Manual Differential Cell Counts Help Predict Bacterial Infection
| Autor: | Juan C. Millan, Louis D. Homer, Stede Gaehler, Michael J. Wile, Shirley E. Phillips |
|---|---|
| Rok vydání: | 2001 |
| Předmět: |
Adult
medicine.medical_specialty Multivariate analysis Adolescent Neutrophils Logistic regression Leukocyte Count Predictive Value of Tests Internal medicine Humans Medicine Child Aged Aged 80 and over Receiver operating characteristic medicine.diagnostic_test business.industry Immature Granulocyte Infant Newborn Infant Complete blood count Bacterial Infections Hematology General Medicine Middle Aged Band counts Logistic Models ROC Curve Child Preschool Predictive value of tests Multivariate Analysis Immunology Absolute neutrophil count business |
| Zdroj: | American Journal of Clinical Pathology. 115:644-649 |
| ISSN: | 1943-7722 0002-9173 |
| Popis: | We developed logistic regression models that combine information from the automated CBC and manual 100-cell differential counts to predict bacterial infection. The logistic models were fitted from a case group of 116 patients with proven bacterial infection and a control group of 930 presumably uninfected outpatients. A 4-variable, 15-parameter model, which includes automated absolute neutrophil, manual band, and manual immature granulocyte counts, performed best with a receiver operating characteristic (ROC) curve area of 89%. A more practical 2-variable model including automated absolute neutrophil and manual band counts performed almost as well with an ROC curve area of 86%. The automated neutrophil count-only model is less informative with an ROC curve area of 78%. The combined information from automated and manual differential cell counts more accurately predicts bacterial infection than automated counting alone. Despite these modest improvements, the high cost of manual differential cell counts dictates careful patient selection. The supplemental information gained from manual differential counts is most useful for patients with low to normal neutrophil counts (8,000/microL [8.0 x 10(9)/L] or less). Further studies are indicated to determine the characteristic patient populations deriving maximal benefit from this information. |
| Databáze: | OpenAIRE |
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