lead to sensory and motor deficits, cranial nerve palsies, impairment of consciousness, dysautonomia, and respiratory failure. The brainstem is prone to various primary and secondary insults, resulting in acute or chronic dysfunction. Of particular importance for characterizing brainstem dysfunction and identifying the underlying etiology are a detailed clinical examination, MRI, neurophysiologic tests such as brainstem auditory evoked potentials, and an analysis of the cerebrospinal fluid. Detection of brainstem dysfunction is challenging but of utmost importance in comatose and deeply sedated patients both to guide therapy and to support outcome prediction. In the present review, we summarize the neuroanatomy, clinical syndromes, and diagnostic techniques of critical illness-associated brainstem dysfunction for the critical care setting.
| S-EPMC6945639 | biostudies-literature
Project description:We investigated the effect of antibiotic timing on outcomes based on changes in surrogate markers of organ failure, including platelet, serum bilirubin, serum creatinine levels, and the PaO₂/FiO₂ (P/F) ratio. This was a single-center, retrospective observational study of critically ill septic patients who presented to the emergency department (ED). The study period extended from August 2008 to September 2016. The primary outcomes included changes in platelet, serum bilirubin, serum creatinine levels, and the P/F ratio (δ-platelet, δ-serum bilirubin, δ-serum creatinine, and δ-P/F ratio were calculated as values measured on Day 3; values measured at ED enrollment). A multivariable linear regression model was developed to assess variables related to outcomes (δ-platelet, δ-serum bilirubin, δ-serum creatinine, and δ-P/F ratio). We analyzed 1784 patients who met the inclusion criteria. The overall 28-day mortality was 14% (n = 256/1784). On multivariable linear regression analysis, the hourly delay in antibiotic therapy was significantly associated with a decrease in δ-platelet count (coefficient, -1.741; standard error, 0.740; p = 0.019), and an increase in δ-serum bilirubin (coefficient, 0.054; standard error, 0.021; p = 0.009). In contrast, it was not associated with δ-creatinine (coefficient, 0.008; standard error, 0.010; p = 0.434) or the δ-P/F ratio (coefficient, -0.797; standard error, 1.858; p = 0.668). The hourly delay of antibiotic therapy was associated with decreased platelet count and increased serum bilirubin concentration in critically ill septic patients during the first three days of ED admission.
| S-EPMC6406307 | biostudies-literature
Project description:ObjectivesTo determine clinician accuracy in the identification and prediction of multiple organ dysfunction syndrome.DesignProspective cohort study.SettingUniversity of Michigan's C.S. Mott Children's Hospital PICU.PatientsPatients admitted to the PICU with an anticipated PICU length of stay greater than 48 hours.InterventionsNone.Measurements and main resultsFor each patient, the clinical team (attending, fellow, resident/nurse practitioner) was surveyed regarding existing and anticipated organ dysfunction. The primary outcomes were clinicians' accuracy at identifying multiple organ dysfunction syndrome and predicting new or progressive multiple organ dysfunction syndrome, compared to the objective assessment of multiple organ dysfunction syndrome using Proulx criteria. We also measured sensitivity, specificity, negative and positive predictive values, and negative and positive likelihood ratios of clinician assessments. We tested for differences in accuracy by clinician type using chi-square tests. Clinicians rated their confidence in prediction on a 5-point Likert scale. There were 476 eligible PICU admissions, for whom 1,218 surveys were completed. Multiple organ dysfunction syndrome was present in 89 patients (18.7%) at enrollment, and new or progressive multiple organ dysfunction syndrome occurred in 39 (8.2%). Clinicians correctly identified multiple organ dysfunction syndrome with 79.9% accuracy and predicted additional organ dysfunction with 82.6% accuracy. However, the positive and negative likelihood ratios for new or progressive multiple organ dysfunction syndrome prediction were 3.0 and 0.7, respectively, indicating a weak relationship between the clinician prediction and development of new or progressive multiple organ dysfunction syndrome. The positive predictive value of new or progressive multiple organ dysfunction syndrome prediction was just 22.1%. We found no differences in accuracy by clinician type for either identification of multiple organ dysfunction syndrome (80.2% vs 78.2% vs 81.0%; p = 0.57) or prediction of new or progressive multiple organ dysfunction syndrome (84.8% vs 82.8% vs 80.3%; p = 0.26) for attendings, fellows, and residents/nurse practitioners, respectively. There was a weak correlation between the confidence and accuracy of prediction (pairwise correlation coefficient, 0.26; p < 0.001).ConclusionsPICU clinicians correctly identified multiple organ dysfunction syndrome and predicted new or progressive multiple organ dysfunction syndrome with 80% accuracy. However, only 8% of patients developed new or progressive multiple organ dysfunction syndrome, so accuracy was largely due to true negative predictions. The positive predictive value for new or progressive multiple organ dysfunction syndrome prediction was just 22%. Accuracy did not differ by clinician type, but was correlated with self-rated confidence and was higher for negative predictions.
| S-EPMC7959260 | biostudies-literature
Project description:ABSTRACT Introduction Up to 70% of intermittent hemodialysis (IHD) sessions in critically ill patients are complicated by hemodynamic instability. Although several clinical characteristics have been associated with hemodynamic instability during IHD, the discriminatory capacity of predicting such events during IHD sessions is less defined. In the present study, we aimed to analyse endothelium-related biomarkers collected before IHD sessions and their capacity to predict hemodynamic instability related to IHD in critically ill patients. Methods In this prospective observational study, we enrolled adult critically ill patients with acute kidney injury who required fluid removal with IHD. We screened each included patient daily for IHD sessions. Thirty minutes before each IHD session, each patient had a 5-mL blood collection for measurement of endothelial biomarkers—vascular cell adhesion molecule-1 (VCAM-1), angiopoietin-1 and -2 (AGPT1 and AGPT2) and syndecan-1. Hemodynamic instability during IHD was the main outcome. Analyses were adjusted for variables already known to be associated with hemodynamic instability during IHD. Results Plasma syndecan-1 was the only endothelium-related biomarker independently associated with hemodynamic instability. The accuracy of syndecan-1 for predicting hemodynamic instability during IHD was moderate [area under the receiver operating characteristic curve 0.78 (95% confidence interval 0.68–0.89)]. The addition of syndecan-1 improved the discrimination capacity of a clinical model from 0.67 to 0.82 (P < .001) and improved risk prediction, as measured by net reclassification improvement. Conclusion Syndecan-1 is associated with hemodynamic instability during IHD in critically ill patients. It may be useful to identify patients who are at increased risk for such events and suggests that endothelial glycocalyx derangement is involved in the pathophysiology of IHD-related hemodynamic instability.
| S-EPMC10310513 | biostudies-literature