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Eosinopenia as predictor of infection in patients admitted to an internal medicine ward: a cross-sectional study

BACKGROUND: The identification of infection in an internal medicine ward is crucial but not always straightforward. Eosinopenia has been proposed as a marker of infection, but specific cutoffs for prediction are not established yet. We aim to assess whether there is difference in eosinophil count be...

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Detalles Bibliográficos
Autores principales: Silva, João M., Costa, Artur M., Tuna, Célia, Gonçalves, Renato, Ferreira, Sara, Belém, Francisco, Evangelista, Maria C., Ascensão, Margarida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665260/
https://www.ncbi.nlm.nih.gov/pubmed/33204891
http://dx.doi.org/10.1097/j.pbj.0000000000000084
Descripción
Sumario:BACKGROUND: The identification of infection in an internal medicine ward is crucial but not always straightforward. Eosinopenia has been proposed as a marker of infection, but specific cutoffs for prediction are not established yet. We aim to assess whether there is difference in eosinophil count between infected and noninfected patients and, if so, the best cutoffs to differentiate them. METHODS: Cross-sectional, observational study with analysis of all patients admitted to an Internal Medicine Department during 2 consecutive months. Clinical, laboratory and imaging data were analyzed. Infection at hospital admission was defined in the presence of either a microbiological isolation or suggestive clinical, laboratory, and/or imaging findings. Use of antibiotics in the 8 days before hospital admission, presence of immunosuppression, hematologic neoplasms, parasite, or fungal infections were exclusion criteria. In case of multiple hospital admissions, only the first admission was considered. Sensitivity and specificity values for eosinophils, leukocytes, neutrophils, and C-reactive protein were determined by receiver operating characteristic curve. Statistical analysis was performed with IBM SPSS Statistics® v25 and MedCalc Statistical Software® v19.2.3. RESULTS: A total of 323 hospitalization episodes were evaluated, each corresponding to a different patient. One hundred fifteen patients were excluded. A total of 208 patients were included, 62.0% (n = 129) of them infected at admission. Ten patients had multiple infections. Infected patients had fewer eosinophils than uninfected patients (15.8 ± 42 vs 71.1 ± 159 cell/mm(3); P < .001). An eosinophil count at admission ≤69 cell/mm(3) had a sensitivity of 89.1% and specificity of 54.4% (area under the curve 0.752; 95% confidence interval 0.682–0.822) for the presence of infection. Eosinophil count of >77 cells/mm(3) had a negative likelihood ratio of 0.16. CONCLUSIONS: Eosinophil count was significantly lower in infected than in uninfected patients. The cutoff 69 cells/mm(3) was the most accurate in predicting infection. Eosinophil count >77 cells/mm(3) was a good predictor of absence of infection.