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

Abstract

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.

Neutrophil-to-lymphocyte ratios and platelet-to-lymphocyte ratios in juvenile systemic lupus erythematosus: correlation with disease manifestations

“…We did not find a significant correlation between NLR and LN, which was inconsistent with a previous study (23). Some studies have found that NLR was a useful marker to assess disease activity both in jSLE and aSLE patients (11,(20)(21)(22). A meta-analysis demonstrated that NLR had positive clinical value for diagnosing SLE, active SLE, and LN (11,24).…”

“…The PLR was positively correlated with SLEDAI and may be useful marker to evaluate SLE disease activity (11). The same findings were reported in both aSLE (22,23) and jSLE patients (20). While in the present study, we did not find that PLR was correlated with SLEDAI, which was consistent with a previous study (27).…”

“…Our data showed that with respect to organ involvement, significantly higher NLR was only found in participants with serositis. Previous studies have reported that NLR was not associated with serositis in jSLE or aSLE patients (20,21). Dorota et al reported that NLR was significantly higher in aSLE patients with cutaneous and/or mucosal symptoms and kidney damage (21).…”