Immune-Inflammatory, Metabolic, Oxidative, and Nitrosative Stress Biomarkers Predict Acute Ischemic Stroke and Short-Term Outcome

Alfieri, Daniela Frizon; Lehmann, Márcio Francisco; Flauzino, Tamires; Araújo, Maria Caroline Martins de; Pivoto, Nicolas; Tirolla, Rafaele Maria; Simão, Andréa Name Colado; Maes, Michael; Reiche, Edna Maria Vissoci

doi:10.1007/s12640-020-00221-0

Cited by 24 publications

(30 citation statements)

References 81 publications

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“…Although studies have shown that the ratio of nomogram neutrophils to lymphocytes can predict stroke-related infections, our work includes constructing and verifying larger sample models, and the results seem to be more accurate (1,38). Multimarker clinical studies have shown that panel of laboratory biomarkers incorporated male sex, systolic blood pressure, glucose, nitric oxide metabolites, lipid hydroperoxides, 25-hydroxyvitamin D, IL-6, and WBC with the sensitivity of 86.2% and specificity of 93.0% are related to ischemic stroke and predict a poor outcome at 3-month follow-up (39). In a recent study, observing the diagnostic accuracy of lymph node metastasis in colorectal cancer, the training accuracy of the radiomics nomogram was lower than 80% (40).…”

Section: Discussionmentioning

confidence: 97%

Risk Estimation of Infectious and Inflammatory Disorders in Hospitalized Patients With Acute Ischemic Stroke Using Clinical-Lab Nomogram

Huang

Pang

et al. 2021

Front. Neurol.

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Background: Infections after acute ischemic stroke are common and likely to complicate the clinical course and negatively affect patient outcomes. Despite the development of various risk factors and predictive models for infectious and inflammatory disorders (IAID) after stroke, more objective and easily obtainable predictors remain necessary. This study involves the development and validation of an accessible, accurate nomogram for predicting in-hospital IAID in patients with acute ischemic stroke (AIS).Methods: A retrospective cohort of 2,257 patients with AIS confirmed by neurological examination and radiography was assessed. The International Statistical Classification of Diseases and Health related Problem's definition was used for IAID. Data was obtained from two hospitals between January 2016 and March 2020.Results: The incidence of IAID was 19.8 and 20.8% in the derivation and validation cohorts, respectively. Using an absolute shrinkage and selection operator (LASSO) algorithm, four biochemical blood predictors and four clinical indicators were optimized from fifty-five features. Using a multivariable analysis, four predictors, namely age (adjusted odds ratio, 1.05; 95% confidence interval [CI], 1.038–1.062; p < 0.001), comatose state (28.033[4.706–536.403], p = 0.002), diabetes (0.417[0.27–0.649], p < 0.001), and congestive heart failure (CHF) (5.488[2.451–12.912], p < 0.001) were found to be risk factors for IAID. Furthermore, neutrophil, monocyte, hemoglobin, and high-sensitivity C-reactive protein were also found to be independently associated with IAID. Consequently, a reliable clinical-lab nomogram was constructed to predict IAID in our study (C-index value = 0.83). The results of the ROC analysis were consistent with the calibration curve analysis. The decision curve demonstrated that the clinical-lab model added more net benefit than either the lab-score or clinical models in differentiating IAID from AIS patients.Conclusions: The clinical-lab nomogram predicted IAID in patients with acute ischemic stroke. As a result, this nomogram can be used for identification of high-risk patients and to further guide clinical decisions.

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Section: Discussionmentioning

confidence: 97%

Risk Estimation of Infectious and Inflammatory Disorders in Hospitalized Patients With Acute Ischemic Stroke Using Clinical-Lab Nomogram

Huang

Pang

et al. 2021

Front. Neurol.

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“…Our finding that ferritin (FTH1) was not connected in the network of blood-based biomarkers predictive of stroke outcomes deserves comment. In recent studies, ferritin in acute stroke patients was related to baseline rather than long-term disability [12,19,20]. It has been shown in the animal model that increased body iron indicated by ferritin worsens ischemic damage induced by transient ischemia and early reperfusion [21].…”

Section: Interaction Network and Gene Ontology Analysis Of Blood Biomarkers Of Stroke Corroborate Their Known Rolesmentioning

confidence: 99%

Protein Biomarkers in Blood Reflect the Interrelationships between Stroke Outcome, Inflammation, Coagulation, Adhesion, Senescence and Cancer

Fuellen¹,

Böhmert²,

Henze³

et al. 2021

Preprint

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The most important predictors for outcomes after ischemic stroke, that is, for health deterioration and death, are chronological age and stroke severity; gender, genetics and lifestyle / environmental factors also play a role. Of all these, only the latter can be influenced after the event, even though recurrent stroke may be prevented by antiaggregant/anticoagulant therapy, angioplasty of high-grade stenoses, and treatment of cardiovascular risk factors. Moreover, blood cell composition and protein biomarkers such as C-reactive protein or interleukins in serum are frequently considered as biomarkers of outcome. We surveyed protein biomarkers that were reported to be predictive for outcome after ischemic stroke, specifically considering biomarkers that predict long-term outcome (≥3 months) and that are measured over the first days following the event. We classified the protein biomarkers as immune‑inflammatory, coagulation-related, and adhesion-related biomarkers. Some of these biomarkers are closely related to cellular senescence and, in particular, to the inflammatory processes that can be triggered by senescent cells. Moreover, the processes that underlie inflammation, hypercoagulation and cellular senescence connect stroke to cancer, and biomarkers of cancer-associated thromboembolism, as well as of sarcopenia, overlap strongly with the biomarkers discussed here. Finally, we demonstrate that most of the outcome-predicting protein biomarkers form a close-meshed functional interaction network, suggesting that the outcome after stroke is partially determined by an interplay of molecular processes relating to inflammation, coagulation, cell adhesion and cellular senescence.

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“…Inflammation promotes infarct enlargement and is accountable for its resolution with implications for remodeling and repair ( Lambertsen et al, 2019 ). This conflicting outcome may be due to genetic variation in molecules involved in inflammatory and metabolic pathways ( Alfieri et al, 2020 ). Although experimental evidence suggests that targeting some of these inflammatory cytokines holds promise for treating ischemic stroke ( Lambertsen et al, 2019 ), studies on the connection between circulating inflammatory cytokines and stroke risk remain scarce.…”

Section: Introductionmentioning

confidence: 99%

Inflammatory Cytokines and Risk of Ischemic Stroke: A Mendelian Randomization Study

Wang

et al. 2022

Front. Pharmacol.

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Background: Observational studies have revealed the association between some inflammatory cytokines and the occurrence of ischemic stroke, but the causal relationships remain unclear.Methods: We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal effects of thirty inflammatory cytokines and the risk of ischemic stroke. For exposure data, we collected genetic variants associated with inflammatory cytokines as instrumental variables (IVs) from a genome-wide association study (GWAS) meta-analysis from Finland (sample size up to 8,293). For the outcome data, we collected summary data of ischemic stroke from a large-scale GWAS meta-analysis involved 17 studies (34,217 cases and 406,111 controls). We further performed a series of sensitivity analyses as validation of primary MR results.Results: According to the primary MR estimations and further sensitivity analyses, we established one robust association after Bonferroni correction: the odds ratio (95% CI) per unit change in genetically increased IL-4 was 0.84 (0.89–0.95) for ischemic stroke. The chemokine MCP3 showed a nominally significant association with ischemic stroke risk (OR: 0.93, 95% CI: 0.88–0.99, unadjusted p < 0.05). There was no evidence of a causal effect of other inflammatory cytokines and the risk of ischemic stroke.Conclusions: Our study suggested that genetically increased IL-4 levels showed a protective effect on the risk of ischemic stroke, which provides important new insights into the potential therapeutic target for preventing ischemic stroke.

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Immune-Inflammatory, Metabolic, Oxidative, and Nitrosative Stress Biomarkers Predict Acute Ischemic Stroke and Short-Term Outcome

Cited by 24 publications

References 81 publications

Risk Estimation of Infectious and Inflammatory Disorders in Hospitalized Patients With Acute Ischemic Stroke Using Clinical-Lab Nomogram

Risk Estimation of Infectious and Inflammatory Disorders in Hospitalized Patients With Acute Ischemic Stroke Using Clinical-Lab Nomogram

Protein Biomarkers in Blood Reflect the Interrelationships between Stroke Outcome, Inflammation, Coagulation, Adhesion, Senescence and Cancer

Inflammatory Cytokines and Risk of Ischemic Stroke: A Mendelian Randomization Study

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