Authors: José Fernando Gómez-Urrego, Nathalie Yepes-Madrid, Mónica Alexandra Gil-Artunduaga, María del Pilar Gómez-Mora, Luis Fernando Mejía-Rivera, Robinson Pacheco-López, Juan Pablo Rojas-Hernández
Categories: Research, Bacteria, Biomarkers, Fever, Systemic lupus erythematosus
Source: Pediatric Rheumatology
Authors: José Fernando Gómez-Urrego, Nathalie Yepes-Madrid, Mónica Alexandra Gil-Artunduaga, María del Pilar Gómez-Mora, Luis Fernando Mejía-Rivera, Robinson Pacheco-López, Juan Pablo Rojas-Hernández
Juvenile Systemic Lupus Erythematosus (JSLE) is a chronic, systemic autoimmune disease characterized by an increased susceptibility to infections. Fever in these patients can result from infection, heightened lupus activity, or a combination of both. Various clinical factors and biomarkers have been proposed to differentiate between infection and disease activity, but the results remain inconclusive. The Systemic Lupus Erythematosus Disease Activity Index-2000 (SLEDAI-2 k) is used to assess lupus activity in the presence or absence of infection. This study aimed to identify factors associated with bacterial infections in JSLE patients presenting with fever.
A case–control study, approved by the institutional ethics committee, was conducted.
Bacterial infection was identified in 17% of 116 patients. Factors evaluated included immunomodulator use, high-dose steroids, renal replacement therapy, erythrocyte sedimentation rate (ESR) > 20, C-reactive protein (CRP) > 60 and > 90 mg/L, ferritin > 500 ng/mL, neutrophil-to-lymphocyte ratio (NLR) > 6, platelet-to-lymphocyte ratio (PLR) > 133, procalcitonin (PCT) > 0.9 ng/mL, lymphocyte-to-C4 ratio (LC4R) > 66.7, and ESR/CRP ratio < 2. In the adjusted model, PCT > 0.9 ng/mL retained significance with p < 0.01. Nagelkerke’s R^2^ was 0.65, and the Hosmer–Lemeshow test indicated good internal validity.
Bacterial infection was detected in 17% of JSLE patients with fever. Procalcitonin > 0.9 ng/mL is a critical marker for identifying bacterial infection. NLR, PLR, ESR/CRP ratio, LC4R, and ferritin require further investigation to establish definitive cut-off values for differentiating bacterial infections from other infections or disease activity. Individual patient evaluation remains the recommended approach for diagnosis.
Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease characterized by the presence of autoantibodies caused by immune system dysregulation. Its prevalence ranges from 3.2 to 300 cases per 100,000 people, with an incidence of 1.4 to 8.7 per 100,000 people [1]. SLE exhibits extensive phenotypic variability, with juvenile-onset SLE (JSLE) being the most common, accounting for 55.7% of cases. JSLE typically manifests between the ages of 7 and 13 [2] and is associated with a higher susceptibility to infections, increased disease activity, greater tissue and organ damage [3], and the need for more intensive immunosuppressive therapy [4]. The disease alternates between potentially life-threatening periods of immune activity and phases of remission [5–7].
In JSLE, infections contribute to morbidity and mortality in 44% of cases and increase healthcare costs by 30% due to prolonged hospitalizations and admissions to pediatric intensive care units. Infections can be bacterial, viral, or fungal in nature [8–10]. Approximately 50% of adults with SLE experience severe infectious episodes requiring extended hospitalization, and early identification of infected patients significantly improves outcomes [11]. Fever is a common symptom of both infection and heightened lupus activity, and these conditions often coexist. Fever is reported in 36–96% of adults with SLE, with 60% of cases attributed to disease activity, 23% to infection, and 12% to both conditions [12, 13].
Several clinical features and biomarkers have been investigated to assist clinicians in differentiating between disease activity and infection in SLE patients with fever. Evidence regarding the utility of biomarkers such as C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), neutrophil-to-lymphocyte ratio (NLR), ferritin, and procalcitonin (PCT) remains inconclusive [14–20]. Ju-Yang et al. (2019) identified serositis, hematologic involvement, and high-dose glucocorticoids (> 7.5 mg/day of prednisolone) as factors associated with severe infections, such as those requiring Intensive Care Unit (ICU) hospitalization or intravenous antibiotic use [21].
Zhai et al. (2021) reported a scoring system for identifying bacterial infections in adults with SLE, achieving an area under the curve (AUC) of 0.842 and a 95% confidence interval (CI) of 0.794–0.891. Variables such as white blood cell count, neutrophil count, ESR, CRP, PCT, interleukin-6, interleukin-10, interferon-gamma, and tumor necrosis factor-alpha were significantly elevated in patients with bacterial infections [22].
In pediatrics, Luo et al. reported that the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (SDI), fever, CRP, PCT, lymphocyte percentage, NLR, hemoglobin, and the SLE Disease Activity Index 2000 (SLEDAI-2 K) are predictive of infection, with an area under the curve (AUC) of 0.7886, sensitivity of 63.5%, and specificity of 89.2%. The authors recommend individualized clinical analysis for decision-making [23].
Sari et al. identified urinary tract infections (41%), skin and soft tissue infections (20.5%), and pneumonia (20.5%) as the most common infections, with methylprednisolone pulse therapy being a predictor of infection [24].
Disease activity indices, such as SLEDAI, are designed to classify disease activity regardless of the triggering cause [25–27]. Biomarkers like NLR, ESR/CRP ratio, platelet-to-lymphocyte ratio (PLR), and lymphocyte/C4 index (L/C4) have been studied in adult Colombian populations to differentiate infection from disease activity. The optimal cutoff values for infection detection were NLR > 6, ESR/CRP ratio < 2, PLR > 132, and L/C4 index > 66.7 [28].
The objective of this study is to identify factors associated with bacterial infections in JSLE patients with fever.
The study protocol was approved by the Pediatric Research Group (GRINPED) under record 072 on August 12, 2023; the Ethics and Bioethics Research Committee of Fundación Clínica Infantil Club Noel under registration 268 on October 20, 2023; and the Ethics Committee of Universidad Libre Seccional Cali, Colombia (Resolution CEB-10–2024, dated March 28, 2024), in accordance with the Declaration of Helsinki of the World Medical Association.
An observational, analytical case–control study with retrospective data collection was conducted at a pediatric referral institution in Cali, Colombia (Fundación Clínica Infantil Club Noel). The study was self-funded.
The study included 116 febrile patients with juvenile systemic lupus erythematosus (JSLE) who were admitted between January 2015 and December 2023.
Cases were defined as JSLE patients diagnosed according to the American College of Rheumatology 2017 criteria, the SLICC 2012 criteria, or diagnostic confirmation by a pediatric rheumatology expert, who experienced at least one febrile episode exceeding 38 °C of non-hospital onset, with bacterial infection confirmed by culture isolation or detection using staining, antigenic tests, serological, or molecular methods.
Controls included febrile JSLE patients, as defined above, in whom bacterial pathogens could not be detected or isolated.
Patients were excluded if Had more than 20% of their data missing.Received initial stabilization care and were referred to another institution.Presented with severe trauma, burns, or underwent major surgery.Had malignant neoplasms, coexisting inflammatory bowel disease, chronic liver disease, or pre-existing and known chronic infections (e.g., osteomyelitis, endocarditis, active HIV, or hepatitis B).Experienced macrophage activation syndrome.
The calculated sample size (Epi Info 7.10) of 18 cases and 78 controls (Fleiss method) was achieved. Figure 1 shows the patient selection flowchart.Fig. 1Flowchart of patient selection for the study
The data were sourced from medical records. Disease activity was classified using the SLEDAI-2 K scale [25–27]. Sociodemographic variables included age, sex, place of residence, and social security coverage. Clinical variables analyzed included duration of fever (in days), temperature at admission, disease onset, nutritional status, use of immunosuppressants, use of high-dose steroids (> 7.5 mg/day of prednisolone), renal replacement therapy, and the SLEDAI-2 K score.
Laboratory tests analyzed were those performed upon patient admission and included hematological parameters and biomarkers such as C-reactive protein (CRP), procalcitonin (PCT), erythrocyte sedimentation rate (ESR), ferritin (FERRI), complement C3 (C3), and complement C4 (C4). Ratios such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), ESR/CRP ratio, and lymphocyte/C4 ratio were also calculated. Immunological tests included rheumatoid factor (RF), antinuclear antibodies (ANA), anti-dsDNA antibodies, anti-RNP antibodies, anti-Sm antibodies, anti-SS-A/Ro antibodies, and perinuclear anti-neutrophil cytoplasmic antibodies (p-ANCA), as well as C3 and C4 levels.
The dependent variable was bacterial infection, defined as isolation by culture or detection through molecular tests, staining, or antigen tests. Clinical bacterial infections without microbiological confirmation were not classified as cases to minimize investigator bias.
Data were collected in Microsoft Office Excel® and processed using IBM SPSS Statistics version 29.0.2.0 (2020) © International Business Machines Corporation.
The distribution of quantitative variables was determined using the Kolmogorov–Smirnov test, and in the case of non-normality, they were summarized by median and interquartile range. Qualitative variables were summarized using frequencies and percentages. Associations were established through bivariate and multivariate analyses, assessing the goodness of fit of the resulting model. To assess how well the regression model explains the observed data, Nagelkerke's R-squared and the Hosmer–Lemeshow test were used.
A total of 116 febrile JSLE patients were included in the study, of which 20 patients with confirmed bacterial detection or isolation formed the case group, and 96 patients without bacterial detection or isolation comprised the control group, yielding a case-to-control ratio of 4. The cohort consisted of 16 males and 100 females, with 70 patients residing in Cali and 46 from other municipalities.
Regarding social security coverage, 37 patients were under the contributory scheme, 78 under the subsidized scheme, and one under a special scheme.
Twenty-eight patients were unaware of their disease status, and 19 were undergoing renal replacement therapy (RRT). The proportion of confirmed bacterial infection was 17%.
All 116 study patients had a positive SLEDAI-2 K score indicating disease activity, with 22 patients classified as having mild activity and 94 as having moderate to severe activity.
Table 1 provides a detailed description of the sociodemographic and clinical characteristics of the study population, stratified by case and control groups. Table 1Sociodemographic and clinical characteristics of the study population, stratified by case and control groupsCharacteristicTotal (n, %)Confirmed Bacterial Infection (Cases n = 20)No Bacterial Confirmation (Controls n = 96)Sex: male16 (13%)2 (10%)14 (15%)Sex female100 (86%)18 (90%)82 (85%)Origin: Cali70 (60%)11 (55%)59 (61%)Social Security Contributive37 (32%)6 (30%)31 (32%) Subsidized78 (67%)14 (70%)64 (67%) Special101 Exception000 Uninsured000Main Complaint Symptom Respiratory11 (9%)2 (10%)9 (9%) Gastrointestinal14 (12%)2 (10%)12 (13%) Urinary2 (2%)02 (2%) Systemics32 (28%)4 (20%)28 (29%) Musculoskeletal25 (22%)4 (20%)21 (22%) Skin, Soft Tissues, Neurological5 (4%)1 (5%)4 (4%)6 (5%)06 (6%) Fever2 (2%)02 (2%) Hematological19 (16%)7 (35%)12 (13%) Use of Immunomodulators63 (54%)16 (80%)47 (49%)Type of Immunomodulator Steroid alone7 (6%)1 (5%)6 (6%) Azathioprine3 (3%)03 (3%) Methotrexate1 (1%)01 (1%) Mycophenolate2 (2%)02 (2%) Cyclophosphamide1 (1%)01 (1%) Biologics1 (1%)01 (1%) Combined Therapy52 (45%)14 (70%)38 (40%) High-dose Steroids24 (21%)6 (30%)18 (19%) SLE Onset28 (24%)2 (10%)26 (27%) Renal Replacement Therapy19 (16%)7 (35%)12 (13%)Nutritional Status Eutrophic60 (52%)9 (45%)51 (53%) Depleted43 (37%)6 (30%)37 (39%) Severe Malnutrition5 (4%)1 (5%)4 (4%) Obesity8 (7%)4 (20%)4 (4%)
Table 2 presents the quantitative clinical and laboratory characteristics of interest. The distribution of all quantitative variables, except for the SLEDAI-2 K score, was non-parametric as determined by the Kolmogorov–Smirnov test. All variables, including the SLEDAI-2 K score, are summarized using the median and interquartile range (IQR). Table 2Clinical and laboratory characteristics at admission of febrile JSLE patients, stratified by confirmed bacterial infectionCharacteristic (n)****Median (IQR) (n)p-valuen **= 116****Confirmed Infection (cases) (**n **= 20)***No infection confirmation (controls) (**n **= 96)**Age in years11614,5 (12 – 16)15 (13–16)0,64Fever duration in days1152 (1 – 7)4 (1 – 15)0,48Temperature (°C)11638 (38 – 39)38 (38 – 39)0,82PCT (ng/mL)260,57 (0,16 – 4,51)0,14 (0,06 – 0,30)0,20CRP (mg/L)11142,5 (2,70 – 115)14,6 (3,06 – 45,6)0,77ESR (mm/hra)9790 (49 – 103)80 (35 – 108)0,56Ferritin (ng/mL)66428 (199 – 640)220 (118 – 639)0,07Leukocytes (/ml^3^)1155515 (3860 – 10192)6700 (4800 – 9390)0,48Lymphocytes (/ml^3^)1151030 (722–1412)1400 (920–2050)0,03Neutrophils (/ml^3^)1153940 (2135 – 8625)4530 (3070 – 6700)0,83Hemoglobin (gr/dl)11510,0 (8,3 – 11,8)10,1 (8,6 – 11,8)0,6Platelets (× 10^3^/ml^3^)115217,5 (160,25 – 30825)277 (210 – 396)0,23NLR1155,75 (1,46 – 9,81)3,19 (1,85 – 5,97)0,43VES/PCR942,4 (0,71 – 28,6)4,9 (1,6 – 17,6)0,28IPL115242 (154 – 334)200 (134 – 310)0,20ILC496110 (42,5 – 153)171 (70 – 440)0.01C3 (mg/dl)9758,3 (40 – 89,9)52,5 (32,2 – 111)0,96C4 (mg/dl)9711,9 (6 – 20)6,9 (3,2 – 20)0,28SLEDAI-2 k11623 (3—41)19 (11—28)0,74PCT Procalcitonin, CRP C-reactive protein, ESR Erythrocyte sedimentation rate, NLR Neutrophil-to-lymphocyte ratio, ESR/PCR Erythrocyte sedimentation rate-C-reactive protein index, PLR Platelet-to-lymphocyte ratio, LC4 Lymphocyte-C4 index, SLEDAI-2 k *Systemic Lupus Erythematosus Disease Activity Index 2000
Regarding immunological tests for juvenile systemic lupus erythematosus (JSLE), the most commonly observed antinuclear antibody (ANA) pattern was homogeneous, found in 21 patients, followed by a speckled pattern in 17 patients and a fine granular pattern in 7 of the 59 patients tested.
The most frequently reported ANA titers were 1280, observed in 22 cases, followed by 640 in 14 patients and 2560 in 8, out of a total of 58 patients tested.
Anti-dsDNA antibodies were tested in 64 patients and were positive in 16. Anti-RNP was positive in 4 of 48 patients, anti-Sm in 4 of 47, anti-SS-A/Ro in 10 of 47, and rheumatoid factor in 12 of 36 patients tested.
Table 3 presents the studies conducted on the 116 patients to identify the etiology of the infection, while Table 4 provides details of patients with bacterial isolations or detections and their associated non-bacterial co-infections. Table 3Studies performed on JSLE patients with fever to identify the etiology of the infection (n = 116)StudyNumber of patients who underwent the studyIsolation or microbiological detectionBlood culture73 (63%)10 (9%)Urine culture18 (16%)11 (9%)Stool culture20 (17%)3 (3%)Peritoneal culture5 (4%)1 (1%)Bronchoalveolar lavage (BAL) culture8 (7%)3 (3%)Molecular panel Respiratory16 (14%)10 (9%) Pneumonia2 (2%)1 (1%) Central Nervous System (CNS)1 (1%)0 Sepsis3 (3%)1 (1%) Gastrointestinal4 (4%)2 (2%)Other studies Ziehl–Neelsen stain3 (3%)1 (1%) Galactomannan antigen4 (4%)2 (2%) Dengue serology13 (11%)6 (5%) CMV viral load6 (5%)4 (4%) Respiratory virus antigens60 (52%)35 (30%)Table 4Bacterial isolations or detections in JSLE patients with fever and confirmed bacterial infectionPatient^a^SexAgeIsolation or detection12F17Urine E. coli13F15Urine E. coli14F13Blood Culture: Pasteurella multocidaPeritoneal Fluid Culture: Pasteurella multocida17F16Blood Culture: S. aureus + Leuconostoc lactisMolecular Panel Pneumonia: S. aureus + Streptococcus pneumoniaeSputum Culture: S. aureusDengue Virus Serology Positive19F12Molecular Sepsis Panel: E. coli + S. aureusBlood Culture: E. coli + S. aureusUrine Culture: E. coli + S. aureusStool Culture: E. coliGastrointestinal Molecular Panel: E. coli34F17Blood Culture: S. aureusUrine Culture: Proteus mirabilis35F11Urine Culture: E. coli44F15Urine Culture: E. coli47F15Blood Culture: S. aureusStool Culture:* E. coliDengue Virus Serology: positive48F17Blood Culture Acinetobacter baumannii + Klebsiella pneumoniae51F14Urine Culture: Escherichia coliBronchoalveolar Lavage (BAL): Aspergillus fumigatus with positive galactomannanPositive Bacilloscopy54M15Blood Culture: S,aureusUrocultivo: Leclercia adecarboxylata62F14Hemocultivo: E. coliUrine Culture: E. coli68F11Blood Culture Burkholderia cepaciaPositive Viral Load CMVPositive Viral Load Epstein-Barr Virus70F16Urine Culture: Proteus mirabilis81F17Stool Culture: E. coli92F13Urine Culture: E. coli*93M11Gastrointestinal Molecular Panel: Brucella abortusPositive Serology for SARS-CoV-2/COVID-1997F14Blood Culture: S. aureus + S. hominisSuperficial Fungal Culture: Candida spp116F10Bronchoalveolar lavage (BAL) Staphylococcus aureus^a^Patient data registration row in the database
Bivariate analysis in Tables 5, 6 and 7 describes the relationships between sociodemographic and clinical characteristics, biomarkers and indicators, and immunological tests with confirmed bacterial infection in patients with Juvenile Systemic Lupus Erythematosus (SLEJ) and fever. Table 5Bivariate analysis of sociodemographic and clinical factors and their relationship with bacterial infection in patients with SLEJ and fever (n = 116, Ca = 20, Co = 96)Characteristic and DescriptionNCases (n = 20)Controls (n = 96)ORc95% CIp-valueSex Male162140,650,13 – 3,110,73 Female1001882Origin Cali YES7011590,760,29 – 2,020,59 NO46937Fever for 3 or more days YES639540,620,23 – 1,630,33 NO521141Fever for 7 or more days YES415360,540,18 – 1,630,31 NO641559Immunomodulators YES6316474,171,29–13,380.01 NO53449High-dose Steroids YES246181,850,62—5,490,25 NO921478JSLE Onset YES282260,290,65 – 1,380,15 NO881870Renal Replacement Therapy YES197123,761,25 – 11,30,01 NO971384SLEDAI 2 k Mild225171,540,49 – 4,840,53 Moderate to Severe941579JSLE Juvenile Systemic Lupus Erythematosus, SLEDAI-2 k Systemic Lupus Erythematosus Disease Activity Index 2000Table 6Bivariate analysis of biomarkers and their relationship with bacterial infection in patients with SLEJ and fever (n = 116, Ca = 20, Co = 96)Characteristic and DescriptionNCasesControlsORc95% CIp-valuePCT > 0.90 ng/mL YES541171,47 – 1,960,02 NO21417ESR > 20 mm/hr YES8317660,790,71 – 0,880,12 NO14014CRP > 6 mg/L YES6713541,270,46 – 3,490,63 NO44737CRP > 60 mg/L YES2510155,061,79–14,280,001 NO861076CRP > 90 mg/L YES13675,141,50–17,560,005 NO981484Ferritin > 500 ng/mL YES227152,100,64—6,830,21 NO44836Consumed C3 (< 88 mg/dl) YES6514511,480,48 – 4,550,59 NO32527Consumed C4 (< 15 mg/dl) YES6312510,900,32 – 2,570,85 NO34727NLR > 2.0 YES7714631,180,41—3,370,75 NO38632NLR > 6.0 YES309212,281,05 – 7,880,03 NO952174PLR > 132.9 YES9318752,400,51–11,210,35 NO22220ESR/CRP Index < 2 YES609510,570,19 – 1,660,30 NO34826LC4 > 66.7 YES7313600,640,20 – 1,850,38 NO23617PCT Procalcitonin, CRP C-reactive protein, ESR Erythrocyte sedimentation rate, NLR Neutrophil-to-lymphocyte ratio, ESR/PCR Erythrocyte sedimentation rate-C-reactive protein index, PLR Platelet-to-lymphocyte ratio, LC4 Lymphocyte-C4 index, SLEDAI-2 k Systemic Lupus Erythematosus Disease Activity Index 2000Table 7Bivariate analysis of immunological disease activity markers and their relationship with bacterial infection in patients with SLEJ and fever (n = 116, Ca = 20, Co = 96)Characteristic and DescriptionNCasesControlsORc95% CIp**-value**SLEDAI 2 k Mild225171,540,49 – 4,840,53 Moderate to Severe941579p-ANCAS Positive122100,330,04 – 2,680,34 Negative835Anti-dsDNA Positive143110,770,18 – 3,221,00 Negative501337Anti-RNP Positive4131,290,12–13,981,00 Negative44935Anti-Sm Positive4131,450,13–15,901,00 Negative43835Anti-SS-A/Ro Positive10372,240,44–11,080,37 Negative37631SLEDAI-2 k Systemic Lupus Erythematosus Disease Activity Index 2000, p-ANCAs Perinuclear anti-neutrophil cytoplasmic antibodies, Anti-dsDNA Anti-double stranded DNA antibodies, Anti-RNP Anti-ribonucleoprotein U1 antibodies, Anti-Sm Anti-Smith antigen antibodies, Anti-SS-A/Ro Anti-Sjögren's syndrome-related antigen A
For the multivariate analysis, variables with a significant crude odds ratio (OR) and those with a crude OR < 0.25 were included in the explanatory model for bacterial infection. These variables included the use of immunomodulators, high-dose steroids, renal replacement therapy, erythrocyte sedimentation rate (ESR) > 20, C-reactive protein (CRP) > 60, CRP > 90, ferritin > 500, interleukin (IL) > 6, platelets > 133, procalcitonin (PCT) > 0.9, and, based on researcher interest, the indices ILC4 > 66.7 and ESR/CRP < 2. The variable PCT > 0.9 retained significance with a p-value < 0.01. The other variables were not included in the final model (Table 8). The Nagelkerke R-squared was 0.65. The Hosmer–Lemeshow test demonstrated adequate internal validity, with a chi-squared value of 0.000, indicating perfect concordance between the observed and expected frequencies. Table 8Binary logistic regression of factors associated with bacterial infection in patients with SLE and feverCharacteristicp-valueInclusion in the explanatory modelPCT > 0.90.000YESUse of immunomodulators0,360NoHigh-dose steroids0,685NoRenal replacement therapy0,255NoESR > 200,551NoCRP > 600,423NoCRP > 900,448NoFERRI > 5000,756NoNLR > 60,756NoPLI > 1330,255NoLC4I > 66.70,283NoESR/CRP < 20.91NoPCT Procalcitonin, CRP C-reactive protein, ESR Erythrocyte sedimentation rate, FERRI Ferritin, NLR Neutrophil–lymphocyte index, PLI Platelet-lymphocyte index, LC4I Lymphocyte-complement C4 index, ESR/CRP Erythrocyte sedimentation rate-C-reactive protein indexNagelkerke R-squared = 0.654
In the studied population of patients with SLEJ and fever, the confirmed bacterial infection rate was 17%, which is lower than the 35% reported in Colombia for adult SLE patients by Beltrán et al. and the 32% found in Medellín, Colombia, as reported by Santamaría-Alza et al. in adult populations [13, 28]. The most common infection identified was urinary tract infection, consistent with the findings of Sari et al., who reported a rate of 41% [24].
The clinical presentation of patients with bacterial infections did not significantly differ from those without bacterial infections. In both groups, the primary reason for consultation was systemic or musculoskeletal symptoms, observed in 40% and 51% of cases, respectively. Neither the duration of fever nor the onset of SLEJ were associated with the presence of bacterial infection. The use of immunomodulators in SLEJ initially suggested a higher likelihood of bacterial infection, as reported by Ju-Yang et al. in adult SLE patients. However, this factor did not remain significant in the final model. Other factors, such as hematological involvement and high-dose steroid use—factors previously suggested in adult populations—did not show significant differences between the groups in this study of SLEJ patients [21].
Direct biomarkers such as procalcitonin, CRP, and ESR did not show significant differences between the groups when using the cut-off values suggested for healthy individuals. A recent study in an adult population by Abdel-Magied et al. used a procalcitonin cut-off value of 0.9 ng/mL, which is higher than the 0.25–0.50 ng/mL range typically suggested for healthy subjects.This study confirmed a significant association between elevated procalcitonin levels and bacterial infection [29]. Similarly, the present study found that a procalcitonin level of 0.9 ng/mL was the only variable retained in the final explanatory model for bacterial infection in SLEJ patients with fever. Other variables, such as CRP > 60 mg/L, CRP > 90 mg/L, ESR > 20 mm/h, and ferritin > 500 ng/mL, although significant in the bivariate analysis, were excluded from the final model.
Regarding biomarker indicators, Santamaría-Alza's study in Medellín, Colombia, used a neutrophil-to-lymphocyte ratio (NLR) cut-off of 6.3 in an adult population, significantly higher than the 2.0 cut-off proposed by Abdel-Magied. For other indices, Santamaría-Alza set the platelet-to-lymphocyte ratio (PLR) cut-off at 132.9, suggested a value of < 2 for the ESR/CRP ratio as indicative of infection, and used a lymphocyte-C4 ratio of 66.7. In that study, the lymphocyte-C4 ratio emerged as the best-performing index.
In the present study, bivariate analysis suggested potential associations with IL > 6, PLR > 133, and, for research purposes, we included ILC4 > 66.7 and ESR/CRP < 2 in the multivariate analysis. However, these indices were not retained in the final binary logistic regression model for bacterial infection.
Immunological tests are widely used in adults as markers of disease activity and are incorporated into the SLEDAI-2 K scale. However, their usage in the study population was low, ranging from 17 to 55% depending on the specific marker. This may be attributed to the clinicians' primary focus on identifying the source of fever, leading to an initial treatment for infection. It's important to note that disease activity may increase in the presence of infection. The present study specifically focuses on patients with juvenile systemic lupus erythematosus, also known as childhood-onset systemic lupus erythematosus (cSLE) [30].
Our results must be interpreted in light of several limitations inherent to the chosen study style.
A strategy was implemented to minimize selection bias by clearly defining the study population (patients with SLE and fever) and selecting all eligible patients. The controls were drawn from the database of febrile SLE patients, which is a strength of the study. This design allowed for a focused investigation into bacterial infection in patients with SLEJ and fever, rather than in healthy individuals or those with SLEJ who were not febrile.
To further control for bias, patients with a clinical diagnosis of bacterial infection, but without microbiological confirmation, were included as controls, regardless of whether they were receiving antimicrobial treatment. This helped minimize the possibility of biases that could arise from treatment-induced differences.
Information bias was mitigated by establishing operational definitions and using quantitatively measured exposures, which helped ensure the validity of the recorded data. The only reconstructed variables in the study were nutritional status and the SLEDAI-2 K score. Furthermore, the multivariate analysis was adjusted for potential confounding variables, strengthening the model's reliability.
The detection of bacterial infection in patients with SLEJ and fever continues to be a challenging clinical issue. In our study, the bacterial infection rate was 17%. Procalcitonin, with a cut-off of 0.9 ng/mL, proved to be a valuable decision-making tool, although it is not definitive on its own. Other biomarkers such as interleukin (IL), platelet-to-lymphocyte ratio (PLR), ESR/CRP ratio, lymphocyte-C4 ratio (ILC4), and ferritin levels warrant further investigation. The optimal cut-off values for these biomarkers in distinguishing bacterial infection from other types of infections or disease activity in febrile SLEJ patients are yet to be established. Ultimately, individualized patient assessment remains the cornerstone of clinical practice.