ReviewDevelopment and validation of a risk calculator to differentiate flares from infections in systemic lupus erythematosus patients with fever☆
Introduction
Systemic lupus erythematosus (SLE) is a relapsing multisystem autoimmune disorder that may affect almost any organ [1]. Clinical presentation is broad and heterogeneous and non-specific constitutional symptoms are common in these patients [2]. Fever has been reported as part of SLE initial manifestations in 28–36% of patients and in 52–60% during disease course [3], [4]. Importantly, fever has been reported as one of the main causes leading to admission in this disease [5], [6].
In SLE, fever can reflect an ongoing infection apart from being a manifestation of recurrences. Based on two retrospective series of hospitalized patients with this disorder, the estimated frequency of fever episodes that are of infectious origin or secondary to SLE activity is about 23–54% and 42–60%, respectively [7], [8].
In clinical practice, differentiation between SLE flares and infections can be extremely difficult. On one side and despite current therapeutic regimes, relapses are still observed in 25–35% of lupus patients [9]. On the other side, immunosuppressive therapy used in moderate–severe cases increases the risk and severity of infections [10], [11]. Infections are reported in 10–40% of SLE patients and are the main cause of death in 25–30% in large study cohorts [12], [13]. To increase the complexity of this problem, systemic infections may also trigger SLE recurrences [14], [15], [16].
Based on these data, accurate discrimination of activity or infection in SLE patients presenting with a febrile episode is crucial, as treatment options are completely different. In this regard, several candidates have been evaluated as potential biomarkers for differentiation of SLE flares and infections: erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), procalcitonin (PCT), and the newer molecules pentraxin 3, soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) and neutrophil CD64 + [14], [17], [18], [19], [20], [21], [22].
The aim of this study was to develop and validate a predictive risk calculator algorithm that could assist daily clinical decision-making to differentiate flares from infections in SLE patients presenting with fever.
Section snippets
Patients
A retrospective cohort study was conducted by reviewing the medical records of adult patients with SLE admitted because of fever at the Department of Autoimmune Diseases of Hospital Clínic, between January 2000 and February 2013. Patients with final diagnosis of a SLE flare and/or an infection were included. Drug-induced lupus patients and overlapping autoimmune syndromes were excluded. Fever episodes on a same patient were recorded independently. This study was approved by the local ethics
General characteristics
A total of 242 febrile episodes requiring admission to our Department were identified among 147 patients suffering from SLE. Thirty-two episodes that occurred in 17 patients were excluded because fever was due to other causes instead of infection or SLE flare (drug related hypersensitivity, crystal induced arthritis, hemophagocytic syndrome, malignancy, deep venous thrombosis, Budd–Chiari syndrome or fever of unknown origin). Overall, 130 patients (83% women) presented 210 febrile episodes that
Discussion
Here, we have created a simple risk algorithm calculator to assist clinicians in a frequently faced dilemma: try to differentiate flares from infections in SLE patients. To the best of our knowledge, this is the first study conducted with this purpose.
Infections and active disease are the leading cause of death in patients with SLE [13], [45]. As both conditions may present with similar clinical findings, implementation of ancillary tools that accurately identify them could be used to assist
Take-home messages
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In SLE patients, fever can be a sign of an ongoing infection or disease activity.
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In daily clinical practice, differentiation between SLE flares and infections is usually difficult, as no single clinical or laboratory finding is reliable for this purpose.
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The proposed risk algorithm for flares prediction performed well, and could be useful to differentiate between relapses and infections in febrile SLE patients. The impact of this finding needs to be assessed in large cohorts.
Conflict of interest statement
The authors declare no conflicts of interest.
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MA Alba was supported by Consejo Nacional de Ciencia y Tecnología (CONACyT) (CONACyT: 309320), Mexico and by the Agencia de Gestió d'Ajuts Universitaris i de Recerca (AGAUR, Generalitat de Catalunya) (AGAUR: 2014FI-B2 00014).
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S Beça, I Rodríguez-Pintó and MA Alba contributed equally to this study.