Association of early inflammatory parameters after subarachnoid hemorrhage with functional outcome: A prospective cohort study

Höllig, Anke; Remmel, Daniel; Stoffel‐Wagner, Birgit; Schubert, Gerrit Alexander; Coburn, Mark; Clusmann, Hans

doi:10.1016/j.clineuro.2015.08.030

Cited by 40 publications

(36 citation statements)

References 36 publications

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“…Neuroinflammation seems to have properties, which can be considered in some cases as protective, but in others, as deleterious, e.g., depending on the magnitude of the response, time-point after the ictus when activation of the inflammatory response occurs, and the type of cells recruited in the response (27). Hence, it is not surprising that there is inconsistency regarding the prognostic value of many inflammatory biomarkers such as IL-6 and HMGB1 after aSAH (19, 25, 28, 29). Nevertheless, although no biomarker has been identified, these studies have increased our understanding of the inflammatory process in aSAH and, in fact, also novel inflammatory biomarkers are claimed to have some prognostic potential, e.g., toll-like receptor 4 (30).…”

Section: Discussionmentioning

confidence: 99%

Plasma Soluble Urokinase-Type Plasminogen Activator Receptor Is Not Associated with Neurological Outcome in Patients with Aneurysmal Subarachnoid Hemorrhage

et al. 2017

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ObjectAneurysmal subarachnoid hemorrhage (aSAH) is a common cause of death or long-term disability. Despite advances in neurocritical care, there is still only a very limited ability to monitor the development of secondary brain injury or to predict neurological outcome after aSAH. Soluble urokinase-type plasminogen activator receptor (suPAR) has shown potential as a prognostic and as an inflammatory biomarker in a wide range of critical illnesses since it displays an association with overall immune system activation. This is the first time that suPAR has been evaluated as a prognostic biomarker in aSAH.MethodsIn this prospective population-based study, plasma suPAR levels were measured in aSAH patients (n = 47) for up to 5 days. suPAR was measured at 0, 12, and 24 h after patient admission to the intensive care unit (ICU) and daily thereafter until he/she was transferred from the ICU. The patients’ neurological outcome was evaluated with the modified Rankin Scale (mRS) at 6 months after aSAH.ResultssuPAR levels (n = 47) during the first 24 h after aSAH were comparable in groups with a favorable (mRS 0–2) or an unfavorable (mRS 3–6) outcome. suPAR levels during the first 24 h were not associated with the findings in the primary brain CT, with acute hydrocephalus, or with antimicrobial medication use during 5-days’ follow-up. suPAR levels were associated with generally accepted inflammatory biomarkers (C-reactive protein, leukocyte count).ConclusionPlasma suPAR level was not associated with either neurological outcome or selected clinical conditions. While suPAR is a promising biomarker for prognostication in several conditions requiring intensive care, it did not reveal any value as a prognostic biomarker after aSAH.

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Section: Discussionmentioning

confidence: 99%

Plasma Soluble Urokinase-Type Plasminogen Activator Receptor Is Not Associated with Neurological Outcome in Patients with Aneurysmal Subarachnoid Hemorrhage

et al. 2017

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“…IL-6, PCT, CRP levels, and leukocyte counts were collected, as these systemic inflammatory parameters have been reported to correlate with occurrence of ischemic complications and/or poor clinical outcome. 9,12,15,16,18 Patients underwent routine follow-up in the neurosurgical outpatient clinics 1 year after aSAH. The functional outcome was assessed according to the Glasgow Outcome Scale (GOS).…”

Section: Databasementioning

confidence: 99%

Decision tree analysis in subarachnoid hemorrhage: prediction of outcome parameters during the course of aneurysmal subarachnoid hemorrhage using decision tree analysis

Hostettler

Muroi

Richter

et al. 2018

Journal of Neurosurgery

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OBJECTIVE The aim of this study was to create prediction models for outcome parameters by decision tree analysis based on clinical and laboratory data in patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS The database consisted of clinical and laboratory parameters of 548 patients with aSAH who were admitted to the Neurocritical Care Unit, University Hospital Zurich. To examine the model performance, the cohort was randomly divided into a derivation cohort (60% [n = 329]; training data set) and a validation cohort (40% [n = 219]; test data set). The classification and regression tree prediction algorithm was applied to predict death, functional outcome, and ventriculoperitoneal (VP) shunt dependency. Chi-square automatic interaction detection was applied to predict delayed cerebral infarction on days 1, 3, and 7. RESULTS The overall mortality was 18.4%. The accuracy of the decision tree models was good for survival on day 1 and favorable functional outcome at all time points, with a difference between the training and test data sets of < 5%. Prediction accuracy for survival on day 1 was 75.2%. The most important differentiating factor was the interleukin-6 (IL-6) level on day 1. Favorable functional outcome, defined as Glasgow Outcome Scale scores of 4 and 5, was observed in 68.6% of patients. Favorable functional outcome at all time points had a prediction accuracy of 71.1% in the training data set, with procalcitonin on day 1 being the most important differentiating factor at all time points. A total of 148 patients (27%) developed VP shunt dependency. The most important differentiating factor was hyperglycemia on admission. CONCLUSIONS The multiple variable analysis capability of decision trees enables exploration of dependent variables in the context of multiple changing influences over the course of an illness. The decision tree currently generated increases awareness of the early systemic stress response, which is seemingly pertinent for prognostication.

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“…Although controversial, some groups have correlated cytokine concentrations measured in blood/plasma in the acute and chronic setting of patients with TBI and SAH to functional outcome (46–48). This suggests that, while these mediators may represent non-brain-specific inflammatory activity, systemic inflammation is triggered by brain injury, potentially having long-term sequelae such as stimulating an acute-phase response in the liver (49).…”

Section: Cytokine and Chemokine Monitoring In Acute Brain Injurymentioning

confidence: 99%

Monitoring the Neuroinflammatory Response Following Acute Brain Injury

et al. 2017

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Traumatic brain injury (TBI) and subarachnoid hemorrhage (SAH) are major contributors to morbidity and mortality. Following the initial insult, patients may deteriorate due to secondary brain damage. The underlying molecular and cellular cascades incorporate components of the innate immune system. There are different approaches to assess and monitor cerebral inflammation in the neuro intensive care unit. The aim of this narrative review is to describe techniques to monitor inflammatory activity in patients with TBI and SAH in the acute setting. The analysis of pro- and anti-inflammatory cytokines in compartments of the central nervous system (CNS), including the cerebrospinal fluid and the extracellular fluid, represent the most common approaches to monitor surrogate markers of cerebral inflammatory activity. Each of these compartments has a distinct biology that reflects local processes and the cross-talk between systemic and CNS inflammation. Cytokines have been correlated to outcomes as well as ongoing, secondary injury progression. Alongside the dynamic, focal assay of humoral mediators, imaging, through positron emission tomography, can provide a global in vivo measurement of inflammatory cell activity, which reveals long-lasting processes following the initial injury. Compared to the innate immune system activated acutely after brain injury, the adaptive immune system is likely to play a greater role in the chronic phase as evidenced by T-cell-mediated autoreactivity toward brain-specific proteins. The most difficult aspect of assessing neuroinflammation is to determine whether the processes monitored are harmful or beneficial to the brain as accumulating data indicate a dual role for these inflammatory cascades following injury. In summary, the inflammatory component of the complex injury cascade following brain injury may be monitored using different modalities. Using a multimodal monitoring approach can potentially aid in the development of therapeutics targeting different aspects of the inflammatory cascade and improve the outcome following TBI and SAH.

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Association of early inflammatory parameters after subarachnoid hemorrhage with functional outcome: A prospective cohort study

Cited by 40 publications

References 36 publications

Plasma Soluble Urokinase-Type Plasminogen Activator Receptor Is Not Associated with Neurological Outcome in Patients with Aneurysmal Subarachnoid Hemorrhage

Plasma Soluble Urokinase-Type Plasminogen Activator Receptor Is Not Associated with Neurological Outcome in Patients with Aneurysmal Subarachnoid Hemorrhage

Decision tree analysis in subarachnoid hemorrhage: prediction of outcome parameters during the course of aneurysmal subarachnoid hemorrhage using decision tree analysis

Monitoring the Neuroinflammatory Response Following Acute Brain Injury

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