title: Which observations from the complete blood cell count predict mortality for hospitalized patients?
abstract: BACKGROUND
  Information on the prognostic utility of the admission complete blood count (CBC) and differential count is lacking.
  
  
  OBJECTIVE
  To identify independent predictors of mortality from the varied number and morphology of cells in the complete blood count defined as a hemogram, automated five cell differential count and manual differential count.
  
  
  METHODS
  Retrospective cohort study and chart review.
  
  
  METHODS
  Wishard Memorial Hospital, a large urban primary care hospital.
  
  
  METHODS
  A total of 46,522 adult inpatients admitted over 10 years to Wishard Memorial Hospital-from January 1993 through December 2002.
  
  
  METHODS
  None.
  
  
  METHODS
  Thirty-day mortality measured from day of admission as determined by electronic medical records and Indiana State death records.
  
  
  RESULTS
  Controlling for age and sex, the multivariable regression model identified 3 strong independent predictors of 30-day mortality-nucleated red blood cells (NRBCs), burr cells, and absolute lymphocytosis-each of which was associated with a 3-fold increase in the risk of death within 30 days. The presence of nucleated RBCs was associated with a 30-day mortality rate of 25.5% across a range of diagnoses, excluding patients with sickle-cell disease and obstetric patients, for whom NRBCs were not associated with increased mortality. Having burr cells was associated with a mortality rate of 27.3% and was found most commonly in patients with renal or liver failure. Absolute lymphocytosis predicted poor outcome in patients with trauma and CNS injury.
  
  
  CONCLUSIONS
  Among patients admitted to Wishard Memorial Hospital, the presence of nucleated RBCs, burr cells, or absolute lymphocytosis at admission was each independently associated with a 3-fold increase in risk of death within 30 days of admission.
authors.affiliation: Regenstrief Institute, Inc. abel.kho@nmff.org
authors.forename: Abel N
authors.initials: AN
authors.lastname: Kho
authors.forename: Siu
authors.initials: S
authors.lastname: Hui
authors.forename: Joe G
authors.initials: JG
authors.lastname: Kesterson
authors.forename: Clement J
authors.initials: CJ
authors.lastname: McDonald
mesh_terms: D000328:Adult; D017677:Age Distribution; D001772:Blood Cell Count / Q000706:statistics & numerical data*; D015331:Cohort Studies; D005260:Female; D017052:Hospital Mortality; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007196:Indiana / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D010343:Patient Admission / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D012044:Regression Analysis; D012189:Retrospective Studies; D012720:Severity of Illness Index; D017678:Sex Distribution