Manual Differential Cell Counts Help Predict Bacterial Infection

Abstract

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.

Mean cell volumes of neutrophils and monocytes are promising markers of sepsis in elderly patients

“…WBC count as well as the percentage of neutrophils and immature granulocytes can be measured using automated hematology analyzers and have been used to predict infection [4]. Manual PB examination can also provide useful diagnostic information such as morphologic changes in neutrophils, including toxic granulation, toxic vacuolization, and the presence of Döhle bodies [14].…”

“…However, manual slide differential counting is labor-intensive and time-consuming. Furthermore, the 100-cell differential count has problems associated with imprecision, insensitivity, interobserver variation, and variation owing to the heterogeneous distribution of leukocytes on blood films [4]. …”

“…WBC count is routinely recommended as an initial screening marker. Elevated WBC and absolute neutrophil count as well as left-shifted neutrophils are associated with sepsis [4]. These parameters can be determined using an automated hematology analyzer, but the morphology of neutrophils should also be reviewed through peripheral blood (PB) smears.…”

Neutrophils: Neglected Players in Viral Diseases

“…Neutrophils have been used as diagnostic tools in clinical settings: neutrophil absolute count (Wile et al, 2001;Pratt and Attia, 2007;Bressan et al, 2010;Manzano et al, 2011), enumeration of band neutrophils (band count) (Seebach et al, 1997;Al-Gwaiz and Babay, 2007), and the expression levels of neutrophil surface proteins (Nupponen et Rudensky et al, 2008;Dilli et al, 2010;Genel et al, 2012;Jia et al, 2013) to predict bacterial infections and severity outcomes. Due to the increasing evidence of neutrophils being involved in mediating viral diseases (Tumpey et al, 2005;Duffy et al, 2012), it is now possible to develop new diagnostic tools capable of distinguishing between viral and bacterial diseases.…”

Haematology- From CBC to CPD

“…The cell population data of normal leucocytes is generated by these instruments. The cell population data or CPD are research population data ,also known as "Investigation screen parameters" which can be of help in diagnosing and predicting variety of infections and malignancies like bacterial infections and sepsis, malaria, dengue, viral infections some types of anemia's like megaloblastic anemia's, myelodysplastic syndromes, lymph proliferative and myeloproliferative disorders and several plated related disorders [5,6]. These CPD consist of volumes of neutrophils, lymphocytes and monocytes (MMoV, MNeV, MLyV) and their standard deviations (SD).…”