scholarly journals Biomarkers of Coagulation and Inflammation in COVID-19–Associated Ischemic Stroke

Stroke ◽  
2021 ◽  
Author(s):  
Charles Esenwa ◽  
Natalie T. Cheng ◽  
Jorge Luna ◽  
Joshua Willey ◽  
Amelia K. Boehme ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cluster Analysis ◽  
Ischemic Stroke ◽  
Lactate Dehydrogenase ◽  
Healthcare Systems ◽  
C Reactive Protein ◽  
Blood Cell Count ◽  
Reactive Protein ◽  
Separate Cohort ◽  
D Dimer

Background and Purpose: We sought to determine if biomarkers of inflammation and coagulation can help define coronavirus disease 2019 (COVID-19)–associated ischemic stroke as a novel acute ischemic stroke (AIS) subtype. Methods: We performed a machine learning cluster analysis of common biomarkers in patients admitted with severe acute respiratory syndrome coronavirus 2 to determine if any were associated with AIS. Findings were validated using aggregate data from 3 large healthcare systems. Results: Clustering grouped 2908 unique patient encounters into 4 unique biomarker phenotypes based on levels of c-reactive protein, D-dimer, lactate dehydrogenase, white blood cell count, and partial thromboplastin time. The most severe cluster phenotype had the highest prevalence of AIS (3.6%, P <0.001), in-hospital AIS (53%, P <0.002), severe AIS (31%, P =0.004), and cryptogenic AIS (73%, P <0.001). D-dimer was the only biomarker independently associated with prevalent AIS with quartile 4 having an 8-fold higher risk of AIS compared to quartile 1 ( P =0.005), a finding that was further corroborated in a separate cohort of 157 patients hospitalized with COVID-19 and AIS. Conclusions: COVID-19–associated ischemic stroke may be related to COVID-19 illness severity and associated coagulopathy as defined by increasing D-dimer burden.

scholarly journals C-Reactive Protein and White Blood Cell Count in Non-Infective Acute Ischemic Stroke Patients Treated with Intravenous Thrombolysis

2021 ◽  
Vol 10 (8) ◽  
pp. 1610
Author(s):  
Marcin Wnuk ◽  
Justyna Derbisz ◽  
Leszek Drabik ◽  
Agnieszka Slowik
Keyword(s):  
Ischemic Stroke ◽  
Blood Cell ◽  
Acute Ischemic Stroke ◽  
Cell Count ◽  
White Blood Cell Count ◽  
White Blood Cell ◽  
Intravenous Thrombolysis ◽  
C Reactive Protein ◽  
Blood Cell Count ◽  
Reactive Protein

Background: Previous studies on inflammatory biomarkers in acute ischemic stroke (AIS) produced divergent results. We evaluated whether C-reactive protein (CRP) and white blood cell count (WBC) measured fasting 12–24 h after intravenous thrombolysis (IVT) were associated with outcome in AIS patients without concomitant infection. Methods: The study included 352 AIS patients treated with IVT. Excluded were patients with community-acquired or nosocomial infection. Outcome was measured on discharge and 90 days after stroke onset with the modified Rankin scale (mRS) and defined as poor outcome (mRS 3–6) or death (mRS = 6). Results: Final analysis included 158 patients (median age 72 years (interquartile range 63-82), 53.2% (n = 84) women). Poor outcome on discharge and at day 90 was 3.8-fold and 5.8-fold higher for patients with CRP ≥ 8.65 mg/L (fifth quintile of CRP), respectively, compared with first quintile (<1.71 mg/L). These results remained significant after adjustment for potential confounders (odds ratio (OR) on discharge = 10.68, 95% CI: 2.54–44.83, OR at day 90 after stroke = 7.21, 95% CI: 1.44–36.00). In-hospital death was 6.3-fold higher for patients with fifth quintile of CRP as compared with first quintile and remained independent from other variables (OR = 4.79, 95% CI: 1.29–17.88). Independent predictors of 90-day mortality were WBC < 6.4 × 109 /L (OR = 5.00, 95% CI: 1.49–16.78), baseline National Institute of Health Stroke Scale (NIHSS) score (OR = 1.13 per point, 95% CI: 1.01–1.25) and bleeding brain complications (OR = 5.53, 95% CI: 1.59–19.25) but not CRP ≥ 8.65 mg/L. Conclusions: Non-infective CRP levels are an independent risk factor for poor short- and long-term outcomes and in-hospital mortality in AIS patients treated with IVT. Decreased WBC but not CRP is a predictor for 90-day mortality.

The role of IL-6 receptor inhibitor treatment in critical patient monitoring with COVID-19

2021 ◽  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Lactate Dehydrogenase ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Group 2 ◽  
D Dimer

Objectives: The COVID-19 disease can manifest itself with acute respiratory distress syndrome, renal failure, and septic shock in critically ill patients. There are opinions that there is a correlation between high IL-6 levels and disease severity. In our intensive care unit, we evaluated the changes in the laboratory data and radiological involvement severity of our patients who underwent tocilizumab treatment and examined the appropriate laboratory parameter in the treatment follow-up and its effect on survival. Methods: In the critical patient follow-up of COVID-19, 17 of the 23 patients treated with tocilizumab had a mortal course (Group 1) and the remaining 6 (Group 2) were. The C-reactive protein, lactate dehydrogenase, IL-6, D-dimer, procalcitonin, albumin, and ferritin values, which were routinely screened in our clinic on the day of tocilizumab treatment and the 5th day after, were recorded. Both the change between the two groups and the change between days 1 and 5 were analyzed. Results: A total of 23 patients (55.35 ± 13.31 years) were included in the study. The computed tomography severity score assessed at the intensive care unit admission was statistically significantly higher in Group 2. The procalcitonin and lactate dehydrogenase values measured on day 5 after tocilizumab were significantly lower in Group 2. On the 5th day after treatment, the levels of C-reactive protein, ferritin, chest X-rays, IL-6 and D-dimer statistically significantly changed compared to the first day of the treatment. In correlation with the decrease in PCT as of the 5th day after tocilizumab administration, an increasing tendency was observed in 28-day survival. Conclusion: This study demonstrated that tocilizumab treatment may positively contribute to the treatment by decreasing cytokine levels. PCT and LDH follow-up before and after treatment in critically ill patients who are receiving tocilizumab treatment can give an idea about survival.

Diagnostic value of combination serum assay of lactate dehydrogenase, D-dimer, and C-reactive protein for uterine leiomyosarcoma

2018 ◽  
Vol 45 (1) ◽  
pp. 189-194 ◽  
Author(s):  
Yoshiko Nishigaya ◽  
Yoichi Kobayashi ◽  
Yukiko Matsuzawa ◽  
Kiyoshi Hasegawa ◽  
Ichio Fukasawa ◽  
...  
Keyword(s):  
Lactate Dehydrogenase ◽  
Diagnostic Value ◽  
Uterine Leiomyosarcoma ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Serum Assay ◽  
D Dimer

scholarly journals Visual Classification of Three Computed Tomography Lung Patterns to Predict Prognosis of COVID-19: A Retrospective Study

2021 ◽  
Author(s):  
Daisuke Yamada ◽  
Sachiko Ohde ◽  
Kengo Ikejima ◽  
Masaki Matsusako ◽  
Yasuyuki Kurihara
Keyword(s):  
Computed Tomography ◽  
Lactate Dehydrogenase ◽  
Neutrophil Count ◽  
Lymphocyte Count ◽  
Ct Images ◽  
C Reactive Protein ◽  
Clinical Variables ◽  
Reactive Protein ◽  
D Dimer

Abstract Background: Quantitative evaluation of radiographic images has been developed and suggested for the diagnosis of coronavirus disease 2019 (COVID-19). However, there are limited opportunities to use these image-based diagnostic indices in clinical practice. Our aim in this study was to evaluate the utility of a visually-based classification of pulmonary findingsfrom computed tomography (CT) images among COVID-19 patients that we developed, with the following three patterns defined: peripheral, multifocal, and diffuse findings of pneumonia. We also evaluated the prognostic value of this classification to predict the severity of COVID-19. Methods: This was a single-center retrospective cohort study of patients hospitalized with COVID-19 between January and September 2020, who presented with suspicious findings on CT lung images (n=69). We compared the association between the three predefined patterns (peripheral, multifocal, and diffuse) and admission to the intensive care unit, tracheal intubation, and death. The following demographic and clinical variables were compared between the three groups: sex, age, respiratory rate, pulse rate, blood pressure, temperature, oxygen saturation, partial pressure of oxygen, white blood cell count, lymphocyte count, neutrophil count, c-reactive protein, lactate dehydrogenase, Krebs von den Lungen-6 antigen, D-dimer, platelet count, steroid administration, heparin administration, favipiravir administration, Acute Physiology and Chronic Health Evaluation-II score, and sequential organ failure assessment score.Results: Patients with a diffuse pattern were intubated more frequently and for a longer duration than patients with a peripheral or multifocal pattern. The following clinical variables were significantly different between the diffuse pattern and peripheral and multifocal groups: body temperature, lymphocyte count, neutrophil count, c-reactive protein, lactate dehydrogenase, Krebs von den Lungen-6 antigen, D-dimer, and steroid and Avigan administration.Conclusions: Our simple visual assessment of CT images can predict a systemic cytokine storm, a resulting decrease in respiratory function, and the need for supplemental respiratory ventilationamong patientswith COVID-19.

scholarly journals Biomarkers of cytokine storm as red flags for severe and fatal COVID-19 cases: A living systematic review and meta-analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253894
Author(s):  
Ana Karla G. Melo ◽  
Keilla M. Milby ◽  
Ana Luiza M. A. Caparroz ◽  
Ana Carolina P. N. Pinto ◽  
Rodolfo R. P. Santos ◽  
...  
Keyword(s):  
Lactate Dehydrogenase ◽  
Interleukin 6 ◽  
Aspartate Aminotransferase ◽  
Laboratory Data ◽  
Cytokine Storm ◽  
Red Flags ◽  
C Reactive Protein ◽  
Laboratory Parameters ◽  
Reactive Protein ◽  
D Dimer

Objective To describe the laboratory parameters and biomarkers of the cytokine storm syndrome associated with severe and fatal COVID-19 cases. Methods A search with standardized descriptors and synonyms was performed on November 28th, 2020 of the MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, LILACS, and IBECS to identify studies of interest. Grey literature searches and snowballing techniques were additionally utilized to identify yet-unpublished works and related citations. Two review authors independently screened the retrieved titles and abstracts, selected eligible studies for inclusion, extracted data from the included studies, and then assessed the risk of bias using the Newcastle-Ottawa Scale. Eligible studies were those including laboratory parameters—including serum interleukin-6 levels—from mild, moderate, or severe COVID-19 cases. Laboratory parameters, such as interleukin-6, ferritin, hematology, C-Reactive Protein, procalcitonin, lactate dehydrogenase, aspartate aminotransferase, creatinine, and D-dimer, were extracted from the studies. Meta-analyses were conducted using the laboratory data to estimate mean differences with associated 95% confidence intervals. Data synthesis The database search yielded 9,620 records; 40 studies (containing a total of 9,542 patients) were included in the final analysis. Twenty-one studies (n = 4,313) assessed laboratory data related to severe COVID-19 cases, eighteen studies (n = 4,681) assessed predictors for fatal COVID-19 cases and one study (n = 548) assessed laboratory biomarkers related to severe and fatal COVID-19 cases. Lymphopenia, thrombocytopenia, and elevated levels of interleukin-6, ferritin, D-dimer, aspartate aminotransferase, C-Reactive-Protein, procalcitonin, creatinine, neutrophils and leucocytes were associated with severe and fatal COVID-19 cases. Conclusions This review points to interleukin-6, ferritin, leukocytes, neutrophils, lymphocytes, platelets, C-Reactive Protein, procalcitonin, lactate dehydrogenase, aspartate aminotransferase, creatinine, and D-dimer as important biomarkers of cytokine storm syndrome. Elevated levels of interleukin-6 and hyperferritinemia should be considered as red flags of systemic inflammation and poor prognosis in COVID-19.

scholarly journals Efficiency of il-6 inhibitor (olokizumab) in suppressing inflammation in patients with moderate COVID-19 pneumonia

2020 ◽  
Vol 5 (4) ◽  
pp. 8-13
Author(s):  
N. G. Ganyukova ◽  
M. I. Likstanov ◽  
M. V. Kosinova ◽  
I. N. Kushnir ◽  
V. G. Moses ◽  
...  
Keyword(s):  
Placebo Group ◽  
Treatment Group ◽  
Blood Cell ◽  
Cell Count ◽  
Treatment Outcomes ◽  
Lymphocyte Count ◽  
C Reactive Protein ◽  
Blood Cell Count ◽  
Reactive Protein ◽  
D Dimer

Aim. To study the efficiency of IL-6 inhibitor olokizumab in suppressing the inflammation and improving treatment outcomes in patients with moderate COVID-19 pneumonia. Materials and Methods. We enrolled 48 patients with confirmed COVID-19 pneumonia who had indications for the treatment with olokizumab. Treatment group (n = 29) included patients who received a single subcutaneous injection of olokizumab (0.4 mL, 160 mg/mL) while placebo group (n = 19) included those who did not receive the drug because of contraindications. Inflammatory markers (C-reactive protein, white blood cell count, lymphocyte count, ferritin and D-dimer) have been evaluated on the 1st and the 5th day after the administration of olokizumab. Efficiency of olokizumab was assessed by the treatment outcome and suppression of cytokine storm. Results. At the 5th day, SpO2 was 90% (88; 92-93) in both groups, yet none of the patients in the treatment group required a mechanical ventilation, in contrast to 21.1% patients in the placebo group (p = 0.001). Inflammatory parameters were also reduced in the treatment group according to the measurements of serum C-reactive protein (5.6 (1.8;13.5) and 23 (17;92.5) mg/L in the treatment and placebo group, respectively, p = 0.0002) and white blood cell count (5.9 (4.8;6.2) and 7.6 (6.6;12 )*109 /L in the treatment and placebo group, respectively, p=0.03). No statistically significant differences were registered regarding serum ferritin (325 (200; 700) and 215 (186; 526) ng/mL, p = 0.41), D-dimer (827 (378; 1940) and 1464 (677; 4600) ng FEU/mL, p = 0.16) and lymphocyte count (1.3 (0.8; 2.1) and 1.5 (1; 2.1)*109 /L, p =0.44). Death was registered in 3.5% and 21.1% of patients in the treatment and placebo group, respectively, (p = 0.05). Conclusion. Olokizumab ameliorated the progression of COVID-19 pneumonia, improved treatment outcomes and reduced systemic inflammation.

scholarly journals Early prediction of mortality risk among patients with severe COVID-19, using machine learning

2020 ◽  
Author(s):  
Chuanyu Hu ◽  
Zhenqiu Liu ◽  
Yanfeng Jiang ◽  
Oumin Shi ◽  
Xin Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Predictive Model ◽  
Mortality Risk ◽  
Protein Level ◽  
Lymphocyte Count ◽  
External Validation ◽  
High Sensitivity ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
D Dimer

Abstract Background Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 infection, has been spreading globally. We aimed to develop a clinical model to predict the outcome of patients with severe COVID-19 infection early. Methods Demographic, clinical and first laboratory findings after admission of 183 patients with severe COVID-19 infection (115 survivors and 68 non-survivors from the Sino-French New City Branch of Tongji Hospital, Wuhan) were used to develop the predictive models. Machine learning approaches were used to select the features and predict the patients’ outcomes. The area under the receiver operating characteristic curve (AUROC) was applied to compare the models’ performance. A total of 64 with severe COVID-19 infection from the Optical Valley Branch of Tongji Hospital, Wuhan, were used to externally validate the final predictive model. Results The baseline characteristics and laboratory tests were significantly different between the survivors and non-survivors. Four variables (age, high-sensitivity C-reactive protein level, lymphocyte count and d-dimer level) were selected by all five models. Given the similar performance among the models, the logistic regression model was selected as the final predictive model because of its simplicity and interpretability. The AUROCs of the external validation sets were 0.881. The sensitivity and specificity were 0.839 and 0.794 for the validation set, when using a probability of death of 50% as the cutoff. Risk score based on the selected variables can be used to assess the mortality risk. The predictive model is available at [https://phenomics.fudan.edu.cn/risk_scores/]. Conclusions Age, high-sensitivity C-reactive protein level, lymphocyte count and d-dimer level of COVID-19 patients at admission are informative for the patients’ outcomes.

scholarly journals The Role of D-Dimer, Fibrinogen and C-Reactive Protein as Plasma Biomarkers in Acute Ischemic Stroke

2015 ◽  
Vol 5 (6) ◽  
pp. 277-282 ◽  
Author(s):  
Mostafa Saleh Melake ◽  
Rasha Ali El-Kabany ◽  
Aktham Ismail Al-Emam ◽  
Ahmed Mohamed El-Shereef ◽  
Mohamed Okda
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
C Reactive Protein ◽  
Plasma Biomarkers ◽  
Reactive Protein ◽  
D Dimer

scholarly journals Correlation analysis between disease severity and clinical and biochemical characteristics of 143 cases of COVID-19 in Wuhan, China: a descriptive study

2020 ◽  
Author(s):  
Dan Wang ◽  
Ruifang Li ◽  
Juan Wang ◽  
Qunqun Jiang ◽  
Chang Gao ◽  
...  
Keyword(s):  
Lactate Dehydrogenase ◽  
Disease Severity ◽  
Serum Potassium ◽  
Critically Ill Patients ◽  
Lymphocyte Count ◽  
Serum Amyloid A ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Amyloid A ◽  
D Dimer

Abstract Background: Coronavirus disease 2019 ( COVID-19 ) is a novel infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan and has quickly spread across the world. The mortality rate in critically ill patients with COVID-19 is high. This study analyzed clinical and biochemical parameters between mild and severe patients, helping to identify severe or critical patients early. Methods: In this single center, cross-sectional study, 143 patients were included and divided to mild/moderate and sever/critical groups. Correlation between the disease criticality and clinical features and peripheral blood biochemical markers was analyzed. Cut-off values for critically ill patients were speculated through the ROC curve. Results: Significantly, disease severity was associated with age (r = 0.458, P < 0.001) , comorbidities (r = 0.445, P < 0.001) , white cell counts (r = 0.229, P = 0.006) , neutrophil count (r = 0.238, P = 0.004) , lymphocyte count (r = -0.295, P < 0.001) , albumin (r = -0.603, P < 0.001) , high-density lipoprotein cholesterol (r= -0.362, P < 0.001) , serum potassium (r = -0.237, P = 0.004) , plasma glucose (r = 0.383, P < 0.001) , total bilirubin (r = 0.340, P < 0.001) , serum amyloid A (r = 0.58, P < 0.001) , procalcitonin (r = 0.345, P < 0.001) , C-reactive protein ( r = 0.477, P < 0.001) , lactate dehydrogenase (r = 0.548, P < 0.001) , aspartate aminotransferase (r = 0.342, P < 0.001) , alanine aminotransferase (r = 0.264, P = 0.001) , erythrocyte sedimentation rate (r = 0.284, P = 0.001) and D-dimer (r = 0.477, P ＜ 0.001) . Conclusion: With following parameters such as age > 52 years, C-reactive protein > 64.79 mg/L, lactate dehydrogenase > 245 U/L, D-dimer > 0.96 ug/mL, serum amyloid A > 100.02 mg/L, or a lbumin ＜ 36 g/L, the progress of COVID-19 to critical stage should be closely observed and possibly prevented. Lymphocyte count, serum potassium and procalcitonin may also be a prognostic indicator .

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