Manual differential cell counts help predict bacterial infection. A multivariate analysis.

@article{Wile2001ManualDC,
  title={Manual differential cell counts help predict bacterial infection. A multivariate analysis.},
  author={M J Wile and Louis D. Homer and Siegfried G{\"a}hler and Scott Phillips and Jose Antonio Jimenez Millan},
  journal={American journal of clinical pathology},
  year={2001},
  volume={115 5},
  pages={
          644-9
        }
}
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… CONTINUE READING
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