Year in review 2010: Critical Care--Multiple organ dysfunction and sepsis.
Ontology highlight
ABSTRACT:
SUBMITTER: de Montmollin E
PROVIDER: S-EPMC3388699 | biostudies-literature | 2011
REPOSITORIES: biostudies-literature
Publications
Year in review 2010: Critical Care--Multiple organ dysfunction and sepsis.
de Montmollin Etienne E Annane Djillali D
Critical care (London, England) 20111205 6
This review summarizes new insights in the pathophysiologic implications of inflammation and microvascular alterations in organ dysfunction, as well as genetic factor contribution, from clinical and experimental studies that were published in 2010 in Critical Care in the fields of multiple organ dysfunction and sepsis. New diagnostic and prognostic markers of organ dysfunction are presented. Evaluations of novel therapeutic strategies, including implementation of international guidelines, modula ...[more]
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Project description:Sepsis-induced multiple organ dysfunction syndrome (MODS) is a major cause of morbidity and mortality in critically ill patients and remains impervious to most therapeutic interventions. We utilized a clinically relevant murine model of MODS induced by ventilator-associated pneumonia to systematically delineate pathways dysregulated in lung, liver, and kidney. We focused on processes commonly activated across injured organs and constructed a MODS-associated network based on connectivity among the gene members of these functionally coherent pathways. Our analyses led to the identification of several putative drivers of MODS whose expression was regulated by epidermal growth factor receptor. Our unbiased, integrative method is a promising approach to unravel mechanisms in system-wide disorders afflicting multiple compartments such as sepsis-induced MODS, and guide the discovery of novel putative therapeutic targets.
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Project description:Exposure to traumatic or infectious insults results in a rapid activation of the complement cascade as major fluid defense system of innate immunity. The complement system acts as a master alarm system during the molecular danger response after trauma and significantly contributes to the clearance of DAMPs and PAMPs. However, depending on the origin and extent of the damaged macro- and micro -milieu, the complement system can also be either excessively activated or inhibited. In both cases, this can lead to a maladaptive immune response and subsequent multiple cellular and organ dysfunction. The arsenal of complement-specific drugs offers promising strategies for various critical conditions after trauma, hemorrhagic shock, sepsis, and multiple organ failure. The imbalanced immune response needs to be detected in a rational and real-time manner before the translational therapeutic potential of these drugs can be fully utilized. Overall, the temporal-spatial complement response after tissue trauma and during sepsis remains somewhat enigmatic and demands a clinical triad: reliable tissue damage assessment, complement activation monitoring, and potent complement targeting to highly specific rebalance the fluid phase innate immune response.
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Project description:BackgroundSepsis remains a complex medical problem and a major challenge in healthcare. Diagnostics and outcome predictions are focused on physiological parameters with less consideration given to patients' medical background. Given the aging population, not only are diseases becoming increasingly prevalent but occur more frequently in combinations ("multimorbidity"). We hypothesized the existence of patient subgroups in critical care with distinct multimorbidity states. We further hypothesize that certain multimorbidity states associate with higher rates of organ failure, sepsis, and mortality co-occurring with these clinical problems.MethodsWe analyzed 36,390 patients from the open source Medical Information Mart for Intensive Care III (MIMIC III) dataset. Morbidities were defined based on Elixhauser categories, a well-established scheme distinguishing 30 classes of chronic diseases. We used latent class analysis to identify distinct patient subgroups based on demographics, admission type, and morbidity compositions and compared the prevalence of organ dysfunction, sepsis, and inpatient mortality for each subgroup.ResultsWe identified six clinically distinct multimorbidity subgroups labeled based on their dominant Elixhauser disease classes. The "cardiopulmonary" and "cardiac" subgroups consisted of older patients with a high prevalence of cardiopulmonary conditions and constituted 6.1% and 26.4% of study cohort respectively. The "young" subgroup included 23.5% of the cohort composed of young and healthy patients. The "hepatic/addiction" subgroup, constituting 9.8% of the cohort, consisted of middle-aged patients (mean age of 52.25, 95% CI 51.85-52.65) with the high rates of depression (20.1%), alcohol abuse (47.75%), drug abuse (18.2%), and liver failure (67%). The "complicated diabetics" and "uncomplicated diabetics" subgroups constituted 9.4% and 24.8% of the study cohort respectively. The complicated diabetics subgroup demonstrated higher rates of end-organ complications (88.3% prevalence of renal failure). Rates of organ dysfunction and sepsis ranged 19.6-69% and 12.5-46.7% respectively in the six subgroups. Mortality co-occurring with organ dysfunction and sepsis ranges was 8.4-23.8% and 11.7-27.4% respectively. These adverse outcomes were most prevalent in the hepatic/addiction subgroup.ConclusionWe identify distinct multimorbidity states that associate with relatively higher prevalence of organ dysfunction, sepsis, and co-occurring mortality. The findings promote the incorporation of multimorbidity in healthcare models and the shift away from the current single-disease paradigm in clinical practice, training, and trial design.
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Project description:: In sepsis, quiescent blood vessels become leaky and inflamed by mechanisms that are incompletely understood. We hypothesized that angiopoietin-2, a partial antagonist of the endothelium-stabilizing receptor Tie-2 secreted by endothelium, contributes to adverse outcomes in this disease.: Laboratory and animal research.: Research laboratories and Emergency Department of Beth Israel Deaconess Medical Center, Boston, MA.: Angiopoietin-2 heterozygous mice, emergency department patients.: Mice with one functional angiopoietin-2 allele developed milder kidney and lung injury, less tissue inflammation, and less vascular leakage compared to wild-type counterparts. Heterozygotes experienced >40% absolute survival advantage following two different models of sepsis (p = .004 and .018). In human subjects presenting to our emergency department with suspected infection (n = 270 combined), circulating angiopoietin-2 was markedly elevated within the first hour of clinical care. First-hour angiopoietin-2 concentrations were proportional to current disease severity (p < .0001), rose further over time in eventual nonsurvivors (p < .0001), and predicted the future occurrence of shock (p < .0001) or death (p < .0001) in the original cohort and an independent validation group. Finally, septic human serum disrupted the barrier function of microvascular endothelial cells, an effect fully neutralized by an angiopoietin-2 monoclonal antibody.: We conclude that angiopoietin-2 induction precedes and contributes to the adverse outcomes in sepsis, opening a new avenue for therapeutic investigation.
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Project description:MotivationSepsis is a leading cause of death and disability in children globally, accounting for ∼3 million childhood deaths per year. In pediatric sepsis patients, the multiple organ dysfunction syndrome (MODS) is considered a significant risk factor for adverse clinical outcomes characterized by high mortality and morbidity in the pediatric intensive care unit. The recent rapidly growing availability of electronic health records (EHRs) has allowed researchers to vastly develop data-driven approaches like machine learning in healthcare and achieved great successes. However, effective machine learning models which could make the accurate early prediction of the recovery in pediatric sepsis patients from MODS to a mild state and thus assist the clinicians in the decision-making process is still lacking.ResultsThis study develops a machine learning-based approach to predict the recovery from MODS to zero or single organ dysfunction by 1 week in advance in the Swiss Pediatric Sepsis Study cohort of children with blood-culture confirmed bacteremia. Our model achieves internal validation performance on the SPSS cohort with an area under the receiver operating characteristic (AUROC) of 79.1% and area under the precision-recall curve (AUPRC) of 73.6%, and it was also externally validated on another pediatric sepsis patients cohort collected in the USA, yielding an AUROC of 76.4% and AUPRC of 72.4%. These results indicate that our model has the potential to be included into the EHRs system and contribute to patient assessment and triage in pediatric sepsis patient care.Availability and implementationCode available at https://github.com/BorgwardtLab/MODS-recovery. The data underlying this article is not publicly available for the privacy of individuals that participated in the study.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:BackgroundSepsis is a heterogeneous syndrome, and the identification of clinical subphenotypes is essential. Although organ dysfunction is a defining element of sepsis, subphenotypes of differential trajectory are not well studied. We sought to identify distinct Sequential Organ Failure Assessment (SOFA) score trajectory-based subphenotypes in sepsis.MethodsWe created 72-h SOFA score trajectories in patients with sepsis from four diverse intensive care unit (ICU) cohorts. We then used dynamic time warping (DTW) to compute heterogeneous SOFA trajectory similarities and hierarchical agglomerative clustering (HAC) to identify trajectory-based subphenotypes. Patient characteristics were compared between subphenotypes and a random forest model was developed to predict subphenotype membership at 6 and 24 h after being admitted to the ICU. The model was tested on three validation cohorts. Sensitivity analyses were performed with alternative clustering methodologies.ResultsA total of 4678, 3665, 12,282, and 4804 unique sepsis patients were included in development and three validation cohorts, respectively. Four subphenotypes were identified in the development cohort: Rapidly Worsening (n = 612, 13.1%), Delayed Worsening (n = 960, 20.5%), Rapidly Improving (n = 1932, 41.3%), and Delayed Improving (n = 1174, 25.1%). Baseline characteristics, including the pattern of organ dysfunction, varied between subphenotypes. Rapidly Worsening was defined by a higher comorbidity burden, acidosis, and visceral organ dysfunction. Rapidly Improving was defined by vasopressor use without acidosis. Outcomes differed across the subphenotypes, Rapidly Worsening had the highest in-hospital mortality (28.3%, P-value < 0.001), despite a lower SOFA (mean: 4.5) at ICU admission compared to Rapidly Improving (mortality:5.5%, mean SOFA: 5.5). An overall prediction accuracy of 0.78 (95% CI, [0.77, 0.8]) was obtained at 6 h after ICU admission, which increased to 0.87 (95% CI, [0.86, 0.88]) at 24 h. Similar subphenotypes were replicated in three validation cohorts. The majority of patients with sepsis have an improving phenotype with a lower mortality risk; however, they make up over 20% of all deaths due to their larger numbers.ConclusionsFour novel, clinically-defined, trajectory-based sepsis subphenotypes were identified and validated. Identifying trajectory-based subphenotypes has immediate implications for the powering and predictive enrichment of clinical trials. Understanding the pathophysiology of these differential trajectories may reveal unanticipated therapeutic targets and identify more precise populations and endpoints for clinical trials.
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2023-07-07 | GSE236877 | GEO
Project description:OBJECTIVES:To describe the epidemiology, morbidity, and mortality of new or progressive multiple organ dysfunction syndrome in children with severe sepsis. DESIGN:Secondary analysis of a prospective, cross-sectional, point prevalence study. SETTING:International, multicenter PICUs. PATIENTS:Pediatric patients with severe sepsis identified on five separate days over a 1-year period. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Of 567 patients from 128 PICUs in 26 countries enrolled, 384 (68%) developed multiple organ dysfunction syndrome within 7 days of severe sepsis recognition. Three hundred twenty-seven had multiple organ dysfunction syndrome on the day of sepsis recognition. Ninety-one of these patients developed progressive multiple organ dysfunction syndrome, whereas an additional 57 patients subsequently developed new multiple organ dysfunction syndrome, yielding a total proportion with severe sepsis-associated new or progressive multiple organ dysfunction syndrome of 26%. Hospital mortality in patients with progressive multiple organ dysfunction syndrome was 51% compared with patients with new multiple organ dysfunction syndrome (28%) and those with single-organ dysfunction without multiple organ dysfunction syndrome (10%) (p < 0.001). Survivors of new or progressive multiple organ dysfunction syndrome also had a higher frequency of moderate to severe disability defined as a Pediatric Overall Performance Category score of greater than or equal to 3 and an increase of greater than or equal to 1 from baseline: 22% versus 29% versus 11% for progressive, new, and no multiple organ dysfunction syndrome, respectively (p < 0.001). CONCLUSIONS:Development of new or progressive multiple organ dysfunction syndrome is common (26%) in severe sepsis and is associated with a higher risk of morbidity and mortality than severe sepsis without new or progressive multiple organ dysfunction syndrome. Our data support the use of new or progressive multiple organ dysfunction syndrome as an important outcome in trials of pediatric severe sepsis although efforts are needed to validate whether reducing new or progressive multiple organ dysfunction syndrome leads to improvements in more definitive morbidity and mortality endpoints.
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