Differentiating flare and infection in febrile lupus patients: Derivation and validation of a calculator for resource constrained settings. (September 2022)

• Record Type: Journal Article
• Authors: Mehta, Pankti; Singh, Komal; Anand, Swathi; Parikh, Akshay; Patnaik, Abinash; Chatterjee, Rudrarpan; Lawrence, Able; Tripathy, Saumya Ranjan; Kavadichanda, Chengappa; Rajasekhar, Liza; VS, Negi; Das, Bidyut; Amita, Aggarwal
• Is Part Of: Lupus. Volume 31:Number 10(2022)
• Page Start: 1254
• Page End: 1262
• Publication Date: 2022-09
• Subjects: Lupus erythematosus -- systemic -- fever -- C-reactive protein -- procalcitonin -- biomarkers; Systemic lupus erythematosus -- Periodicals; 616.772005
• DOI: 10.1177/09612033221112066
• Languages: English
• ISSNs: 0961-2033

Abstract

Background : Patients with Systemic Lupus Erythematous (SLE) are at an increased risk of infection and it is often difficult to differentiate between infection and disease activity in a febrile patient with SLE. Methods : Patients with SLE (SLICC criteria) presenting with fever between December 2018 and August 2021 were included. Neutrophil to lymphocyte ratio (NLR), NEUT-x, -y, -z indices, Erythrocyte sedimentation rate (ESR), C-reactive protein(CRP), C3, C4, anti-dsDNA antibodies, and procalcitonin(PCT) were tested in addition to investigations as per the treating physician's discretion. Based on the clinical assessment and laboratory data, the febrile episode was classified into infection, disease flare, or both. Statistical analysis was done using GraphPad prism v8.4.2. A novel composite score was devised and validated with a calculator incorporated is a spreadsheet. The performance of a previously proposed model of duration of fever, CRP, and dsDNA (Beca et al) was evaluated and other models using PCT and NEUT-Z were explored. Results : Among 168 febrile episodes in 166 patients with SLE (25 (19–32) years), 46 were due to infection, 77 due to flare, 43 due to both, and two due to other causes. High SLEDAI 2K (0.001), anti-dsDNA ( p = 0.004), and low complements(C3, p = 0.001 and C4, p = 0.001) were characteristic of disease flare, whereas high total leukocyte count (TLC) ( p = 0.008), NLR ( p = 0.008), NEUT-x ( p = 0.001), -y ( p = 0.03), -z ( p = 0.002), CRP ( p = 0.001), and PCT ( p = 0.03) were observed with infection. A model using age, TLC, and CRP was devised using 80% of the cohort with an AUC of 0.88 (0.78–0.97) which was validated in the remaining 20% to have an AUC of 0.83(0.60–1.0). The model devised by Beca et al yielded an AUC of 0.74. Use of PCT did not improve the discrimination between flare and infection. A Model of C4 and NEUT-z analyzed in a subset performed well and needs further exploration. Conclusion : A composite score of low cost and routinely available parameters like age, TLC, and CRP gives a good discrimination between infection and flare in a febrile patient with SLE.