Inflammatory markers in systemic lupus erythematosus

Aringer, Martin

doi:10.1016/j.jaut.2019.102374

Cited by 130 publications

(112 citation statements)

References 112 publications

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“…Our data is in consistent with Aringer et al stating that, without infection, CRP levels are higher in active SLE than in inactive SLE, the opposite is true in infections in SLE patients [18,37]. Table 1a).…”

Section: Patient and Clinical Characteristicssupporting

confidence: 93%

“…3 (a) we found that ESR decreased with time, but the trend of decreasing was more prominent in group A than in group C. ESR appears to be a useful biomarker for SLE activity assessment. An elevated ESR is included in three out of ve validated SLE activity scores [37]. The reported trend of ESR from Dima et al are similar with our trend analysis indicating that the higher initial ESR level re ect the effect of both activity and infections in group A.…”

Section: Trend Analysis Of Parameters Changes With Time Through Hospisupporting

confidence: 83%

“…The utility of traditional markers (e.g., CRP, ESR, PCT) for detecting infection in SLE patients has been discussed for several decades. CRP is an acute-phase reactant synthesized by the liver during IL-6 regulation and is known as an in ammatory biomarker [37]. CRP levels were reported to increase during infection, arthritis, and serositis in SLE patients [14].…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, the same immune complexes induce the production of type I IFNs and various immunoregulatory cytokines. The simple consequence is reduced production of CRP in active SLE (group B > group A) despite increased IL-6 levels, which are visible in concomitant infection [18,28,32,37]. PCT is a precursor peptide of calcitonin associated with invasive bacterial infections.…”

Section: Discussionmentioning

confidence: 99%

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Differential Parameters between Activity Flare and Acute Infection in Pediatric Patients with Systemic Lupus Erythematosus

Luo

Yang

Lin

et al. 2020

Preprint

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Background: Systemic lupus erythematosus (SLE) is a systemic autoimmune disease. SLE patients are vulnerable to infections. Infections might mimic and even trigger SLE flares. To distinguish acute infection from activity flare always remains a clinical challenge.We aim to explore the approach to differentiate active infection from disease activity in pediatric SLE patients.Methods: Fifty pediatric SLE patients presenting with 185 clinical episodes were collected.The associations betweenrelevant data encompassing both clinical and laboratory parameters and the outcome groups were analyzed using generalized estimating equations (GEEs)facilitatingthe analysis of data collected in longitudinal and repeated-measures designs.We also used a multinomial logistic regression model for simultaneous prediction of different outcome groups. Finally, we ran the GLIMMIX procedure to track trends of changes in parameters over time.Results: These 185 episodes were divided into 4 outcome groups: infected-active (n=102), infected-inactive (n=11), noninfected-active (n=59), and noninfected-inactive (n=13) episodes. Multivariate GEE analysis showed that SDI, SLEDAI-2K, neutrophil‐to‐lymphocyte ratio (NLR), hemoglobin, platelet, RDW-to-platelet ratio (RPR), and C3 are predictive of flare (combined calculated AUC of 0.8964 and with sensitivity of 82.2 % and specificity of 90.9%). Multivariate GEE analysis showed that SDI, fever temperature, CRP, procalcitonin, lymphocyte percentage, NLR, hemoglobin, and renal score in SLEDAI-2k are predictive of infection (combinedcalculated AUC of 0.7886 and with sensitivity of 63.5% and specificity of 89.2%). We developed regression equations for simultaneous prediction of 4 different outcome groups.We could differentiate noninfected-active from infected-active episodes by different change patterns of ESR, NLR, lymphocyte, C3, and C4 over time.Conclusions: The proposed approach could differentiateflares from infections in pediatric SLE patients. Combination of parameters from four different domains simultaneously, including inflammation (CRP, ESR, PCT), hematology (Lymphocyte percentage, NLR, PLR), complement (C3, C4), and clinical status (SLEDAI, SDI), is effective to make appropriate judgement and treatment decisions.

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Section: Patient and Clinical Characteristicssupporting

confidence: 93%

Section: Trend Analysis Of Parameters Changes With Time Through Hospisupporting

confidence: 83%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Differential Parameters between Activity Flare and Acute Infection in Pediatric Patients with Systemic Lupus Erythematosus

Luo

Yang

Lin

et al. 2020

Preprint

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“…PCT levels have been reported to increase to more than 0.5ng/ml in the presence of a bacterial infection, such as bacterial pneumonia or sepsis, in the body . 10 When the body is invaded by a virus, the value levels of PCT generally do not increase or only slightly increase. 11 Some of our patients in the control group had bacterial infection; therefore, 38.5% of them had PCT values higher than 0.5ng/ml, which was significantly higher than those of COVID-19 patients.…”

Section: Discussionmentioning

confidence: 98%

Differences between COVID‐19 and suspected then confirmed SARS‐CoV‐2‐negative pneumonia: A retrospective study from a single center

Chen

Yang

Huang

et al. 2020

Journal of Medical Virology

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Coronavirus disease 2019 (COVID‐19) broke out in Wuhan, Hubei, China in December 2019. Tens thousands of people have been infected with the disease. Our aim was to distinguish severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2)‐positive patients from SARS‐CoV‐2‐negative patients. We retrospectively compared the data of COVID‐19 patients with those of suspected and confirmed SARS‐CoV‐2‐negative patients (control patients). There were 78 COVID‐19 patients and 26 control patients, whose median ages were significantly different (P = .001). The percentage of COVID‐19 patients admitting exposure to Wuhan was obviously higher than that of control patients (X2 = 29.130; P < .001). Fever and cough appeared more frequently in COVID‐19 patients than in the control patients. The routine blood workup parameters of COVID‐19 patients did not change much and their mean counts were in the normal range. There were 38.5% of control patients had higher procalcitonin (PCT) levels than 0.5 ng/mL, which was significantly higher than that percentage of COVID‐19 patients (X2 = 22.636; P < .05), and COVID‐19 patients were also more likely to have decreased or normal urea and creatinine levels than control patients (X2 = 24.930, 8.480; P < .05).Younger age, exposure to Wuhan, fever, cough, and slight changes in routine blood workup parameters, urea and creatinine were important features discriminating COVID‐19 from control patients. Slightly increased, but far less than 0.5 ng/mL, PCT levels also differentiated COVID‐19 patients from control patients.

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Identification and Characterization of CD8⁺CD27⁺CXCR3⁻ T Cell Dysregulation and Progression‐Associated Biomarkers in Systemic Lupus Erythematosus

Zhang,

Du,

Jin

et al. 2023

Advanced Science

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Systemic Lupus Erythematosus (SLE) etiopathogenesis highlights the contributions of overproduction of CD4+ T cells and loss of immune tolerance. However, the involvement of CD8+ T cells in SLE pathology and disease progression remains unclear. Here, the comprehensive immune cell dysregulation in total 263 clinical peripheral blood samples composed of active SLE (aSLE), remission SLE (rSLE) and healthy controls (HCs) is investigated via mass cytometry, flow cytometry and single‐cell RNA sequencing. This is observed that CD8+CD27+CXCR3− T cells are increased in rSLE compare to aSLE. Meanwhile, the effector function of CD8+CD27+CXCR3− T cells are overactive in aSLE compare to HCs and rSLE, and are positively associated with clinical SLE activity. In addition, the response of peripheral blood mononuclear cells (PBMCs) is monitored to interleukin‐2 stimulation in aSLE and rSLE to construct dynamic network biomarker (DNB) model. It is demonstrated that DNB score‐related parameters can faithfully predict the remission of aSLE and the flares of rSLE. The abundance and functional dysregulation of CD8+CD27+CXCR3− T cells can be potential biomarkers for SLE prognosis and concomitant diagnosis. The DNB score with accurate prediction to SLE disease progression can provide clinical treatment suggestions especially for drug dosage determination.

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Inflammatory markers in systemic lupus erythematosus

Cited by 130 publications

References 112 publications

Differential Parameters between Activity Flare and Acute Infection in Pediatric Patients with Systemic Lupus Erythematosus

Differential Parameters between Activity Flare and Acute Infection in Pediatric Patients with Systemic Lupus Erythematosus

Differences between COVID‐19 and suspected then confirmed SARS‐CoV‐2‐negative pneumonia: A retrospective study from a single center

Identification and Characterization of CD8⁺CD27⁺CXCR3⁻ T Cell Dysregulation and Progression‐Associated Biomarkers in Systemic Lupus Erythematosus

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Inflammatory markers in systemic lupus erythematosus

Cited by 130 publications

References 112 publications

Differential Parameters between Activity Flare and Acute Infection in Pediatric Patients with Systemic Lupus Erythematosus

Differential Parameters between Activity Flare and Acute Infection in Pediatric Patients with Systemic Lupus Erythematosus

Differences between COVID‐19 and suspected then confirmed SARS‐CoV‐2‐negative pneumonia: A retrospective study from a single center

Identification and Characterization of CD8+CD27+CXCR3− T Cell Dysregulation and Progression‐Associated Biomarkers in Systemic Lupus Erythematosus

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Identification and Characterization of CD8⁺CD27⁺CXCR3⁻ T Cell Dysregulation and Progression‐Associated Biomarkers in Systemic Lupus Erythematosus