Data from: The interest of inflammatory biomarkers in the diagnostic approach
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Abstract
Background: The role of inflammatory biomarkers in the etiological orientation is increasingly under study, and their potential significance is recognized.
Methods: Procalcitonin (PCT), neutrophil-lymphocyte ratio (NLR), C-reactive-protein (CRP), fibrinogen, ferritinaemia and lactate were measured on admission in all patients. The optimal cut-off values for the sensitivities and specificities to the infectious diseases were determined using the receiver operating curve(ROC) analysis and Youden's index. The diagnostic accuracy of biomarkers and their combinations for predicting infectious etiologies was calculated by area under the curve(AUC).
Results: A total of 164 patients were included in the study. The mean age was 50.7 ± 18 years [18 – 92 years]. Fifty-three patients (32.3%) were over 65 years old. Patients were split into four groups: 53 patients (32.3%) with infectious diseases of which 45 patients (84.9%) presented bacterial infections, 62 patients (37.8%) with inflammatory diseases, 14 patients (8.5%) with neoplasms and 35 patients (21.3%) with other diagnosis. The high mean levels of Leukocytes (12047 cells/mm3, Neutrophils (9015 cells/mm3), Neutrophils to lymphocytes ratio (NLR) (9.7), C reactive protein (CRP) (152.5 mg/L), Procalcitonin (PCT)(3.28 ng/ml)and fibrinogen (5.37g/L) were associated to infectious etiologies with statistically significant differences. Thus, we identified cut-offs of NLR(6.1), CRP (123 mg/L),PCT(0.24 ng/mL) and fibrinogen (4.9 g/L) to discriminate infectious etiologies in our population. For diagnosing infectious diseases, the CRP showed higher AUC( Area under the curve) (Sp: 89.7%, Se: 64.3%, AUC=0.9, CI: 0.83-0.96, p<10-3) than PCT (Sp: 86.1%,Se: 62.3%, AUC=0,87, CI:0.80-0.93, p<10-3), NLR (Sp: 87.1%, Se: 61%, AUC=0.81, CI: 0.731- 0.902, p <10-3) and Fibrinogen (Sp: 84.7%, Se:68.3%, AUC=0.77, CI: 0.65 – 0.98, p<10-3).The combination of CRP and NLR levels improved the diagnostic accuracy (AUC 0.93, 95% CI 0.84–0.96; p< 10-3) for distinguishing between infectious and non-infectious diseases.
Conclusions: Our study is characterized by the variety of included disease categories. It showed the usefulness of inflammatory biomarkers, particularly the NLR and its combination with CRP, which are low cost and easy to assess, in promoting the diagnostic accuracy to distinguish infections among inflammatory, neoplasia and other diagnoses.
The role of inflammatory biomarkers in the etiological orientation is increasingly under study, and their potential significance is recognized. The role of inflammatory biomarkers in the etiological orientation is increasingly under study, and their potential significance is recognized. We conducted a prospective descriptive and analytical study about the etiological profile of inflammatory biomarkers measured on admission to distinguish infectious diseases, inflammatory diseases and neoplasia.
Data collection:
The following data were collected from hospitalized patients: epidemiological details, history of comorbidities, clinical presentation, the final diagnosis, and inflammatory biomarkers. These biomarkers were as follows: white blood cells (WBC) (normal range: 4000-10000 cell/mm 3), neutrophils (normal range: 1500-7000 cells/mm3), lymphocytes (normal range:1500-4000 cells/mm3), NLR (normal range: 1-3), C-reactive protein (CRP)with normal range < 5mg/L, procalcitonin (normal range<0.1 ng/mL), fibrinogen (normal range: 2-4 g/l), lactate < 2mmol/L and ferritinemia ( normal range in men < 300 µg/L and in women < 200 µg/L). PCT positive level for infectious diseases was > 0.25 ng/ml. In the SPSS file, we made quantitative variables which are the inflammatory biomarkers count, then we made qualitative variable (the name of the variable + the word analyse) to define if the count is elevated or not. Elderly subjects were defined as those aged 65 and over
Missing data: The empty cells mean that we didn’t get the result of the inflammatory biomarker.
Statistical analysis:
Statistical analysis was performed using the Statistical Package for Social Sciences (SPSS®), version: 26.0.for Windows. Qualitative variables were described by their frequencies and percentages and quantitative variables by their means and standard deviation when the distribution was Gaussian and the median and the interquartile range [25th percentile - 75th percentile] otherwise. For the association of categorical variables, the Chi-square test was used. Student’s T test for independent samples was used to compare means. We considered a p<0.05 as statistically significant. The optimal cut-off values for the sensitivities and specificities to the infectious diseases of the NLR, CRP and PCT, were determined using the receiver operating curve (ROC) analysis and Youden’s index. The diagnostic accuracy of biomarkers and their combinations for predicting infectious etiologies was calculated by area under the curve (AUC). Patients were assigned into 4 groups: Group 1 (G1): infectious diseases, Group 2 (G2): inflammatory diseases (connective tissue diseases, vasculitis, granulomatosis…), Group 3 (G3): Neoplasia, and Group 4 (G4): other diseases. The non-infectious etiologies combined inflammatory diseases, neoplasia and other diagnoses. We carried out a comparative study of inflammatory biomarkers among the four categories, compared their mean levels among infectious and non-infectious diseases, and determined their cut-offs to discriminate infectious diseases.
Procalcitonin (PCT), neutrophil-lymphocyte ratio (NLR), C-reactive-protein (CRP), fibrinogen, ferritinaemia and lactate were measured on admission in all patients. The optimal cut-off values for the sensitivities and specificities to the infectious diseases were determined using the receiver operating curve(ROC) analysis and Youden's index. The diagnostic accuracy of biomarkers and their combinations for predicting infectious etiologies was calculated by area under the curve(AUC).